Analyzes competitor prices from search queries and suggests optimal pricing using Bayesian methods and AI to maximize profit
Size
157.4 KB
Version
2.1.70
Created
Jan 12, 2026
Updated
3 months ago
1// ==UserScript==
2// @name OZON Price Optimizer with Competitor Analysis
3// @description Analyzes competitor prices from search queries and suggests optimal pricing using Bayesian methods and AI to maximize profit
4// @version 2.1.70
5// @match https://*.ozon.ru/*
6// @icon https://st.ozone.ru/assets/favicon.ico
7// @grant GM.getValue
8// @grant GM.setValue
9// @grant GM.xmlhttpRequest
10// @require https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js
11// ==/UserScript==
12(function() {
13 'use strict';
14
15 console.log('🚀🚀🚀 OZON PRICE OPTIMIZER VERSION 2.0.1 LOADED 🚀🚀🚀');
16
17 // Product data mapping (артикул -> себестоимость, комиссия, доставка)
18 const PRODUCT_DATA = {
19'1740824669': { cost: 146.4, commission: 0.39, delivery: 105 },
20 '1157786755': { cost: 159.6, commission: 0.39, delivery: 105 },
21 '1126896590': { cost: 111.6, commission: 0.39, delivery: 105 },
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323 '235824492': { cost: 105.6, commission: 0.3, delivery: 90 },
324 '912117351': { cost: 153.6, commission: 0.3, delivery: 90 },
325 '1162577837': { cost: 117.6, commission: 0.3, delivery: 90 },
326 '838273559': { cost: 163.2, commission: 0.3, delivery: 90 },
327 '953470782': { cost: 134.4, commission: 0.3, delivery: 90 },
328 '1591125774': { cost: 328.8, commission: 0.3, delivery: 90 },
329 '1239742307': { cost: 139.2, commission: 0.3, delivery: 90 },
330 '422559168': { cost: 159.6, commission: 0.3, delivery: 90 },
331 '1581558117': { cost: 117.6, commission: 0.3, delivery: 90 },
332 '697870104': { cost: 92.4, commission: 0.3, delivery: 90 },
333 '561033759': { cost: 112.8, commission: 0.3, delivery: 90 },
334 '1696256652': { cost: 115.2, commission: 0.3, delivery: 90 },
335 '2925806092': { cost: 0, commission: 0.3, delivery: 90 },
336 '1911238277': { cost: 103.2, commission: 0.3, delivery: 90 },
337 '282398558': { cost: 123.6, commission: 0.3, delivery: 90 },
338 '1880336894': { cost: 340.8, commission: 0.3, delivery: 90 },
339 '1394598690': { cost: 127.2, commission: 0.3, delivery: 90 },
340 '1161957584': { cost: 141.6, commission: 0.3, delivery: 90 },
341 '697830627': { cost: 182.4, commission: 0.3, delivery: 90 },
342 '307964008': { cost: 94.8, commission: 0.3, delivery: 90 },
343 '254895676': { cost: 112.8, commission: 0.3, delivery: 90 },
344 '1417478667': { cost: 124.8, commission: 0.3, delivery: 90 },
345 '1609652145': { cost: 144, commission: 0.3, delivery: 90 },
346 '1010086939': { cost: 141.6, commission: 0.3, delivery: 90 },
347 '952853707': { cost: 128.4, commission: 0.3, delivery: 90 },
348 '1665302366': { cost: 224.4, commission: 0.3, delivery: 90 },
349 '302361373': { cost: 104.4, commission: 0.3, delivery: 90 },
350 '952754284': { cost: 144.54, commission: 0.3, delivery: 90 },
351 '273926369': { cost: 88.8, commission: 0.3, delivery: 90 },
352 '838115048': { cost: 164.4, commission: 0.3, delivery: 90 },
353 '838251281': { cost: 103.788, commission: 0.3, delivery: 90 },
354 '732238010': { cost: 148.8, commission: 0.3, delivery: 90 },
355 '445989855': { cost: 85.2, commission: 0.3, delivery: 90 },
356 '269076077': { cost: 301.452, commission: 0.3, delivery: 90 },
357 '257568474': { cost: 73.2, commission: 0.3, delivery: 90 },
358 '954664346': { cost: 129.6, commission: 0.3, delivery: 90 },
359 '254600991': { cost: 132, commission: 0.3, delivery: 90 },
360 '772640606': { cost: 106.8, commission: 0.3, delivery: 90 },
361 '955283837': { cost: 182.4, commission: 0.3, delivery: 90 },
362 '254686077': { cost: 174, commission: 0.3, delivery: 90 },
363 '1394711785': { cost: 144, commission: 0.3, delivery: 90 },
364 '257884238': { cost: 130.8, commission: 0.3, delivery: 90 },
365 '1620776878': { cost: 157.2, commission: 0.3, delivery: 90 },
366 '951783485': { cost: 132, commission: 0.3, delivery: 90 },
367 '356177679': { cost: 69.6, commission: 0.3, delivery: 90 },
368 '1394612090': { cost: 159.6, commission: 0.3, delivery: 90 },
369 '2897675749': { cost: 0, commission: 0.3, delivery: 90 },
370 '1162445078': { cost: 186, commission: 0.3, delivery: 90 },
371 '1932949948': { cost: 235.2, commission: 0.3, delivery: 90 },
372 '879083250': { cost: 186, commission: 0.3, delivery: 90 },
373 '256466996': { cost: 200.4, commission: 0.3, delivery: 90 },
374 '3006918397': { cost: 313.2, commission: 0.3, delivery: 90 },
375 '1418277399': { cost: 346.8, commission: 0.3, delivery: 90 },
376 '496419419': { cost: 258, commission: 0.3, delivery: 90 },
377 '1007822873': { cost: 134.4, commission: 0.3, delivery: 90 },
378 '608351238': { cost: 120, commission: 0.3, delivery: 90 },
379 '1413857256': { cost: 159.6, commission: 0.3, delivery: 90 },
380 '1787673702': { cost: 150, commission: 0.3, delivery: 90 },
381 '1162216260': { cost: 145.2, commission: 0.3, delivery: 90 },
382 '1413837107': { cost: 87.6, commission: 0.3, delivery: 90 },
383 '768941637': { cost: 171.6, commission: 0.3, delivery: 90 },
384 '1507653510': { cost: 96, commission: 0.3, delivery: 90 },
385 '1007787669': { cost: 132, commission: 0.3, delivery: 90 },
386 '2352209417': { cost: 283.752, commission: 0.3, delivery: 90 },
387 '1397098991': { cost: 331.2, commission: 0.3, delivery: 90 },
388 '1507630430': { cost: 99.6, commission: 0.3, delivery: 90 },
389 '1189589105': { cost: 130.8, commission: 0.3, delivery: 90 },
390 '1506037461': { cost: 470.4, commission: 0.3, delivery: 90 },
391 '1162348932': { cost: 194.4, commission: 0.3, delivery: 90 },
392 '2975103256': { cost: 163.056, commission: 0.3, delivery: 90 },
393 '1506047716': { cost: 171.6, commission: 0.3, delivery: 90 },
394 '911292485': { cost: 112.8, commission: 0.3, delivery: 90 },
395 '1880333546': { cost: 364.8, commission: 0.3, delivery: 90 },
396 '1608793966': { cost: 132, commission: 0.3, delivery: 90 },
397 '1880315436': { cost: 344.4, commission: 0.3, delivery: 90 },
398 '2352282340': { cost: 283.752, commission: 0.3, delivery: 90 },
399 '709600226': { cost: 129.6, commission: 0.3, delivery: 90 },
400 '3016287234': { cost: 274.8, commission: 0.3, delivery: 90 },
401 '3016266763': { cost: 240, commission: 0.3, delivery: 90 },
402 '3026343193': { cost: 283.2, commission: 0.3, delivery: 90 },
403 '3011261105': { cost: 208.8, commission: 0.3, delivery: 90 },
404 '3026384906': { cost: 309.6, commission: 0.3, delivery: 90 },
405 '1303951724': { cost: 67.2, commission: 0.3, delivery: 90 },
406 '3026360459': { cost: 310.8, commission: 0.3, delivery: 90 },
407 '951614842': { cost: 116.4, commission: 0.3, delivery: 90 },
408 '1758263220': { cost: 776.4, commission: 0.3, delivery: 90 },
409 '1162674702': { cost: 152.4, commission: 0.3, delivery: 90 },
410 '236327983': { cost: 120, commission: 0.3, delivery: 90 },
411 '256416463': { cost: 104.4, commission: 0.3, delivery: 90 },
412 '1790465865': { cost: 62.4, commission: 0.3, delivery: 90 },
413 '2975215156': { cost: 163.056, commission: 0.3, delivery: 90 },
414 '1005952104': { cost: 94.8, commission: 0.3, delivery: 90 },
415 '399215466': { cost: 102, commission: 0.3, delivery: 90 },
416 '1162300125': { cost: 116.4, commission: 0.3, delivery: 90 },
417 '1005952110': { cost: 93.6, commission: 0.3, delivery: 90 },
418 '496044796': { cost: 116.4, commission: 0.3, delivery: 90 },
419 '203389028': { cost: 166.8, commission: 0.3, delivery: 90 },
420 '1005550551': { cost: 96, commission: 0.3, delivery: 90 },
421 '203480472': { cost: 94.8, commission: 0.3, delivery: 90 },
422 '203473290': { cost: 121.2, commission: 0.3, delivery: 90 },
423 '1620772534': { cost: 321.6, commission: 0.3, delivery: 90 },
424 '282469378': { cost: 100.8, commission: 0.3, delivery: 90 },
425 '1805671797': { cost: 58.8, commission: 0.3, delivery: 90 },
426 '203350791': { cost: 134.4, commission: 0.3, delivery: 90 },
427 '1394625221': { cost: 129.6, commission: 0.3, delivery: 90 },
428 '301908659': { cost: 111.6, commission: 0.3, delivery: 90 },
429 '1507673120': { cost: 253.2, commission: 0.36, delivery: 200 },
430 '1239609957': { cost: 123.6, commission: 0.36, delivery: 200 },
431 '1006163518': { cost: 188.4, commission: 0.36, delivery: 200 },
432 '1422925703': { cost: 252, commission: 0.36, delivery: 200 },
433 '1572975136': { cost: 547.2, commission: 0.36, delivery: 200 },
434 '2394561998': { cost: 106.8, commission: 0.36, delivery: 200 },
435 '838220448': { cost: 136.8, commission: 0.36, delivery: 200 },
436 '543848911': { cost: 228, commission: 0.36, delivery: 200 },
437 '1020579419': { cost: 88.8, commission: 0.36, delivery: 200 },
438 '557726786': { cost: 217.2, commission: 0.36, delivery: 200 },
439 '1608785751': { cost: 176.4, commission: 0.36, delivery: 200 },
440 '1020578939': { cost: 92.4, commission: 0.36, delivery: 200 },
441 '519816761': { cost: 231.6, commission: 0.36, delivery: 200 },
442 '1673659402': { cost: 1267, commission: 0.36, delivery: 200 },
443 '501441185': { cost: 216, commission: 0.36, delivery: 200 },
444 '860254877': { cost: 223.2, commission: 0.36, delivery: 200 },
445 '774068400': { cost: 358.8, commission: 0.36, delivery: 200 },
446 '519740742': { cost: 216, commission: 0.36, delivery: 200 },
447 '1673650914': { cost: 1537, commission: 0.36, delivery: 200 },
448 '519734762': { cost: 234, commission: 0.36, delivery: 200 },
449 '1558177759': { cost: 366, commission: 0.36, delivery: 200 },
450 '1558176776': { cost: 421.2, commission: 0.36, delivery: 200 },
451 '643844171': { cost: 112.8, commission: 0.36, delivery: 200 },
452 '519732586': { cost: 98.4, commission: 0.36, delivery: 200 },
453 '1019659629': { cost: 91.2, commission: 0.36, delivery: 200 },
454 '1673649384': { cost: 1517, commission: 0.36, delivery: 200 },
455 '860261495': { cost: 240, commission: 0.36, delivery: 200 },
456 '1880450237': { cost: 271.2, commission: 0.36, delivery: 200 },
457 '1558174139': { cost: 372, commission: 0.36, delivery: 200 },
458 '1845802065': { cost: 768, commission: 0.36, delivery: 200 },
459 '1673647587': { cost: 1497, commission: 0.36, delivery: 200 },
460 '557670932': { cost: 392.4, commission: 0.36, delivery: 200 },
461 '1979738121': { cost: 637.2, commission: 0.36, delivery: 200 },
462 '1020579926': { cost: 88.8, commission: 0.36, delivery: 200 },
463 '1880440770': { cost: 273.6, commission: 0.36, delivery: 200 },
464 '1979755177': { cost: 662.4, commission: 0.36, delivery: 200 },
465 '2898154255': { cost: 124.8, commission: 0.36, delivery: 200 },
466 '2899553513': { cost: 145.2, commission: 0.36, delivery: 200 },
467 '1846354292': { cost: 768, commission: 0.36, delivery: 200 },
468 '1880410608': { cost: 285.6, commission: 0.36, delivery: 200 },
469 '2898115411': { cost: 136.8, commission: 0.36, delivery: 200 },
470 '1880442651': { cost: 270, commission: 0.36, delivery: 200 },
471 '501438861': { cost: 220.8, commission: 0.36, delivery: 200 },
472 '1397099331': { cost: 372, commission: 0.36, delivery: 200 },
473 '1846363096': { cost: 768, commission: 0.36, delivery: 200 },
474 '2631471568': { cost: 685.2, commission: 0.36, delivery: 200 },
475 '1911710527': { cost: 276, commission: 0.36, delivery: 200 },
476 '1911695310': { cost: 267.6, commission: 0.36, delivery: 200 },
477 '1911704413': { cost: 264, commission: 0.36, delivery: 200 },
478 '1020579746': { cost: 90, commission: 0.36, delivery: 200 },
479 '335431876': { cost: 51.6, commission: 0.36, delivery: 200 },
480 '439685200': { cost: 55.2, commission: 0.36, delivery: 200 },
481 '1019698970': { cost: 88.8, commission: 0.36, delivery: 200 },
482 '439692165': { cost: 55.2, commission: 0.36, delivery: 200 },
483 '335431975': { cost: 54, commission: 0.36, delivery: 200 },
484 '335446268': { cost: 52.8, commission: 0.36, delivery: 200 },
485 '1846315219': { cost: 768, commission: 0.36, delivery: 200 },
486 '335440088': { cost: 61.2, commission: 0.36, delivery: 200 },
487 '838167533': { cost: 106.8, commission: 0.3, delivery: 90 },
488 '878312141': { cost: 265.2, commission: 0.36, delivery: 200 },
489 '1572991087': { cost: 290.4, commission: 0.36, delivery: 200 },
490 '1521855158': { cost: 104.4, commission: 0.3, delivery: 90 },
491 '646434083': { cost: 252, commission: 0.3, delivery: 90 },
492 '646441179': { cost: 273.6, commission: 0.3, delivery: 90 },
493 '2352128160': { cost: 340.8, commission: 0.36, delivery: 200 },
494 '446010027': { cost: 344.4, commission: 0.3, delivery: 90 },
495 '1773177807': { cost: 192, commission: 0.36, delivery: 200 },
496 '1980328072': { cost: 338.4, commission: 0.36, delivery: 200 },
497 '646441673': { cost: 258, commission: 0.3, delivery: 90 },
498 '772524320': { cost: 131.64, commission: 0.3, delivery: 90 },
499 '302573933': { cost: 258, commission: 0.3, delivery: 90 },
500 '824213857': { cost: 172.8, commission: 0.3, delivery: 90 },
501 '1609643510': { cost: 175.2, commission: 0.3, delivery: 90 },
502 '439749049': { cost: 357.6, commission: 0.3, delivery: 90 },
503 '496064096': { cost: 230.052, commission: 0.3, delivery: 90 },
504 '732341657': { cost: 205.2, commission: 0.36, delivery: 200 },
505 '955327749': { cost: 146.4, commission: 0.3, delivery: 90 },
506 '1787680920': { cost: 230.4, commission: 0.3, delivery: 90 },
507 '2352063264': { cost: 285.6, commission: 0.36, delivery: 200 },
508 '2352107373': { cost: 321.6, commission: 0.36, delivery: 200 },
509 '1521854115': { cost: 177.6, commission: 0.3, delivery: 90 },
510 '240602548': { cost: 128.4, commission: 0.3, delivery: 90 },
511 '1239644265': { cost: 207.6, commission: 0.3, delivery: 90 },
512 '203465007': { cost: 124.8, commission: 0.36, delivery: 200 },
513 '1937534346': { cost: 144, commission: 0.3, delivery: 90 },
514 '1979698296': { cost: 324, commission: 0.36, delivery: 200 },
515 '256430704': { cost: 99.6, commission: 0.3, delivery: 90 },
516 '1505980019': { cost: 183.6, commission: 0.3, delivery: 90 }
517 };
518
519 // Extract product ID from URL
520 function getProductId() {
521 const match = window.location.href.match(/product\/[^\/]+-(\d+)/);
522 return match ? match[1] : null;
523 }
524
525 // Get short SKU from full product ID (last 5 digits)
526 function getShortSku(fullProductId) {
527 if (PRODUCT_DATA[fullProductId]) {
528 return fullProductId;
529 }
530
531 const last5 = fullProductId.slice(-5);
532 if (PRODUCT_DATA[last5]) {
533 return last5;
534 }
535
536 const last6 = fullProductId.slice(-6);
537 if (PRODUCT_DATA[last6]) {
538 return last6;
539 }
540
541 return null;
542 }
543
544 // Extract daily price and sales data from MP Stats chart
545 async function extractDailyDataFromChart(widget) {
546 console.log('>>> extractDailyDataFromChart CALLED (ECharts version) <<<');
547
548 try {
549 const dailyData = [];
550
551 // Find ECharts canvas elements
552 const canvases = widget.querySelectorAll('canvas[data-zr-dom-id]');
553 console.log('Found ECharts canvas elements:', canvases.length);
554
555 if (canvases.length === 0) {
556 console.log('No canvas charts found');
557 return dailyData;
558 }
559
560 const salesCanvas = canvases[0];
561 console.log('Analyzing sales chart (Canvas 0)...');
562
563 const rect = salesCanvas.getBoundingClientRect();
564 console.log('Canvas rect:', rect);
565
566 const seenDates = new Set();
567
568 // Try 30 points (30 days) with multiple Y positions
569 for (let day = 0; day < 30; day++) {
570 let found = false;
571
572 // Try different Y positions (top to bottom) to hit the bars
573 for (let yOffset = 0.2; yOffset <= 0.8 && !found; yOffset += 0.15) {
574 const xPos = rect.left + (rect.width * ((day + 0.5) / 30));
575 const yPos = rect.top + rect.height * yOffset;
576
577 salesCanvas.dispatchEvent(new MouseEvent('mousemove', {
578 bubbles: true,
579 cancelable: true,
580 view: window,
581 clientX: xPos,
582 clientY: yPos
583 }));
584
585 await new Promise(resolve => setTimeout(resolve, 150));
586
587 // Find tooltip with sales and price data
588 const allElements = Array.from(document.querySelectorAll('*'));
589 const tooltip = allElements.find(el => {
590 const text = el.textContent;
591 return text.includes('Продажи:') && text.includes('Цена:') &&
592 window.getComputedStyle(el).position === 'absolute';
593 });
594
595 if (tooltip) {
596 const text = tooltip.textContent;
597 const salesMatch = text.match(/Продажи:\s*(\d+)\s*шт/);
598 const priceMatch = text.match(/Цена:\s*(\d+)\s*₽/);
599 const dateMatch = text.match(/(\d+)\s+(января|февраля|марта|апреля|мая|июня|июля|августа|сентября|октября|ноября|декабря)\s+(\d+)/);
600
601 if (salesMatch && priceMatch && dateMatch) {
602 const dateKey = dateMatch[0];
603 if (!seenDates.has(dateKey)) {
604 seenDates.add(dateKey);
605 const sales = parseInt(salesMatch[1]);
606 const price = parseInt(priceMatch[1]);
607
608 dailyData.push({
609 day: dailyData.length + 1,
610 date: dateKey,
611 sales: sales,
612 price: price
613 });
614
615 console.log(`Day ${dailyData.length}: ${dateKey} - ${sales} шт @ ${price}₽`);
616 found = true;
617 }
618 }
619 }
620 }
621 }
622
623 console.log(`Total extracted daily data points: ${dailyData.length}`);
624 console.log('Sample data - First 5 days:', dailyData.slice(0, 5));
625 console.log('Sample data - Last 5 days:', dailyData.slice(-5));
626 return dailyData;
627
628 } catch (error) {
629 console.error('Error extracting daily data:', error);
630 return [];
631 }
632 }
633
634 // Extract stock data from MP Stats stock chart
635 async function extractStockData(widget) {
636 console.log('Extracting stock data from MP Stats (ECharts version)...');
637
638 if (!widget) {
639 console.error('Widget not provided to extractStockData');
640 return null;
641 }
642
643 // Find ECharts canvas elements
644 const canvases = widget.querySelectorAll('canvas[data-zr-dom-id]');
645 console.log(`Found ${canvases.length} canvas charts for stock data`);
646
647 if (!canvases || canvases.length < 4) {
648 console.error(`Stock chart canvas not found - only ${canvases ? canvases.length : 0} charts available, need at least 4`);
649 return null;
650 }
651
652 const stockCanvas = canvases[3];
653 console.log('Analyzing stock chart (Canvas 3)...');
654
655 const rect = stockCanvas.getBoundingClientRect();
656 console.log('Stock canvas rect:', rect);
657
658 const stockPoints = [];
659 const seenDates = new Set();
660 console.log('Starting stock tooltip extraction...');
661
662 // Try 30 points (30 days) with multiple Y positions
663 for (let day = 0; day < 30; day++) {
664 let found = false;
665
666 // Try different Y positions (top to bottom) to hit the bars
667 for (let yOffset = 0.2; yOffset <= 0.8 && !found; yOffset += 0.15) {
668 const xPos = rect.left + (rect.width * ((day + 0.5) / 30));
669 const yPos = rect.top + rect.height * yOffset;
670
671 stockCanvas.dispatchEvent(new MouseEvent('mousemove', {
672 bubbles: true,
673 cancelable: true,
674 view: window,
675 clientX: xPos,
676 clientY: yPos
677 }));
678
679 await new Promise(resolve => setTimeout(resolve, 150));
680
681 // Find tooltip with stock data
682 const allElements = Array.from(document.querySelectorAll('*'));
683 const tooltip = allElements.find(el => {
684 const text = el.textContent;
685 return text.includes('Остаток:') && text.includes('шт') &&
686 window.getComputedStyle(el).position === 'absolute';
687 });
688
689 if (tooltip) {
690 const text = tooltip.textContent;
691 const stockMatch = text.match(/Остаток:\s*(\d+)\s*шт/);
692 const dateMatch = text.match(/(\d+)\s+(января|февраля|марта|апреля|мая|июня|июля|августа|сентября|октября|ноября|декабря)\s+(\d+)/);
693
694 if (stockMatch && dateMatch) {
695 const dateKey = dateMatch[0];
696 if (!seenDates.has(dateKey)) {
697 seenDates.add(dateKey);
698 const stock = parseInt(stockMatch[1]);
699
700 stockPoints.push({
701 day: stockPoints.length + 1,
702 date: dateKey,
703 stock: stock
704 });
705
706 console.log(`Stock Day ${stockPoints.length}: ${dateKey} - ${stock} шт`);
707 found = true;
708 }
709 }
710 }
711 }
712 }
713
714 console.log(`Extracted ${stockPoints.length} days of stock data from chart`);
715 console.log('Stock data sample - First 5 days:', stockPoints.slice(0, 5));
716 console.log('Stock data sample - Last 5 days:', stockPoints.slice(-5));
717 return stockPoints;
718 }
719
720 // NEW: Filter outliers using IQR method
721 function filterOutliers(dataPoints) {
722 console.log('=== FILTERING OUTLIERS (IQR Method) ===');
723 console.log('Original data points:', dataPoints.length);
724
725 if (!dataPoints || dataPoints.length < 5) {
726 console.log('Not enough data for outlier filtering');
727 return dataPoints;
728 }
729
730 // Step 1: Remove zero sales
731 let filtered = dataPoints.filter(d => d.sales > 0);
732 console.log(`After removing zero sales: ${filtered.length} points (removed ${dataPoints.length - filtered.length})`);
733
734 if (filtered.length < 5) {
735 console.log('Not enough data after removing zero sales');
736 return filtered;
737 }
738
739 // Step 2: IQR filtering for prices
740 const prices = filtered.map(d => d.price).sort((a, b) => a - b);
741 const priceQ1 = prices[Math.floor(prices.length * 0.25)];
742 const priceQ3 = prices[Math.floor(prices.length * 0.75)];
743 const priceIQR = priceQ3 - priceQ1;
744 const priceLowerBound = priceQ1 - 1.5 * priceIQR;
745 const priceUpperBound = priceQ3 + 1.5 * priceIQR;
746
747 console.log(`Price IQR: Q1=${priceQ1}, Q3=${priceQ3}, IQR=${priceIQR}`);
748 console.log(`Price bounds: [${priceLowerBound}, ${priceUpperBound}]`);
749
750 filtered = filtered.filter(d => d.price >= priceLowerBound && d.price <= priceUpperBound);
751 console.log(`After price outlier removal: ${filtered.length} points`);
752
753 if (filtered.length < 5) {
754 console.log('Not enough data after price filtering');
755 return filtered;
756 }
757
758 // Step 3: IQR filtering for sales
759 const sales = filtered.map(d => d.sales).sort((a, b) => a - b);
760 const salesQ1 = sales[Math.floor(sales.length * 0.25)];
761 const salesQ3 = sales[Math.floor(sales.length * 0.75)];
762 const salesIQR = salesQ3 - salesQ1;
763 const salesLowerBound = salesQ1 - 1.5 * salesIQR;
764 const salesUpperBound = salesQ3 + 1.5 * salesIQR;
765
766 console.log(`Sales IQR: Q1=${salesQ1}, Q3=${salesQ3}, IQR=${salesIQR}`);
767 console.log(`Sales bounds: [${salesLowerBound}, ${salesUpperBound}]`);
768
769 const beforeSalesFilter = filtered.length;
770 filtered = filtered.filter(d => d.sales >= salesLowerBound && d.sales <= salesUpperBound);
771 console.log(`After sales outlier removal: ${filtered.length} points (removed ${beforeSalesFilter - filtered.length})`);
772
773 console.log(`=== OUTLIER FILTERING COMPLETE: ${dataPoints.length} → ${filtered.length} points ===`);
774 return filtered;
775 }
776
777 // NEW: Determine product segment based on competitive positioning
778 function determineProductSegment(currentPrice, competitorPrices) {
779 console.log('=== DETERMINING PRODUCT SEGMENT ===');
780
781 if (!competitorPrices || competitorPrices.length === 0) {
782 console.log('No competitor data, defaulting to mid-market segment');
783 return {
784 segment: 'mid-market',
785 description: 'Средний сегмент (нет данных о конкурентах)',
786 strategy: 'Оптимизация прибыли с учетом эластичности спроса'
787 };
788 }
789
790 const prices = competitorPrices.map(c => c.price).sort((a, b) => a - b);
791 const minPrice = Math.min(...prices);
792 const maxPrice = Math.max(...prices);
793 const avgPrice = prices.reduce((a, b) => a + b, 0) / prices.length;
794 const medianPrice = prices[Math.floor(prices.length / 2)];
795
796 console.log(`Price analysis: min=${minPrice}, max=${maxPrice}, avg=${avgPrice.toFixed(0)}, median=${medianPrice}`);
797 console.log(`Current price: ${currentPrice}`);
798
799 const pricePosition = (currentPrice - minPrice) / (maxPrice - minPrice);
800 console.log(`Price position: ${(pricePosition * 100).toFixed(1)}% of range`);
801
802 let segment, description, strategy;
803
804 if (currentPrice < avgPrice * 0.8) {
805 segment = 'budget';
806 description = 'Бюджетный сегмент (цена ниже рынка на 20%+)';
807 strategy = 'Захват доли рынка через низкую цену. Фокус на объёме продаж.';
808 } else if (currentPrice < avgPrice * 0.95) {
809 segment = 'value';
810 description = 'Ценностный сегмент (цена немного ниже среднего)';
811 strategy = 'Баланс цены и качества. Конкурентное преимущество по цене.';
812 } else if (currentPrice <= avgPrice * 1.05) {
813 segment = 'mid-market';
814 description = 'Средний сегмент (цена на уровне рынка)';
815 strategy = 'Оптимизация прибыли. Конкуренция по качеству и сервису.';
816 } else if (currentPrice <= avgPrice * 1.2) {
817 segment = 'premium';
818 description = 'Премиум сегмент (цена выше среднего на 5-20%)';
819 strategy = 'Позиционирование как премиум продукт. Фокус на маржинальности.';
820 } else {
821 segment = 'luxury';
822 description = 'Люкс сегмент (цена выше рынка на 20%+)';
823 strategy = 'Эксклюзивное позиционирование. Максимальная маржа, низкий объём.';
824 }
825
826 console.log(`Segment: ${segment} - ${description}`);
827 console.log(`Strategy: ${strategy}`);
828
829 return { segment, description, strategy };
830 }
831
832 // NEW: Calculate inventory strategy based on days of supply
833 function getInventoryStrategy(daysOfSupply) {
834 console.log('=== CALCULATING INVENTORY STRATEGY ===');
835 console.log(`Days of supply: ${daysOfSupply.toFixed(1)}`);
836
837 let strategy, action, priceAdjustment;
838
839 if (daysOfSupply < 7) {
840 strategy = 'critical_low';
841 action = 'Критически низкий остаток';
842 priceAdjustment = 'НЕ СНИЖАТЬ цену. Можно повысить на 5-10% для максимизации прибыли.';
843 } else if (daysOfSupply <= 30) {
844 strategy = 'low';
845 action = 'Низкий остаток';
846 priceAdjustment = 'Оптимизация прибыли. Небольшое повышение цены допустимо.';
847 } else if (daysOfSupply <= 90) {
848 strategy = 'optimal';
849 action = 'Оптимальный остаток';
850 priceAdjustment = 'Стандартная оптимизация прибыли по эластичности спроса.';
851 } else if (daysOfSupply <= 180) {
852 strategy = 'high';
853 action = 'Высокий остаток';
854 priceAdjustment = 'Можно снижать цену для ускорения продаж и освобождения склада.';
855 } else {
856 strategy = 'critical_high';
857 action = 'Критически высокий остаток';
858 priceAdjustment = 'АГРЕССИВНОЕ снижение цены! Риск затоваривания и списания.';
859 }
860
861 console.log(`Strategy: ${strategy} - ${action}`);
862 console.log(`Price adjustment: ${priceAdjustment}`);
863
864 return { strategy, action, priceAdjustment, daysOfSupply };
865 }
866
867 // NEW: Extract competitors from search query
868 async function extractCompetitorsFromSearch(keyQuery) {
869 console.log('=== START extractCompetitorsFromSearch ===');
870 console.log('Key query:', keyQuery);
871
872 try {
873 // Encode query for URL
874 const encodedQuery = encodeURIComponent(keyQuery);
875 const searchUrl = `https://www.ozon.ru/search/?text=${encodedQuery}&from_global=true`;
876
877 console.log('Opening search URL in new tab:', searchUrl);
878 console.log('⚠️ ВАЖНО: Новая вкладка откроется для сбора данных о конкурентах. Пожалуйста, не закрывайте её - она закроется автоматически.');
879
880 // Open search page in new tab (in foreground so user can see it)
881 await GM.openInTab(searchUrl, true);
882
883 // Wait for new tab to load and process
884 console.log('Waiting for search page to load...');
885
886 // The new tab will handle extraction and save to storage
887 // This function just initiates the process
888 return null;
889
890 } catch (error) {
891 console.error('Error in extractCompetitorsFromSearch:', error);
892 return null;
893 }
894 }
895
896 // NEW: Extract competitors in search page context
897 async function extractCompetitorsInSearchPage() {
898 console.log('=== extractCompetitorsInSearchPage CALLED ===');
899
900 // Check if we're on a search or category page
901 if (!window.location.href.includes('/search/') && !window.location.href.includes('/category/')) {
902 console.log('Not on search/category page, skipping competitor extraction');
903 return;
904 }
905
906 // Check if we have a pending analysis state (meaning we came from product page)
907 const stateJson = await GM.getValue('analysis_state', null);
908 if (!stateJson) {
909 console.log('No analysis state found, not extracting competitors');
910 return;
911 }
912
913 const state = JSON.parse(stateJson);
914
915 // Check if state is recent (within 2 minutes)
916 if (Date.now() - state.timestamp > 120000) {
917 console.log('Analysis state is too old, ignoring');
918 await GM.deleteValue('analysis_state');
919 return;
920 }
921
922 console.log('Found analysis state, will extract competitors from this search page');
923 console.log('Our product ID:', state.productId);
924
925 // Wait for MPStats widget to load
926 console.log('Waiting for MPStats widget to load...');
927 let mpstatsWidget = null;
928 let attempts = 0;
929 const maxAttempts = 30;
930
931 while (attempts < maxAttempts && !mpstatsWidget) {
932 await new Promise(resolve => setTimeout(resolve, 1000));
933 mpstatsWidget = document.getElementById('mpstat-ozone-search-result');
934 attempts++;
935 console.log(`Attempt ${attempts}/${maxAttempts} to find MPStats widget...`);
936 }
937
938 if (!mpstatsWidget) {
939 console.error('MPStats widget not found in search results after 30 seconds');
940 // Mark as failed and close tab
941 await GM.setValue('competitors_extracted', 'failed');
942 window.close();
943 return;
944 }
945
946 console.log('MPStats widget found, waiting for data to load...');
947
948 // Wait for table rows to appear
949 let rows = [];
950 attempts = 0;
951
952 while (attempts < 20 && rows.length === 0) {
953 await new Promise(resolve => setTimeout(resolve, 1000));
954 rows = mpstatsWidget.querySelectorAll('tbody tr');
955 attempts++;
956 console.log(`Attempt ${attempts}/20: Found ${rows.length} rows`);
957 }
958
959 if (rows.length === 0) {
960 console.error('No rows found in MPStats table after waiting');
961 await GM.setValue('competitors_extracted', 'failed');
962 window.close();
963 return;
964 }
965
966 console.log(`Found ${rows.length} rows in MPStats table, extracting competitor data...`);
967
968 const competitors = [];
969
970 for (let i = 0; i < rows.length; i++) {
971 const row = rows[i];
972
973 try {
974 // Extract SKU from the third column
975 const skuCell = row.querySelectorAll('td')[2];
976 if (!skuCell) continue;
977
978 const skuText = skuCell.textContent.trim();
979 const sku = skuText.match(/\d+/) ? skuText.match(/\d+/)[0] : null;
980
981 if (!sku) continue;
982
983 // ⚠️ NEW: Skip our own product
984 if (sku === state.productId || sku === state.shortSku) {
985 console.log(`⚠️ Skipping our own product: SKU ${sku}`);
986 continue;
987 }
988
989 // Extract brand from the fourth column
990 const brandCell = row.querySelectorAll('td')[3];
991 if (!brandCell) continue;
992
993 const brand = brandCell.textContent.trim();
994
995 if (!brand || brand.length < 2) continue;
996
997 // Extract price from the fifth column
998 const priceCell = row.querySelectorAll('td')[4];
999 if (!priceCell) continue;
1000
1001 const priceText = priceCell.textContent.trim();
1002 const priceMatch = priceText.match(/(\d[\d\s]*)\s*₽/);
1003 if (!priceMatch) continue;
1004
1005 const price = parseInt(priceMatch[1].replace(/\s/g, ''));
1006 if (isNaN(price) || price < 100 || price > 100000) continue;
1007
1008 // Extract sales from the sixth column (orders per month)
1009 const salesCell = row.querySelectorAll('td')[5];
1010 if (!salesCell) continue;
1011
1012 const salesText = salesCell.textContent.trim();
1013 const sales = parseInt(salesText.replace(/\s/g, ''));
1014 if (isNaN(sales)) continue;
1015
1016 // Calculate revenue
1017 const revenue = price * sales;
1018
1019 if (revenue > 0) {
1020 competitors.push({
1021 brand: brand,
1022 sku: sku,
1023 price: price,
1024 sales30days: sales,
1025 revenue30days: revenue
1026 });
1027
1028 console.log(`Competitor: ${brand} - Price: ${price}₽, Sales: ${sales}, Revenue: ${revenue}₽`);
1029 }
1030
1031 } catch (error) {
1032 console.error(`Error extracting competitor from row ${i}:`, error);
1033 }
1034 }
1035
1036 // Sort by revenue (descending)
1037 competitors.sort((a, b) => b.revenue30days - a.revenue30days);
1038
1039 console.log(`Extracted ${competitors.length} competitors from search (excluding our product)`);
1040 console.log('>>> COMPETITOR PRICES EXTRACTED <<<');
1041 console.log('Competitor count:', competitors.length);
1042 if (competitors.length > 0) {
1043 const prices = competitors.map(c => c.price);
1044 const minCompPrice = Math.min(...prices);
1045 const maxCompPrice = Math.max(...prices);
1046 const avgCompPrice = Math.round(prices.reduce((a, b) => a + b, 0) / prices.length);
1047 console.log('Price range:', minCompPrice, '-', maxCompPrice, '₽');
1048 console.log('Average price:', avgCompPrice, '₽');
1049 console.log('All competitor prices:', prices);
1050 console.log('Top 5 competitors by revenue:', competitors.slice(0, 5).map(c => `${c.brand}: ${c.price}₽, ${c.sales30days} шт, ${c.revenue30days}₽`));
1051 }
1052
1053 // Save competitors to storage
1054 await GM.setValue('temp_competitors', JSON.stringify(competitors));
1055 console.log('Competitors saved to storage');
1056
1057 // Mark that extraction is complete
1058 await GM.setValue('competitors_extracted', 'true');
1059
1060 // Close the tab after successful extraction
1061 console.log('Closing competitor search tab...');
1062 setTimeout(() => {
1063 window.close();
1064 }, 1000);
1065 }
1066
1067 // Extract summary data from MP Stats widget
1068 async function extractMPStatsData() {
1069 console.log('Extracting MP Stats summary data...');
1070
1071 const widget = document.querySelector('.mps-sidebar');
1072 if (!widget) {
1073 console.error('MP Stats widget not found');
1074 return null;
1075 }
1076
1077 const revenueText = widget.textContent.match(/Выручка за 30 суток\s*([\d\s]+)/);
1078 const salesText = widget.textContent.match(/Продаж за 30 суток\s*([\d\s]+)/);
1079 const currentStockText = widget.textContent.match(/Текущий остаток\s*([\d\s]+)/);
1080
1081 if (revenueText && salesText) {
1082 const revenue = parseInt(revenueText[1].replace(/\s/g, ''));
1083 const sales = parseInt(salesText[1].replace(/\s/g, ''));
1084
1085 let avgPrice = revenue / sales;
1086 const webPriceWidget = document.querySelector('[data-widget="webPrice"]');
1087 if (webPriceWidget) {
1088 const priceSpans = webPriceWidget.querySelectorAll('span');
1089 const prices = [];
1090 priceSpans.forEach(span => {
1091 const text = span.textContent.trim();
1092 const match = text.match(/^(\d[\d\s]*)\s*₽$/);
1093 if (match) {
1094 const priceText = match[1].replace(/\s/g, '');
1095 const parsedPrice = parseInt(priceText);
1096 if (!isNaN(parsedPrice) && parsedPrice > 100 && parsedPrice < 100000) {
1097 prices.push(parsedPrice);
1098 }
1099 }
1100 });
1101 if (prices.length > 0) {
1102 avgPrice = Math.min(...prices);
1103 console.log('Found prices in webPrice:', prices, 'Using minimum:', avgPrice);
1104 }
1105 }
1106
1107 const currentStock = currentStockText ? parseInt(currentStockText[1].replace(/\s/g, '')) : 0;
1108
1109 const dataPoints = await extractDailyDataFromChart(widget);
1110
1111 if (!dataPoints || dataPoints.length === 0) {
1112 console.error('Failed to extract chart data');
1113 return null;
1114 }
1115
1116 const stockPoints = await extractStockData(widget);
1117 console.log('Stock points extracted:', stockPoints);
1118
1119 const totalSales = dataPoints.reduce((sum, d) => sum + d.sales, 0);
1120 const avgDailySales = totalSales / dataPoints.length;
1121
1122 let matchedStockPoints = null;
1123 if (stockPoints && stockPoints.length > 0) {
1124 console.log('Matching stock data with sales data...');
1125 matchedStockPoints = dataPoints.map(salesDay => {
1126 const stockDay = stockPoints.find(s => s.day === salesDay.day);
1127 return {
1128 day: salesDay.day,
1129 sales: salesDay.sales,
1130 price: salesDay.price,
1131 stock: stockDay ? stockDay.stock : null
1132 };
1133 });
1134 console.log('Matched stock data - First 5 days:', matchedStockPoints.slice(0, 5));
1135 console.log('Matched stock data - Last 5 days:', matchedStockPoints.slice(-5));
1136 } else {
1137 console.log('No stock data to match');
1138 }
1139
1140 console.log('Extracted summary data:', {
1141 revenue,
1142 sales,
1143 avgPrice,
1144 currentStock,
1145 avgDailySales,
1146 daysOfData: dataPoints.length,
1147 stockDataPoints: stockPoints ? stockPoints.length : 0,
1148 matchedDataPoints: matchedStockPoints ? matchedStockPoints.length : 0
1149 });
1150
1151 return {
1152 revenue,
1153 sales,
1154 avgPrice,
1155 currentStock,
1156 avgDailySales,
1157 dataPoints,
1158 stockPoints,
1159 matchedStockPoints
1160 };
1161 }
1162
1163 return null;
1164 }
1165
1166 // Calculate demand elasticity from historical data
1167 function calculateDemandElasticity(dataPoints, matchedStockPoints) {
1168 console.log('=== CALCULATING DEMAND ELASTICITY (Bayesian Log-Linear) ===');
1169 console.log('dataPoints:', dataPoints);
1170 console.log('matchedStockPoints:', matchedStockPoints);
1171
1172 // NEW: Filter outliers first
1173 let filteredPoints = filterOutliers(dataPoints);
1174 console.log(`Using ${filteredPoints.length} points after outlier filtering`);
1175
1176 // Filter out days with zero stock and the day before zero stock
1177 let validPoints = filteredPoints;
1178 if (matchedStockPoints && matchedStockPoints.length > 0) {
1179 const zeroStockDays = new Set();
1180 matchedStockPoints.forEach((d, index) => {
1181 if (d.stock === 0) {
1182 zeroStockDays.add(d.day);
1183 // Also exclude the day before zero stock
1184 if (index > 0) {
1185 zeroStockDays.add(matchedStockPoints[index - 1].day);
1186 }
1187 }
1188 });
1189 validPoints = filteredPoints.filter(d => !zeroStockDays.has(d.day));
1190 console.log(`Excluded ${zeroStockDays.size} days (zero stock and day before)`);
1191 }
1192
1193 console.log(`Using ${validPoints.length} days for elasticity calculation`);
1194 console.log('Valid points sample:', validPoints.slice(0, 5));
1195
1196 if (validPoints.length < 5) {
1197 console.log('Not enough data points for elasticity calculation, using default -1.5');
1198 return { elasticity: -1.5, reliability: 'bad', r2: 0, uniquePrices: 0, daysUsed: validPoints.length };
1199 }
1200
1201 // === LOG-LINEAR REGRESSION ===
1202 // Transform to log space: log(sales) = intercept + elasticity * log(price)
1203 const logPrices = validPoints.map(d => Math.log(d.price));
1204 const logSales = validPoints.map(d => Math.log(d.sales + 1)); // +1 for stability when sales = 0
1205
1206 const n = validPoints.length;
1207 const sumX = logPrices.reduce((a, b) => a + b, 0);
1208 const sumY = logSales.reduce((a, b) => a + b, 0);
1209 const sumXY = logPrices.reduce((a, b, i) => a + b * logSales[i], 0);
1210 const sumX2 = logPrices.reduce((a, b) => a + b * b, 0);
1211
1212 console.log(`Log-linear regression: n=${n}, sumX=${sumX.toFixed(2)}, sumY=${sumY.toFixed(2)}, sumXY=${sumXY.toFixed(2)}, sumX2=${sumX2.toFixed(2)}`);
1213
1214 const denominator = n * sumX2 - sumX * sumX;
1215 if (denominator === 0) {
1216 console.log('⚠️ Denominator is zero, using default elasticity');
1217 return { elasticity: -1.5, reliability: 'bad', r2: 0, uniquePrices: 0, daysUsed: n };
1218 }
1219
1220 const slope = (n * sumXY - sumX * sumY) / denominator; // This is the elasticity
1221 const intercept = (sumY - slope * sumX) / n;
1222
1223 console.log(`OLS results: slope (elasticity) = ${slope.toFixed(4)}, intercept = ${intercept.toFixed(4)}`);
1224
1225 // Calculate R² (coefficient of determination)
1226 const yMean = sumY / n;
1227 const ssTotal = logSales.reduce((s, y) => s + Math.pow(y - yMean, 2), 0);
1228 const predicted = logPrices.map(x => slope * x + intercept);
1229 const ssResidual = logSales.reduce((s, y, i) => s + Math.pow(y - predicted[i], 2), 0);
1230 const r2 = ssTotal > 0 ? 1 - (ssResidual / ssTotal) : 0;
1231
1232 console.log(`R²: ssTotal=${ssTotal.toFixed(4)}, ssResidual=${ssResidual.toFixed(4)}, R²=${r2.toFixed(4)}`);
1233
1234 // === BAYESIAN CORRECTION WITH INFORMATIVE PRIOR ===
1235 const priorElasticity = -1.5; // Typical value for Ozon products
1236 const priorStrength = 10; // "Equivalent to 10 days of observations"
1237
1238 console.log(`Prior: elasticity=${priorElasticity}, strength=${priorStrength} days`);
1239
1240 const dataStrength = n; // Weight of actual data
1241 const posteriorElasticity = (slope * dataStrength + priorElasticity * priorStrength) / (dataStrength + priorStrength);
1242
1243 console.log(`Posterior elasticity (simple Bayesian average): ${posteriorElasticity.toFixed(4)}`);
1244
1245 // If we have a lot of data and high R² - trust the data more
1246 const weightData = Math.min(1, n / 20) * Math.sqrt(Math.max(0, r2));
1247 const finalElasticity = slope * weightData + posteriorElasticity * (1 - weightData);
1248
1249 console.log(`Data weight: ${weightData.toFixed(4)} (based on n=${n} and R²=${r2.toFixed(4)})`);
1250 console.log(`Final elasticity (weighted): ${finalElasticity.toFixed(4)}`);
1251
1252 // NEW: Improved clamping with better bounds
1253 // Elasticity should be negative (demand curve slopes down)
1254 // Typical range for e-commerce: -0.5 to -2.5
1255 // Only clamp to extreme values if really necessary
1256 let clampedElasticity = finalElasticity;
1257
1258 // If elasticity is positive (wrong direction), use prior
1259 if (finalElasticity > 0) {
1260 console.log(`⚠️ Positive elasticity ${finalElasticity.toFixed(4)} detected, using prior ${priorElasticity}`);
1261 clampedElasticity = priorElasticity;
1262 }
1263 // If elasticity is too extreme (< -2.5), clamp it
1264 else if (finalElasticity < -2.5) {
1265 console.log(`⚠️ Extreme elasticity ${finalElasticity.toFixed(4)} detected, clamping to -2.5`);
1266 clampedElasticity = -2.5;
1267 }
1268 // If elasticity is too weak (> -0.3), clamp it
1269 else if (finalElasticity > -0.3) {
1270 console.log(`⚠️ Very weak elasticity ${finalElasticity.toFixed(4)} detected, clamping to -0.5`);
1271 clampedElasticity = -0.5;
1272 }
1273
1274 // Determine reliability based on R², number of unique prices, and days
1275 const uniquePrices = [...new Set(validPoints.map(d => d.price))];
1276
1277 let reliability = 'bad';
1278 if (r2 >= 0.7 && uniquePrices.length >= 8 && n >= 20) {
1279 reliability = 'good';
1280 } else if (r2 >= 0.4 && uniquePrices.length >= 4 && n >= 10) {
1281 reliability = 'satisfactory';
1282 }
1283
1284 console.log(`=== FINAL ELASTICITY: ${clampedElasticity.toFixed(4)}, R²=${r2.toFixed(4)}, Reliability=${reliability} ===`);
1285 console.log(`Raw OLS elasticity: ${slope.toFixed(4)}, Posterior: ${posteriorElasticity.toFixed(4)}, Final: ${clampedElasticity.toFixed(4)}`);
1286
1287 return {
1288 elasticity: clampedElasticity,
1289 reliability: reliability,
1290 r2: r2,
1291 uniquePrices: uniquePrices.length,
1292 daysUsed: n,
1293 rawElasticity: slope,
1294 posteriorElasticity: posteriorElasticity
1295 };
1296 }
1297
1298 // AI-powered Bayesian price optimization
1299 async function bayesianPriceOptimizationWithAI(historicalData, productData, competitorData, coinvest, drr) {
1300 console.log('=== ENTERED bayesianPriceOptimizationWithAI (v2.0.1) ===');
1301 console.log('Historical data:', historicalData);
1302 console.log('Product data:', productData);
1303 console.log('Competitor data:', competitorData);
1304 console.log('Coinvest:', coinvest, '%, DRR:', drr, '%');
1305
1306 try {
1307 console.log('>>> ABOUT TO CALL calculateDemandElasticity <<<');
1308 console.log('>>> dataPoints:', historicalData.dataPoints);
1309 console.log('>>> matchedStockPoints:', historicalData.matchedStockPoints);
1310
1311 const elasticityResult = calculateDemandElasticity(historicalData.dataPoints, historicalData.matchedStockPoints);
1312 const realElasticity = elasticityResult.elasticity;
1313
1314 console.log(`>>> AFTER calculateDemandElasticity, realElasticity = ${realElasticity} <<<`);
1315 console.log(`Real demand elasticity calculated: ${realElasticity.toFixed(4)}, R²=${elasticityResult.r2.toFixed(4)}, Reliability=${elasticityResult.reliability}`);
1316
1317 // Prepare historical data summary
1318 const uniquePrices = [...new Set(historicalData.dataPoints.map(d => d.price))];
1319
1320 console.log(`Historical data: ${historicalData.dataPoints.length} days, ${uniquePrices.length} unique prices:`, uniquePrices);
1321
1322 // === NEW: Calculate market constraints ===
1323 const displayPriceMultiplier = (100 - coinvest) / 100;
1324 const costPrice = (productData.cost + productData.delivery) / (1 - productData.commission - drr / 100);
1325 const minBreakevenDisplayPrice = Math.ceil(costPrice * displayPriceMultiplier);
1326
1327 let minMarketPrice = minBreakevenDisplayPrice;
1328 let maxMarketPrice = 30000;
1329
1330 // === NEW: Check if we're market leader ===
1331 let isMarketLeader = false;
1332 let ourRevenue = historicalData.avgPrice * historicalData.sales;
1333
1334 if (competitorData && competitorData.length > 0) {
1335 const competitorPrices = competitorData.map(c => c.price);
1336 const minCompPrice = Math.min(...competitorPrices);
1337 const maxCompPrice = Math.max(...competitorPrices);
1338
1339 // Check if our revenue is higher than all competitors
1340 const maxCompetitorRevenue = Math.max(...competitorData.map(c => c.revenue30days || 0));
1341 ourRevenue = historicalData.sales * historicalData.avgPrice; // 30-day revenue
1342
1343 if (ourRevenue > maxCompetitorRevenue * 0.9) {
1344 isMarketLeader = true;
1345 console.log('🏆 MARKET LEADER DETECTED!');
1346 console.log(`Our revenue: ${ourRevenue.toFixed(0)}₽/30d vs Max competitor: ${maxCompetitorRevenue.toFixed(0)}₽/30d`);
1347 }
1348
1349 minMarketPrice = Math.max(minBreakevenDisplayPrice, Math.floor(minCompPrice * 0.7));
1350 maxMarketPrice = Math.min(30000, Math.ceil(maxCompPrice * 1.3));
1351
1352 console.log('=== MARKET CONSTRAINTS ===');
1353 console.log(`Competitor price range: ${minCompPrice}-${maxCompPrice}₽`);
1354 console.log(`Market boundaries (0.7x - 1.3x): ${Math.floor(minCompPrice * 0.7)} - ${Math.ceil(maxCompPrice * 1.3)}₽`);
1355 console.log(`Cost-based minimum: ${minBreakevenDisplayPrice}₽`);
1356 console.log(`FINAL HARD LIMITS: ${minMarketPrice} - ${maxMarketPrice}₽`);
1357 console.log(`Market Leader Status: ${isMarketLeader ? 'YES 🏆' : 'NO'}`);
1358 } else {
1359 console.log('=== MARKET CONSTRAINTS (No Competitors) ===');
1360 console.log(`HARD LIMITS: ${minMarketPrice} - ${maxMarketPrice}₽`);
1361 }
1362
1363 // === NEW: Determine product segment ===
1364 const segmentInfo = determineProductSegment(historicalData.avgPrice, competitorData);
1365
1366 // === NEW: Calculate inventory strategy ===
1367 const daysOfSupply = historicalData.avgDailySales > 0 ? historicalData.currentStock / historicalData.avgDailySales : 999;
1368 const inventoryInfo = getInventoryStrategy(daysOfSupply);
1369
1370 // Prepare competitor analysis
1371 let competitorAnalysis = '';
1372 if (competitorData && competitorData.length > 0) {
1373 const prices = competitorData.map(c => c.price);
1374 const minCompPrice = Math.min(...prices);
1375 const maxCompPrice = Math.max(...prices);
1376 const avgCompPrice = Math.round(prices.reduce((a, b) => a + b, 0) / prices.length);
1377
1378 const topCompetitors = competitorData.slice(0, 3).map(c =>
1379 `${c.price}₽ (${c.sales30days ? (c.sales30days / 30).toFixed(1) + ' шт/день' : 'н/д'})`
1380 ).join(', ');
1381
1382 competitorAnalysis = `\nКОНКУРЕНТЫ (${competitorData.length} шт): цены ${minCompPrice}-${maxCompPrice}₽, средняя ${avgCompPrice}₽. Топ-3 по выручке: ${topCompetitors}.`;
1383
1384 console.log('>>> COMPETITOR PRICES BEING SENT TO AI <<<');
1385 console.log('Competitor count:', competitorData.length);
1386 console.log('Price range:', minCompPrice, '-', maxCompPrice, '₽');
1387 console.log('Average price:', avgCompPrice, '₽');
1388 console.log('Top 3 competitors:', topCompetitors);
1389 console.log('All competitor prices:', prices);
1390 console.log('Competitor analysis text for AI:', competitorAnalysis);
1391 } else {
1392 console.log('>>> NO COMPETITOR DATA - AI WILL NOT CONSIDER COMPETITORS <<<');
1393 }
1394
1395 const commissionPercent = Math.round(productData.commission * 100);
1396
1397 // Calculate actual price from current display price using user's coinvest value
1398 const actualPrice = historicalData.avgPrice / displayPriceMultiplier;
1399
1400 // === НОВЫЕ МЕТРИКИ ===
1401
1402 // 1. Weighted average competitor price (взвешенная по продажам)
1403 let weightedAvgCompPrice = 0;
1404 let totalCompSales = 0;
1405 let minCompPrice = Infinity;
1406 let maxCompPrice = 0;
1407 if (competitorData && competitorData.length > 0) {
1408 competitorData.forEach(c => {
1409 if (c.sales30days > 0) {
1410 weightedAvgCompPrice += c.price * c.sales30days;
1411 totalCompSales += c.sales30days;
1412 }
1413 minCompPrice = Math.min(minCompPrice, c.price);
1414 maxCompPrice = Math.max(maxCompPrice, c.price);
1415 });
1416 weightedAvgCompPrice = totalCompSales > 0 ? weightedAvgCompPrice / totalCompSales : historicalData.avgPrice;
1417 } else {
1418 weightedAvgCompPrice = historicalData.avgPrice;
1419 minCompPrice = historicalData.avgPrice;
1420 maxCompPrice = historicalData.avgPrice;
1421 }
1422
1423 // 2. RPI (Relative Price Index)
1424 const currentDisplayPrice = historicalData.avgPrice;
1425 const rpi = (currentDisplayPrice / weightedAvgCompPrice) * 100;
1426
1427 // 3. Popularity Score (твои средние продажи vs средние конкурентов)
1428 let avgCompDailySales = 0;
1429 if (competitorData && competitorData.length > 0) {
1430 avgCompDailySales = competitorData.reduce((sum, c) => sum + (c.sales30days || 0) / 30, 0) / competitorData.length;
1431 }
1432 const popularityScore = avgCompDailySales > 0 ? historicalData.avgDailySales / avgCompDailySales : 1;
1433
1434 // 4. PVBI (Price Value Benefit Index) — proxy ценности
1435 let maxCompValue = 0;
1436 if (competitorData && competitorData.length > 0) {
1437 competitorData.forEach(c => {
1438 const value = c.sales30days > 0 ? (c.sales30days / 30) / c.price : 0;
1439 maxCompValue = Math.max(maxCompValue, value);
1440 });
1441 }
1442 const yourValue = historicalData.avgDailySales / currentDisplayPrice;
1443 const pvbi = maxCompValue > 0 ? yourValue / maxCompValue : 1;
1444
1445 // 6. Топ-3 конкурентов для промпта
1446 const topCompetitors = competitorData && competitorData.length > 0
1447 ? competitorData.slice(0, 3).map(c =>
1448 `${c.brand}: ${c.price}₽ (${(c.sales30days / 30).toFixed(1)} шт/день)`
1449 ).join(', ')
1450 : 'нет данных';
1451
1452 console.log('=== НОВЫЕ МЕТРИКИ ===');
1453 console.log('Weighted Avg Comp Price:', weightedAvgCompPrice.toFixed(0), '₽');
1454 console.log('RPI:', rpi.toFixed(1), '%');
1455 console.log('Popularity Score:', popularityScore.toFixed(2));
1456 console.log('PVBI:', pvbi.toFixed(2));
1457 console.log('Days of Supply:', daysOfSupply.toFixed(1));
1458
1459 const aiPrompt = `Ты — эксперт по динамическому ценообразованию на маркетплейсах (Ozon). Твоя задача — найти цену реализации, которая МАКСИМИЗИРУЕТ ДНЕВНУЮ ПРИБЫЛЬ с учётом всех рисков.
1460
1461⚠️ ЖЁСТКИЕ ОГРАНИЧЕНИЯ (НИКОГДА НЕ НАРУШАЙ):
1462• Минимальная цена реализации: ${minMarketPrice} ₽ (безубыточность + рыночный минимум)
1463• Максимальная цена реализации: ${maxMarketPrice} ₽ (рыночный максимум)
1464• ВСЕ рекомендуемые цены ДОЛЖНЫ быть в диапазоне [${minMarketPrice}, ${maxMarketPrice}] ₽
1465• Если расчёт даёт цену вне диапазона — используй ближайшую границу
1466
1467${isMarketLeader ? `
1468🏆 КРИТИЧЕСКИ ВАЖНО - ВЫ ЛИДЕР РЫНКА:
1469• Ваша выручка (${Math.round(ourRevenue)}₽/30д) ВЫШЕ всех конкурентов
1470• Вы уже занимаете доминирующую позицию на рынке
1471• Снижение цены приведёт к ПОТЕРЕ ПРИБЫЛИ без существенного роста продаж
1472• Конкуренты с низкими ценами имеют МЕНЬШУЮ выручку - их стратегия НЕ эффективнее вашей
1473• ЗАПРЕЩЕНО рекомендовать снижение цены более чем на 5% от текущей
1474• Приоритет: СОХРАНЕНИЕ МАРЖИНАЛЬНОСТИ, а не рост объёма продаж
1475` : ''}
1476
1477КРИТИЧЕСКИ ВАЖНО:
1478• Цена реализации — это цена, которую видит покупатель (после соинвеста ${coinvest}% от Ozon).
1479• Фактическая цена = Цена реализации / ${displayPriceMultiplier.toFixed(2)}.
1480• Все расходы (комиссия, ДРР) считаются от фактической цены.
1481• Прибыль = (Факт. цена - Себестоимость - Комиссия - Доставка - Реклама) × Прогноз продаж.
1482
1483ТЕКУЩАЯ СИТУАЦИЯ:
1484• Текущая цена реализации: ${Math.round(historicalData.avgPrice)} ₽
1485• Фактическая цена: ${Math.round(actualPrice)} ₽
1486• Средние продажи: ${historicalData.avgDailySales.toFixed(1)} шт/день
1487• Остаток: ${historicalData.currentStock} шт (Days of Supply: ${daysOfSupply.toFixed(1)} дней)
1488• Popularity Score (относительно конкурентов): ${popularityScore.toFixed(2)} (выше 1 — популярнее рынка)
1489• RPI (Relative Price Index): ${rpi.toFixed(1)}% (100% — средняя цена конкурентов по выручке)
1490• PVBI (Price Value Benefit Index): ${pvbi.toFixed(2)}
1491
1492ПОЗИЦИОНИРОВАНИЕ ТОВАРА:
1493• Сегмент: ${segmentInfo.segment} — ${segmentInfo.description}
1494• Стратегия: ${segmentInfo.strategy}
1495
1496СТРАТЕГИЯ ПО ОСТАТКАМ:
1497• Статус: ${inventoryInfo.action} (${inventoryInfo.daysOfSupply.toFixed(1)} дней)
1498• Рекомендация: ${inventoryInfo.priceAdjustment}
1499
1500ЭЛАСТИЧНОСТЬ СПРОСА (лог-линейная модель, ${historicalData.dataPoints.length} дней, ${uniquePrices.length} уникальных цен):
1501• Коэффициент эластичности: ${realElasticity.toFixed(4)}
1502• Формула прогноза: Прогноз продаж = ${historicalData.avgDailySales.toFixed(1)} × (цена / ${Math.round(historicalData.avgPrice)}) ** ${realElasticity.toFixed(4)}
1503• Достоверность: R² = ${elasticityResult.r2.toFixed(4)}, ${elasticityResult.reliability}
1504
1505СТРУКТУРА РАСХОДОВ:
1506• Себестоимость: ${productData.cost} ₽
1507• Комиссия Ozon: ${commissionPercent}% от факт. цены
1508• Доставка: ${productData.delivery} ₽
1509• ДРР: ${drr}% от факт. цены
1510• Минимальная безубыточная цена реализации: ${minBreakevenDisplayPrice} ₽
1511
1512КОНКУРЕНТЫ (${competitorData ? competitorData.length : 0} шт):
1513• Взвешенная средняя цена: ${Math.round(weightedAvgCompPrice)} ₽
1514• Диапазон: ${minCompPrice === Infinity ? 'н/д' : minCompPrice + '–' + maxCompPrice + ' ₽'}
1515• Топ-3 по выручке: ${topCompetitors}
1516
1517БИЗНЕС-ЛОГИКА (обязательно применяй):
15181. УБЫТОЧНОСТЬ: Никогда не рекомендуй цену ниже ${minBreakevenDisplayPrice} ₽ (себестоимость + расходы)
15192. КОНКУРЕНТОСПОСОБНОСТЬ: Учитывай позицию относительно конкурентов (RPI, сегмент)
15203. ЛИКВИДНОСТЬ: При высоких остатках (>90 дней) приоритет — скорость продаж, при низких (<30) — маржа
15214. ЭЛАСТИЧНОСТЬ: Используй реальную эластичность ${realElasticity.toFixed(4)} для прогноза продаж
15225. РЫНОЧНЫЕ ГРАНИЦЫ: Цена вне [${minMarketPrice}, ${maxMarketPrice}] ₽ нереалистична для этого рынка
1523${isMarketLeader ? '6. ЛИДЕРСТВО: Как лидер рынка, ты НЕ ДОЛЖЕН снижать цену без крайней необходимости (критические остатки >180 дней)' : ''}
1524
1525ДОПОЛНИТЕЛЬНЫЕ КОРРЕКТИРОВКИ:
15261. RPI-корректировка: если RPI > 110 — уменьши прогноз продаж на (RPI-100)/50; если RPI < 90 — увеличь на (100-RPI)/50.
15272. Остатки: ${inventoryInfo.priceAdjustment}
15283. Popularity Score: если > 1.2 — можно устанавливать цену выше рынка без сильного падения продаж.
15294. Сегмент: ${segmentInfo.strategy}
1530
1531ТВОЯ ЗАДАЧА:
15321. Рассчитай прибыль для цен реализации от ${minMarketPrice} ₽ до ${maxMarketPrice} ₽ с шагом 10 ₽.
15332. Для каждой цены применяй ВСЕ корректировки выше (RPI, остатки, популярность, сегмент).
15343. Используй лог-линейную формулу: Прогноз = ${historicalData.avgDailySales.toFixed(1)} × (цена / ${Math.round(historicalData.avgPrice)}) ** ${realElasticity.toFixed(4)}
15354. Выбери цену с МАКСИМАЛЬНОЙ дневной прибылью В ДИАПАЗОНЕ [${minMarketPrice}, ${maxMarketPrice}] ₽.
15365. Также предложи 3 альтернативные цены для исследования (explorationPrices) — чуть ниже/выше оптимума, но СТРОГО в диапазоне.
1537${isMarketLeader ? `
15386. ⚠️ ОСОБОЕ ПРАВИЛО ДЛЯ ЛИДЕРА: Если оптимальная цена ниже текущей более чем на 5%, ИГНОРИРУЙ её и рекомендуй текущую цену или выше. Лидер рынка НЕ должен демпинговать.
1539` : ''}
1540
1541ВАЖНО:
1542• Не бойся рекомендовать изменение цены! Если расчеты показывают, что другая цена даст больше прибыли - рекомендуй её!
1543${isMarketLeader ? '• НО: Как лидер рынка, снижение цены должно быть обосновано КРИТИЧЕСКОЙ необходимостью (остатки >180 дней), а не просто "возможным ростом продаж"' : ''}
1544• ВСЕ цены (optimalPrice, minPrice, maxPrice, explorationPrices) ДОЛЖНЫ быть в диапазоне [${minMarketPrice}, ${maxMarketPrice}] ₽!
1545
1546Верни JSON строго по схеме с оптимальной ценой РЕАЛИЗАЦИИ (той, что дает максимальную прибыль/день).`;
1547
1548 console.log('>>> CALLING RM.aiCall <<<');
1549 const aiResponse = await RM.aiCall(aiPrompt, {
1550 type: 'json_schema',
1551 json_schema: {
1552 name: 'price_optimization',
1553 schema: {
1554 type: 'object',
1555 properties: {
1556 optimalPrice: { type: 'number' },
1557 minPrice: { type: 'number' },
1558 maxPrice: { type: 'number' },
1559 confidence: { type: 'number' },
1560 reasoning: { type: 'string' },
1561 explorationPrices: {
1562 type: 'array',
1563 items: { type: 'number' },
1564 minItems: 3,
1565 maxItems: 3
1566 }
1567 },
1568 required: ['optimalPrice', 'minPrice', 'maxPrice', 'confidence', 'reasoning', 'explorationPrices']
1569 }
1570 }
1571 });
1572
1573 console.log('>>> AI RESPONSE RECEIVED <<<');
1574 console.log('AI response:', aiResponse);
1575 console.log('AI optimalPrice:', aiResponse.optimalPrice);
1576 console.log('AI reasoning:', aiResponse.reasoning);
1577 console.log('AI confidence:', aiResponse.confidence);
1578 console.log('AI explorationPrices:', aiResponse.explorationPrices);
1579
1580 // === NEW: Post-process AI recommendations to enforce market constraints ===
1581 let correctionWarning = '';
1582
1583 // Clamp optimal price to market boundaries
1584 const originalOptimalPrice = aiResponse.optimalPrice;
1585 if (aiResponse.optimalPrice < minMarketPrice) {
1586 aiResponse.optimalPrice = minMarketPrice;
1587 correctionWarning = `⚠️ КОРРЕКЦИЯ: AI предложил ${originalOptimalPrice}₽, но это ниже минимальной рыночной границы. Цена скорректирована до ${minMarketPrice}₽ (минимум рынка).`;
1588 console.log(correctionWarning);
1589 } else if (aiResponse.optimalPrice > maxMarketPrice) {
1590 aiResponse.optimalPrice = maxMarketPrice;
1591 correctionWarning = `⚠️ КОРРЕКЦИЯ: AI предложил ${originalOptimalPrice}₽, но это выше максимальной рыночной границы. Цена скорректирована до ${maxMarketPrice}₽ (максимум рынка).`;
1592 console.log(correctionWarning);
1593 }
1594
1595 // Clamp exploration prices
1596 aiResponse.explorationPrices = aiResponse.explorationPrices.map(price => {
1597 return Math.max(minMarketPrice, Math.min(maxMarketPrice, price));
1598 });
1599
1600 // Clamp min/max prices
1601 aiResponse.minPrice = Math.max(minMarketPrice, Math.min(maxMarketPrice, aiResponse.minPrice));
1602 aiResponse.maxPrice = Math.max(minMarketPrice, Math.min(maxMarketPrice, aiResponse.maxPrice));
1603
1604 // Add warning to reasoning if correction was made
1605 if (correctionWarning) {
1606 aiResponse.reasoning = correctionWarning + '\n\n' + aiResponse.reasoning;
1607 }
1608
1609 // Calculate all possible prices and find the one with maximum profit
1610 const priceRange = [];
1611 const step = (aiResponse.maxPrice - aiResponse.minPrice) / 20;
1612
1613 for (let price = aiResponse.minPrice; price <= aiResponse.maxPrice; price += step) {
1614 priceRange.push(Math.round(price));
1615 }
1616
1617 aiResponse.explorationPrices.forEach(p => {
1618 if (!priceRange.includes(Math.round(p))) {
1619 priceRange.push(Math.round(p));
1620 }
1621 });
1622
1623 priceRange.sort((a, b) => a - b);
1624
1625 const results = priceRange.map(displayPrice => {
1626 let estimatedSales = historicalData.avgDailySales * Math.pow(displayPrice / historicalData.avgPrice, realElasticity);
1627
1628 // Calculate actual price from display price using user's coinvest
1629 const actualPrice = displayPrice / displayPriceMultiplier;
1630 const commission = actualPrice * productData.commission;
1631 const advertisingCost = actualPrice * (drr / 100);
1632 const delivery = productData.delivery;
1633 const profitPerUnit = actualPrice - productData.cost - commission - delivery - advertisingCost;
1634 const profit = profitPerUnit * estimatedSales;
1635 const margin = (profitPerUnit / actualPrice) * 100;
1636
1637 return {
1638 price: Math.round(displayPrice * 10) / 10,
1639 actualPrice: Math.round(actualPrice * 10) / 10,
1640 estimatedDailySales: Math.round(estimatedSales * 10) / 10,
1641 estimatedDailyProfit: Math.round(profit * 10) / 10,
1642 profitMargin: Math.round(margin * 10) / 10,
1643 confidence: aiResponse.confidence,
1644 commission: Math.round(commission * 10) / 10,
1645 advertisingCost: Math.round(advertisingCost * 10) / 10,
1646 delivery: delivery
1647 };
1648 });
1649
1650 // Find the price with maximum profit from our calculations
1651 const maxProfitResult = results.reduce((max, current) =>
1652 current.estimatedDailyProfit > max.estimatedDailyProfit ? current : max
1653 );
1654
1655 console.log('>>> CALCULATED OPTIMAL PRICE <<<');
1656 console.log('Current price:', historicalData.avgPrice, '₽');
1657 console.log('AI suggested:', aiResponse.optimalPrice, '₽');
1658 console.log('Math optimal:', maxProfitResult.price, '₽ with profit:', maxProfitResult.estimatedDailyProfit, '₽/day');
1659
1660 // Log all results sorted by profit
1661 const sortedByProfit = [...results].sort((a, b) => b.estimatedDailyProfit - a.estimatedDailyProfit);
1662 console.log('>>> TOP 10 PRICES BY PROFIT <<<');
1663 sortedByProfit.slice(0, 10).forEach((r, i) => {
1664 console.log(`${i + 1}. Price: ${r.price}₽, Profit: ${r.estimatedDailyProfit}₽/day, Sales: ${r.estimatedDailySales} шт/day, Margin: ${r.profitMargin}%`);
1665 });
1666
1667 console.log('>>> BOTTOM 5 PRICES BY PROFIT <<<');
1668 sortedByProfit.slice(-5).forEach((r, i) => {
1669 console.log(`${sortedByProfit.length - 4 + i}. Price: ${r.price}₽, Profit: ${r.estimatedDailyProfit}₽/day, Sales: ${r.estimatedDailySales} шт/day`);
1670 });
1671
1672 // Use the mathematically optimal price instead of AI suggestion
1673 let optimalResult = maxProfitResult;
1674
1675 // NEW: Check if optimal price actually gives more profit than current price
1676 // Calculate current profit correctly
1677 const currentActualPriceCalc = historicalData.avgPrice / displayPriceMultiplier;
1678 const currentCommissionCalc = currentActualPriceCalc * productData.commission;
1679 const currentAdvertisingCostCalc = currentActualPriceCalc * (drr / 100);
1680 const currentDeliveryCalc = productData.delivery;
1681 const currentProfitPerUnitCalc = currentActualPriceCalc - productData.cost - currentCommissionCalc - currentDeliveryCalc - currentAdvertisingCostCalc;
1682 const currentDailyProfitCalc = Math.round(currentProfitPerUnitCalc * historicalData.avgDailySales * 10) / 10;
1683
1684 console.log('>>> COMPARING OPTIMAL VS CURRENT <<<');
1685 console.log('Current daily profit:', currentDailyProfitCalc, '₽/day');
1686 console.log('Optimal daily profit:', maxProfitResult.estimatedDailyProfit, '₽/day');
1687 console.log('Difference:', (maxProfitResult.estimatedDailyProfit - currentDailyProfitCalc).toFixed(1), '₽/day');
1688 console.log('Percentage improvement:', ((maxProfitResult.estimatedDailyProfit / currentDailyProfitCalc - 1) * 100).toFixed(2), '%');
1689
1690 // NEW: More strict check - if profit improvement is less than 5%, keep current price
1691 const profitImprovement = (maxProfitResult.estimatedDailyProfit / currentDailyProfitCalc - 1) * 100;
1692
1693 if (profitImprovement < 5) {
1694 console.log(`⚠️ WARNING: Profit improvement is only ${profitImprovement.toFixed(2)}% (less than 5% threshold)`);
1695 console.log('Keeping current price as optimal - not worth the risk of changing price for minimal gain');
1696
1697 // Find result for current price or create it
1698 let currentPriceResult = results.find(r => Math.abs(r.price - historicalData.avgPrice) < 5);
1699
1700 if (!currentPriceResult) {
1701 const estimatedSales = historicalData.avgDailySales; // Current sales at current price
1702 const actualPriceForCurrent = historicalData.avgPrice / displayPriceMultiplier;
1703 const commissionForCurrent = actualPriceForCurrent * productData.commission;
1704 const advertisingCostForCurrent = actualPriceForCurrent * (drr / 100);
1705 const deliveryForCurrent = productData.delivery;
1706 const profitForCurrent = (actualPriceForCurrent - productData.cost - commissionForCurrent - deliveryForCurrent - advertisingCostForCurrent) * estimatedSales;
1707 const marginForCurrent = ((actualPriceForCurrent - productData.cost - commissionForCurrent - deliveryForCurrent - advertisingCostForCurrent) / actualPriceForCurrent) * 100;
1708
1709 currentPriceResult = {
1710 price: Math.round(historicalData.avgPrice * 10) / 10,
1711 actualPrice: Math.round(actualPriceForCurrent * 10) / 10,
1712 estimatedDailySales: Math.round(estimatedSales * 10) / 10,
1713 estimatedDailyProfit: Math.round(profitForCurrent * 10) / 10,
1714 profitMargin: Math.round(marginForCurrent * 10) / 10,
1715 confidence: aiResponse.confidence,
1716 commission: Math.round(commissionForCurrent * 10) / 10,
1717 advertisingCost: Math.round(advertisingCostForCurrent * 10) / 10,
1718 delivery: deliveryForCurrent
1719 };
1720 }
1721
1722 optimalResult = currentPriceResult;
1723
1724 const profitDiffAmount = maxProfitResult.estimatedDailyProfit - currentDailyProfitCalc;
1725 aiResponse.reasoning = `⚠️ ВАЖНО: Текущая цена ${Math.round(historicalData.avgPrice)}₽ уже оптимальна. Математический анализ показал, что снижение до ${maxProfitResult.price}₽ увеличит прибыль всего на ${profitDiffAmount.toFixed(1)}₽/день (+${profitImprovement.toFixed(2)}%). Это НЕЗНАЧИТЕЛЬНОЕ улучшение (менее 5%) НЕ оправдывает риски изменения цены: потеря маржинальности (${Math.round(historicalData.avgPrice - maxProfitResult.price)}₽ с каждой продажи), возможные ошибки в прогнозе эластичности, негативное восприятие частых изменений цены покупателями. РЕКОМЕНДАЦИЯ: Сохранить текущую цену ${Math.round(historicalData.avgPrice)}₽ для стабильной максимальной прибыли ${currentDailyProfitCalc}₽/день.`;
1726 }
1727 // Update AI reasoning to reflect the correction
1728 else if (Math.abs(maxProfitResult.price - aiResponse.optimalPrice) > 5) {
1729 const aiSuggestedResult = results.find(r => Math.abs(r.price - aiResponse.optimalPrice) < 1);
1730 const aiSuggestedProfit = aiSuggestedResult ? aiSuggestedResult.estimatedDailyProfit : 0;
1731
1732 aiResponse.reasoning = `Математический расчет показал, что оптимальная цена ${maxProfitResult.price}₽ дает прибыль ${maxProfitResult.estimatedDailyProfit}₽/день, что лучше первоначально предложенной ${aiResponse.optimalPrice}₽ (прибыль ${aiSuggestedProfit}₽/день) и текущей ${Math.round(historicalData.avgPrice)}₽ (прибыль ${currentDailyProfitCalc}₽/день). При цене ${maxProfitResult.price}₽: продажи ${maxProfitResult.estimatedDailySales} шт/день, маржа ${maxProfitResult.profitMargin}%, прибыль/шт ${Math.round(maxProfitResult.actualPrice - productData.cost - maxProfitResult.commission - maxProfitResult.delivery - maxProfitResult.advertisingCost)}₽. Эта цена максимизирует дневную прибыль с учетом эластичности спроса и конкурентной среды.`;
1733 console.log('>>> CORRECTED AI SUGGESTION <<<');
1734 console.log('New reasoning:', aiResponse.reasoning);
1735 }
1736
1737 const alternatives = [];
1738 aiResponse.explorationPrices.forEach(explorePrice => {
1739 if (explorePrice !== aiResponse.optimalPrice) {
1740 let altResult = results.find(r => r.price === explorePrice);
1741
1742 if (!altResult) {
1743 const estimatedSales = historicalData.avgDailySales * Math.pow(explorePrice / historicalData.avgPrice, realElasticity);
1744
1745 const actualPrice = explorePrice / displayPriceMultiplier;
1746 const commission = actualPrice * productData.commission;
1747 const advertisingCost = actualPrice * (drr / 100);
1748 const delivery = productData.delivery;
1749 const profit = (actualPrice - productData.cost - commission - delivery - advertisingCost) * estimatedSales;
1750 const margin = ((actualPrice - productData.cost - commission - delivery - advertisingCost) / actualPrice) * 100;
1751
1752 altResult = {
1753 price: Math.round(explorePrice * 10) / 10,
1754 actualPrice: Math.round(actualPrice * 10) / 10,
1755 estimatedDailySales: Math.round(estimatedSales * 10) / 10,
1756 estimatedDailyProfit: Math.round(profit * 10) / 10,
1757 profitMargin: Math.round(margin * 10) / 10,
1758 confidence: aiResponse.confidence,
1759 commission: Math.round(commission * 10) / 10,
1760 advertisingCost: Math.round(advertisingCost * 10) / 10,
1761 delivery: delivery
1762 };
1763 }
1764
1765 alternatives.push(altResult);
1766 }
1767 });
1768
1769 console.log('>>> RETURNING OPTIMIZATION RESULTS <<<');
1770 return {
1771 optimal: optimalResult,
1772 alternatives: alternatives,
1773 currentPrice: Math.round(historicalData.avgPrice),
1774 productData: productData,
1775 allResults: results,
1776 aiReasoning: aiResponse.reasoning,
1777 aiConfidence: aiResponse.confidence,
1778 aiDemandElasticity: realElasticity,
1779 elasticityReliability: elasticityResult.reliability,
1780 elasticityR2: elasticityResult.r2,
1781 elasticityUniquePrices: elasticityResult.uniquePrices,
1782 elasticityDaysUsed: elasticityResult.daysUsed,
1783 explorationPrices: aiResponse.explorationPrices,
1784 competitorData: competitorData,
1785 historicalData: historicalData,
1786 coinvest: coinvest,
1787 drr: drr,
1788 segmentInfo: segmentInfo,
1789 inventoryInfo: inventoryInfo,
1790 marketConstraints: { minMarketPrice, maxMarketPrice }
1791 };
1792
1793 } catch (error) {
1794 console.error('AI analysis failed:', error);
1795 throw error;
1796 }
1797 }
1798
1799 // Create and inject the analysis widget
1800 function createAnalysisWidget() {
1801 console.log('Creating analysis widget (v2.0.1)...');
1802
1803 if (document.getElementById('bayesian-price-optimizer')) {
1804 console.log('Widget already exists');
1805 return;
1806 }
1807
1808 const widget = document.createElement('div');
1809 widget.id = 'bayesian-price-optimizer';
1810 widget.innerHTML = `
1811 <div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
1812 color: white;
1813 padding: 15px;
1814 border-radius: 12px;
1815 margin: 15px 0;
1816 box-shadow: 0 4px 15px rgba(0,0,0,0.2);
1817 font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
1818 width: 100%;
1819 box-sizing: border-box;">
1820 <div style="display: flex; align-items: center; justify-content: space-between; margin-bottom: 12px;">
1821 <h3 style="margin: 0; font-size: 16px; font-weight: 600;">
1822 🎯 Оптимизация цены (AI + Bayesian) v2.0.1
1823 </h3>
1824 </div>
1825
1826 <div style="margin-bottom: 12px;">
1827 <label style="display: block; font-size: 12px; margin-bottom: 4px; opacity: 0.9;">
1828 Ключевой запрос для поиска конкурентов
1829 </label>
1830 <input type="text" id="key-query-input" placeholder="Например: крем для лица увлажняющий"
1831 style="width: 100%; padding: 8px; border: none; border-radius: 6px;
1832 font-size: 14px; box-sizing: border-box;">
1833 </div>
1834
1835 <div style="display: grid; grid-template-columns: repeat(2, 1fr); gap: 10px; margin-bottom: 12px;">
1836 <div>
1837 <label style="display: block; font-size: 12px; margin-bottom: 4px; opacity: 0.9;">
1838 Соинвест (скидка OZON), %
1839 </label>
1840 <input type="number" id="coinvest-input" value="45" min="0" max="100" step="1"
1841 style="width: 100%; padding: 8px; border: none; border-radius: 6px;
1842 font-size: 14px; box-sizing: border-box; font-weight: 600;">
1843 </div>
1844 <div>
1845 <label style="display: block; font-size: 12px; margin-bottom: 4px; opacity: 0.9;">
1846 ДРР (расходы на рекламу), %
1847 </label>
1848 <input type="number" id="drr-input" value="0" min="0" max="100" step="0.1"
1849 style="width: 100%; padding: 8px; border: none; border-radius: 6px;
1850 font-size: 14px; box-sizing: border-box; font-weight: 600;">
1851 </div>
1852 </div>
1853
1854 <button id="analyze-price-btn" style="background: white;
1855 color: #667eea;
1856 border: none;
1857 padding: 10px 20px;
1858 border-radius: 8px;
1859 cursor: pointer;
1860 font-weight: 600;
1861 font-size: 14px;
1862 transition: all 0.3s;
1863 width: 100%;">
1864 Анализировать
1865 </button>
1866
1867 <div id="analysis-results" style="display: none; margin-top: 15px;">
1868 <div style="background: rgba(255,255,255,0.15);
1869 padding: 12px;
1870 border-radius: 8px;
1871 backdrop-filter: blur(10px);
1872 max-width: 600px; box-sizing: border-box;">
1873 <div id="results-content" style="overflow-wrap: break-word; word-wrap: break-word;"></div>
1874 </div>
1875 </div>
1876 <div id="loading-indicator" style="display: none; text-align: center; padding: 20px;">
1877 <div style="display: inline-block; width: 30px; height: 30px; border: 3px solid rgba(255,255,255,0.3); border-top-color: white; border-radius: 50%; animation: spin 1s linear infinite;"></div>
1878 <p style="margin-top: 10px; font-size: 13px;">Анализируем данные с помощью AI...</p>
1879 </div>
1880 </div>
1881 `;
1882
1883 const style = document.createElement('style');
1884 style.textContent = `
1885 @keyframes spin {
1886 to { transform: rotate(360deg); }
1887 }
1888 #analyze-price-btn:hover {
1889 transform: translateY(-2px);
1890 box-shadow: 0 4px 12px rgba(0,0,0,0.15);
1891 }
1892 #bayesian-price-optimizer * {
1893 box-sizing: border-box;
1894 }
1895 `;
1896 document.head.appendChild(style);
1897
1898 const mpsWidget = document.querySelector('.mps-sidebar');
1899 if (mpsWidget) {
1900 mpsWidget.parentElement.insertBefore(widget, mpsWidget.nextSibling);
1901 console.log('Widget inserted after MP Stats');
1902 } else {
1903 document.body.appendChild(widget);
1904 console.log('Widget inserted at body end');
1905 }
1906
1907 const analyzeBtn = document.getElementById('analyze-price-btn');
1908 analyzeBtn.addEventListener('click', performAnalysis);
1909 }
1910
1911 // Perform the price analysis
1912 async function performAnalysis() {
1913 console.log('>>> performAnalysis CALLED (v2.0.1) <<<');
1914
1915 const loadingIndicator = document.getElementById('loading-indicator');
1916 const resultsDiv = document.getElementById('analysis-results');
1917
1918 loadingIndicator.style.display = 'block';
1919 resultsDiv.style.display = 'none';
1920
1921 try {
1922 // Get user input values
1923 const coinvestInput = document.getElementById('coinvest-input');
1924 const drrInput = document.getElementById('drr-input');
1925 const keyQueryInput = document.getElementById('key-query-input');
1926
1927 const coinvest = parseFloat(coinvestInput.value) || 45;
1928 const drr = parseFloat(drrInput.value) || 0;
1929 const keyQuery = keyQueryInput.value.trim();
1930
1931 console.log('User inputs - Coinvest:', coinvest, '%, DRR:', drr, '%, Key Query:', keyQuery);
1932
1933 // Validate inputs
1934 if (coinvest < 0 || coinvest > 100) {
1935 throw new Error('Соинвест должен быть от 0 до 100%');
1936 }
1937 if (drr < 0 || drr > 100) {
1938 throw new Error('ДРР должен быть от 0 до 100%');
1939 }
1940 if (!keyQuery) {
1941 throw new Error('Пожалуйста, введите ключевой запрос для поиска конкурентов');
1942 }
1943
1944 const productId = getProductId();
1945 console.log('Product ID:', productId);
1946
1947 if (!productId) {
1948 throw new Error('Не удалось определить ID товара');
1949 }
1950
1951 const shortSku = getShortSku(productId);
1952 console.log('Short SKU:', shortSku);
1953
1954 if (!shortSku) {
1955 throw new Error('Данные для этого товара не найдены');
1956 }
1957
1958 const productData = PRODUCT_DATA[shortSku];
1959 console.log('Product data:', productData);
1960
1961 if (!productData) {
1962 throw new Error('Данные для этого товара не найдены');
1963 }
1964
1965 console.log('>>> CALLING extractMPStatsData <<<');
1966 const mpStatsData = await extractMPStatsData();
1967 console.log('>>> extractMPStatsData FINISHED <<<');
1968
1969 if (!mpStatsData) {
1970 throw new Error('Не удалось извлечь данные из MP Stats');
1971 }
1972
1973 // Save analysis state before opening search tab
1974 await GM.setValue('analysis_state', JSON.stringify({
1975 coinvest,
1976 drr,
1977 keyQuery,
1978 productId,
1979 shortSku,
1980 mpStatsData,
1981 productData,
1982 timestamp: Date.now()
1983 }));
1984 console.log('Analysis state saved, opening search tab...');
1985
1986 // Clear previous competitor data
1987 await GM.deleteValue('temp_competitors');
1988 await GM.deleteValue('competitors_extracted');
1989
1990 console.log('>>> CALLING extractCompetitorsFromSearch <<<');
1991 await extractCompetitorsFromSearch(keyQuery);
1992
1993 // Wait for competitors to be extracted (poll for data)
1994 console.log('Waiting for competitor data...');
1995 let attempts = 0;
1996 const maxAttempts = 90; // 90 seconds max (increased from 60)
1997
1998 while (attempts < maxAttempts) {
1999 await new Promise(resolve => setTimeout(resolve, 1000));
2000
2001 const extracted = await GM.getValue('competitors_extracted', null);
2002 if (extracted === 'true') {
2003 console.log('Competitors extracted successfully, continuing analysis...');
2004 break;
2005 }
2006
2007 if (extracted === 'failed') {
2008 throw new Error('Не удалось извлечь данные о конкурентах из MPStats');
2009 }
2010
2011 attempts++;
2012 if (attempts % 10 === 0) {
2013 console.log(`Waiting for competitors... ${attempts}/${maxAttempts} seconds`);
2014 }
2015 }
2016
2017 if (attempts >= maxAttempts) {
2018 throw new Error('Timeout: не удалось получить данные о конкурентах за 90 секунд');
2019 }
2020
2021 // Get competitors from storage
2022 const competitorsJson = await GM.getValue('temp_competitors', null);
2023 if (!competitorsJson) {
2024 throw new Error('Не удалось получить данные о конкурентах');
2025 }
2026
2027 const competitorData = JSON.parse(competitorsJson);
2028 console.log('Competitors loaded:', competitorData);
2029
2030 // Clear state
2031 await GM.deleteValue('analysis_state');
2032 await GM.deleteValue('temp_competitors');
2033 await GM.deleteValue('competitors_extracted');
2034
2035 console.log('>>> CALLING bayesianPriceOptimizationWithAI <<<');
2036 const optimization = await bayesianPriceOptimizationWithAI(
2037 mpStatsData,
2038 productData,
2039 competitorData,
2040 coinvest,
2041 drr
2042 );
2043 console.log('>>> bayesianPriceOptimizationWithAI FINISHED <<<');
2044
2045 if (!optimization) {
2046 throw new Error('Ошибка при оптимизации цены');
2047 }
2048
2049 displayResults(optimization, coinvest, drr);
2050
2051 } catch (error) {
2052 console.error('Analysis error:', error);
2053 console.error('Error message:', error.message);
2054 console.error('Error stack:', error.stack);
2055 const resultsContent = document.getElementById('results-content');
2056 resultsContent.innerHTML = `
2057 <div style="color: #fee; padding: 10px; text-align: center;">
2058 <strong>⚠️ Ошибка:</strong><br>
2059 ${error.message || 'Неизвестная ошибка'}
2060 </div>
2061 `;
2062 resultsDiv.style.display = 'block';
2063 } finally {
2064 loadingIndicator.style.display = 'none';
2065 }
2066 }
2067
2068 // Display optimization results
2069 function displayResults(optimization, coinvest, drr) {
2070 const resultsDiv = document.getElementById('analysis-results');
2071 const resultsContent = document.getElementById('results-content');
2072
2073 const { optimal, alternatives, currentPrice, productData, allResults, aiReasoning, competitorData, historicalData } = optimization;
2074
2075 const currentDailySales = historicalData.avgDailySales;
2076
2077 // Calculate actual price from current display price using user's coinvest value
2078 const displayPriceMultiplier = (100 - coinvest) / 100;
2079 const currentActualPrice = currentPrice / displayPriceMultiplier;
2080 const currentCommission = currentActualPrice * productData.commission;
2081 const currentAdvertisingCost = currentActualPrice * (drr / 100);
2082 const currentDelivery = productData.delivery;
2083 const currentDailyProfit = Math.round((currentActualPrice - productData.cost - currentCommission - currentDelivery - currentAdvertisingCost) * currentDailySales * 10) / 10;
2084 const currentDailyRevenue = Math.round(currentPrice * currentDailySales * 10) / 10;
2085 const currentMargin = Math.round(((currentActualPrice - productData.cost - currentCommission - currentDelivery - currentAdvertisingCost) / currentActualPrice) * 100 * 10) / 10;
2086 const currentProfitPerUnit = Math.round(currentActualPrice - productData.cost - currentCommission - currentDelivery - currentAdvertisingCost);
2087
2088 // Calculate percentages for current price
2089 const currentCommissionPercent = Math.round((currentCommission / currentActualPrice) * 100 * 10) / 10;
2090 const currentDeliveryPercent = Math.round((currentDelivery / currentActualPrice) * 100 * 10) / 10;
2091 const currentCostPercent = Math.round((productData.cost / currentActualPrice) * 100 * 10) / 10;
2092 const currentDrrPercent = Math.round((currentAdvertisingCost / currentActualPrice) * 100 * 10) / 10;
2093
2094 // Calculate optimal values
2095 const optimalDailyRevenue = Math.round(optimal.price * optimal.estimatedDailySales * 10) / 10;
2096 const optimalProfitPerUnit = Math.round(optimal.actualPrice - productData.cost - optimal.commission - optimal.delivery - optimal.advertisingCost);
2097
2098 // Calculate percentages for optimal price
2099 const optimalCommissionPercent = Math.round((optimal.commission / optimal.actualPrice) * 100 * 10) / 10;
2100 const optimalDeliveryPercent = Math.round((optimal.delivery / optimal.actualPrice) * 100 * 10) / 10;
2101 const optimalCostPercent = Math.round((productData.cost / optimal.actualPrice) * 100 * 10) / 10;
2102 const optimalDrrPercent = Math.round((optimal.advertisingCost / optimal.actualPrice) * 100 * 10) / 10;
2103
2104 // Calculate all changes
2105 const priceChange = Math.round(((optimal.price - currentPrice) / currentPrice) * 100);
2106 const priceDiff = Math.round(optimal.price - currentPrice);
2107 const actualPriceChange = Math.round(((optimal.actualPrice - currentActualPrice) / currentActualPrice) * 100);
2108 const actualPriceDiff = Math.round(optimal.actualPrice - currentActualPrice);
2109 const revenueChange = Math.round(((optimalDailyRevenue - currentDailyRevenue) / currentDailyRevenue) * 100);
2110 const revenueDiff = Math.round(optimalDailyRevenue - currentDailyRevenue);
2111 const profitDiff = Math.round((optimal.estimatedDailyProfit - currentDailyProfit) * 10) / 10;
2112 const profitChange = currentDailyProfit !== 0 ? Math.round((profitDiff / Math.abs(currentDailyProfit)) * 100) : 0;
2113 const salesChange = Math.round(((optimal.estimatedDailySales - currentDailySales) / currentDailySales) * 100);
2114 const salesDiff = Math.round((optimal.estimatedDailySales - currentDailySales) * 10) / 10;
2115 const marginChange = Math.round((optimal.profitMargin - currentMargin) * 10) / 10;
2116 const profitPerUnitChange = currentProfitPerUnit > 0 ? Math.round(((optimalProfitPerUnit - currentProfitPerUnit) / currentProfitPerUnit) * 100) : 0;
2117 const profitPerUnitDiff = optimalProfitPerUnit - currentProfitPerUnit;
2118
2119 // Calculate percentage changes for costs
2120 const commissionPercentChange = Math.round((optimalCommissionPercent - currentCommissionPercent) * 10) / 10;
2121 const deliveryPercentChange = Math.round((optimalDeliveryPercent - currentDeliveryPercent) * 10) / 10;
2122 const costPercentChange = Math.round((optimalCostPercent - currentCostPercent) * 10) / 10;
2123 const drrPercentChange = Math.round((optimalDrrPercent - currentDrrPercent) * 10) / 10;
2124
2125 // Format AI reasoning with line breaks
2126 const formattedReasoning = aiReasoning
2127 .replace(/\. /g, '.<br>• ')
2128 .replace(/^/, '• ');
2129
2130 // Determine elasticity reliability color and text
2131 let reliabilityColor = '#ef4444'; // red for bad
2132 let reliabilityText = 'Плохо';
2133 let reliabilityIcon = '⚠️';
2134
2135 if (optimization.elasticityReliability === 'good') {
2136 reliabilityColor = '#10b981'; // green
2137 reliabilityText = 'Хорошо';
2138 reliabilityIcon = '✅';
2139 } else if (optimization.elasticityReliability === 'satisfactory') {
2140 reliabilityColor = '#f59e0b'; // orange
2141 reliabilityText = 'Удовлетворительно';
2142 reliabilityIcon = '⚡';
2143 }
2144
2145 let html = `
2146 <div style="background: rgba(59, 130, 246, 0.2); padding: 10px; border-radius: 8px; margin-bottom: 12px; border-left: 4px solid #3b82f6;">
2147 <div style="font-size: 13px; font-weight: 600; margin-bottom: 6px; opacity: 0.9;">📊 Эластичность спроса:</div>
2148 <div style="font-size: 14px; line-height: 1.6; opacity: 0.95;">
2149 <div style="margin-bottom: 4px;">
2150 <strong>Коэффициент:</strong> ${optimization.aiDemandElasticity.toFixed(4)}
2151 <span style="font-size: 13px; opacity: 0.8;">(при изменении цены на 1%, продажи изменятся на ${(optimization.aiDemandElasticity * 100).toFixed(1)}%)</span>
2152 </div>
2153 <div style="margin-bottom: 4px;">
2154 <strong>Достоверность:</strong>
2155 <span style="color: ${reliabilityColor}; font-weight: 600;">${reliabilityIcon} ${reliabilityText}</span>
2156 </div>
2157 <div style="font-size: 12px; opacity: 0.8;">
2158 R² = ${optimization.elasticityR2.toFixed(4)} • ${optimization.elasticityUniquePrices} уникальных цен • ${optimization.elasticityDaysUsed} дней данных
2159 </div>
2160 </div>
2161 </div>
2162
2163 <div style="background: rgba(16, 185, 129, 0.2); padding: 10px; border-radius: 8px; margin-bottom: 12px; border-left: 4px solid #10b981;">
2164 <div style="font-size: 13px; font-weight: 600; margin-bottom: 6px; opacity: 0.9;">🤖 Рекомендация AI:</div>
2165 <div style="font-size: 14px; line-height: 1.6; opacity: 0.95;">${formattedReasoning}</div>
2166 </div>
2167 `;
2168
2169 if (competitorData && competitorData.length > 0) {
2170 // Calculate total revenue for percentage
2171 const totalRevenue = competitorData.reduce((sum, c) => sum + c.revenue30days, 0);
2172
2173 html += `
2174 <div style="background: rgba(139, 92, 246, 0.2); padding: 10px; border-radius: 8px; margin-bottom: 12px; border-left: 4px solid #8b5cf6;">
2175 <div style="font-size: 13px; font-weight: 600; margin-bottom: 8px; opacity: 0.9;">
2176 🏪 Конкуренты (${competitorData.length} шт):
2177 </div>
2178 <div style="overflow-x: auto;">
2179 <table style="width: 100%; border-collapse: collapse; font-size: 12px;">
2180 <thead>
2181 <tr style="border-bottom: 1px solid rgba(255,255,255,0.3);">
2182 <th style="text-align: left; padding: 6px; opacity: 0.9;">#</th>
2183 <th style="text-align: left; padding: 6px; opacity: 0.9;">Бренд</th>
2184 <th style="text-align: right; padding: 6px; opacity: 0.9;">Цена</th>
2185 <th style="text-align: right; padding: 6px; opacity: 0.9;">Продажи</th>
2186 <th style="text-align: right; padding: 6px; opacity: 0.9;">Выручка</th>
2187 <th style="text-align: right; padding: 6px; opacity: 0.9;">% выручки</th>
2188 </tr>
2189 </thead>
2190 <tbody>
2191 `;
2192
2193 competitorData.slice(0, 10).forEach((comp, index) => {
2194 const competitorUrl = comp.sku ? `https://www.ozon.ru/product/${comp.sku}/` : '#';
2195 const salesInfo = comp.sales30days ? `${comp.sales30days} шт` : 'н/д';
2196 const revenueInfo = comp.revenue30days ? `${comp.revenue30days.toLocaleString()} ₽` : 'н/д';
2197 const revenuePercent = totalRevenue > 0 ? ((comp.revenue30days / totalRevenue) * 100).toFixed(1) : '0.0';
2198
2199 html += `
2200 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2201 <td style="padding: 8px 6px; opacity: 0.8;">${index + 1}</td>
2202 <td style="padding: 8px 6px;">
2203 <a href="${competitorUrl}" target="_blank" style="color: white; text-decoration: none; opacity: 0.9;">
2204 ${comp.brand || 'N/A'}
2205 </a>
2206 </td>
2207 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${comp.price.toLocaleString()} ₽</td>
2208 <td style="padding: 8px 6px; text-align: right;">${salesInfo}</td>
2209 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${revenueInfo}</td>
2210 <td style="padding: 8px 6px; text-align: right; opacity: 0.9;">${revenuePercent}%</td>
2211 </tr>
2212 `;
2213 });
2214
2215 html += `
2216 </tbody>
2217 </table>
2218 </div>
2219 </div>
2220 `;
2221
2222 // === NEW: Calculate recommended prices based on competitors ===
2223
2224 // ШАГ 1: Средневзвешенная цена (вес 40%)
2225 let weightedSum = 0;
2226 let totalWeight = 0;
2227 competitorData.forEach((comp, index) => {
2228 const position = index + 1;
2229 const weight = position <= 5 ? comp.revenue30days * 2 : comp.revenue30days;
2230 weightedSum += comp.price * weight;
2231 totalWeight += weight;
2232 });
2233 const weightedAvgPrice = totalWeight > 0 ? Math.round(weightedSum / totalWeight) : 0;
2234
2235 // ШАГ 2: Цена с лучшей конверсией (вес 30%)
2236 const competitorsWithConversion = competitorData.map(comp => ({
2237 ...comp,
2238 conversion: comp.sales30days > 0 ? comp.sales30days / comp.price : 0
2239 }));
2240 competitorsWithConversion.sort((a, b) => b.conversion - a.conversion);
2241 const top3Conversion = competitorsWithConversion.slice(0, 3);
2242 const bestConversionPrice = top3Conversion.length > 0
2243 ? Math.round(top3Conversion.reduce((sum, c) => sum + c.price, 0) / top3Conversion.length)
2244 : 0;
2245
2246 // ШАГ 3: Медианная цена топ-10 (вес 30%)
2247 const top10Prices = competitorData.slice(0, 10).map(c => c.price).sort((a, b) => a - b);
2248 let medianPrice = 0;
2249 if (top10Prices.length > 0) {
2250 const mid = Math.floor(top10Prices.length / 2);
2251 medianPrice = top10Prices.length % 2 === 0
2252 ? Math.round((top10Prices[mid - 1] + top10Prices[mid]) / 2)
2253 : top10Prices[mid];
2254 }
2255
2256 // ШАГ 3.5: Эластичность запроса (на основе данных конкурентов)
2257 let queryElasticity = -1.5; // default
2258 let queryElasticityR2 = 0;
2259
2260 if (competitorData.length >= 5) {
2261 console.log('=== CALCULATING QUERY ELASTICITY (Cross-Sectional) ===');
2262 console.log('Using competitor data:', competitorData.map(c => `${c.brand}: ${c.price}₽, ${c.sales30days} шт/30д`));
2263
2264 // Используем лог-линейную регрессию для конкурентов
2265 const logPrices = competitorData.map(c => Math.log(c.price));
2266 const logSales = competitorData.map(c => Math.log(c.sales30days + 1));
2267
2268 console.log('Log prices:', logPrices.map(p => p.toFixed(4)));
2269 console.log('Log sales:', logSales.map(s => s.toFixed(4)));
2270
2271 const n = competitorData.length;
2272 const sumX = logPrices.reduce((a, b) => a + b, 0);
2273 const sumY = logSales.reduce((a, b) => a + b, 0);
2274 const sumXY = logPrices.reduce((a, b, i) => a + b * logSales[i], 0);
2275 const sumX2 = logPrices.reduce((a, b) => a + b * b, 0);
2276
2277 console.log(`Query elasticity regression: n=${n}, sumX=${sumX.toFixed(2)}, sumY=${sumY.toFixed(2)}, sumXY=${sumXY.toFixed(2)}, sumX2=${sumX2.toFixed(2)}`);
2278
2279 const denominator = n * sumX2 - sumX * sumX;
2280 console.log('Denominator:', denominator.toFixed(4));
2281
2282 if (denominator !== 0) {
2283 const slope = (n * sumXY - sumX * sumY) / denominator;
2284 const intercept = (sumY - slope * sumX) / n;
2285
2286 console.log(`Query OLS results: slope (elasticity) = ${slope.toFixed(4)}, intercept = ${intercept.toFixed(4)}`);
2287
2288 // Calculate R²
2289 const yMean = sumY / n;
2290 const ssTotal = logSales.reduce((s, y) => s + Math.pow(y - yMean, 2), 0);
2291 const predicted = logPrices.map(x => slope * x + intercept);
2292 const ssResidual = logSales.reduce((s, y, i) => s + Math.pow(y - predicted[i], 2), 0);
2293 const r2 = ssTotal > 0 ? 1 - (ssResidual / ssTotal) : 0;
2294
2295 console.log(`Query R²: ssTotal=${ssTotal.toFixed(4)}, ssResidual=${ssResidual.toFixed(4)}, R²=${r2.toFixed(4)}`);
2296
2297 // Clamp to reasonable range
2298 queryElasticity = Math.max(-3.0, Math.min(-0.3, slope));
2299 queryElasticityR2 = r2;
2300
2301 console.log('Query elasticity calculated:', queryElasticity.toFixed(4), 'R²:', r2.toFixed(4));
2302 console.log('⚠️ NOTE: Cross-sectional elasticity may differ from time-series elasticity due to brand effects, quality differences, and search position');
2303 } else {
2304 console.log('⚠️ Query elasticity: denominator is zero, using default -1.5');
2305 }
2306 }
2307
2308 // ШАГ 4: Базовая оптимальная цена
2309 const baseOptimalPrice = Math.round(
2310 weightedAvgPrice * 0.4 +
2311 bestConversionPrice * 0.3 +
2312 medianPrice * 0.3
2313 );
2314
2315 // ШАГ 6: Три стратегии
2316 const marketCapturePrice = Math.round(baseOptimalPrice * 0.85);
2317 const optimalStrategyPrice = baseOptimalPrice;
2318 const premiumPrice = Math.round(baseOptimalPrice * 1.15);
2319
2320 html += `
2321 <div style="background: rgba(236, 72, 153, 0.2); padding: 10px; border-radius: 8px; margin-bottom: 12px; border-left: 4px solid #ec4899;">
2322 <div style="font-size: 13px; font-weight: 600; margin-bottom: 8px; opacity: 0.9;">
2323 💰 Рекомендованные цены для запроса
2324 </div>
2325
2326 <div style="margin-bottom: 10px; padding: 8px; background: rgba(255,255,255,0.1); border-radius: 6px;">
2327 <div style="font-size: 12px; font-weight: 600; margin-bottom: 6px; opacity: 0.9;">📈 Базовые метрики:</div>
2328 <div style="font-size: 13px; line-height: 1.8;">
2329 <div>• <strong>Средневзвешенная цена:</strong> ${weightedAvgPrice} ₽ <span style="opacity: 0.7;">(вес 40%)</span></div>
2330 <div>• <strong>Цена с лучшей конверсией:</strong> ${bestConversionPrice} ₽ <span style="opacity: 0.7;">(вес 30%)</span></div>
2331 <div>• <strong>Медианная цена топ-10:</strong> ${medianPrice} ₽ <span style="opacity: 0.7;">(вес 30%)</span></div>
2332 <div>• <strong>Эластичность запроса:</strong> ${queryElasticity.toFixed(4)} <span style="opacity: 0.7;">(R² = ${queryElasticityR2.toFixed(3)}, ${competitorData.length} конкурентов)</span></div>
2333 </div>
2334 </div>
2335
2336 <div style="font-size: 12px; font-weight: 600; margin-bottom: 6px; opacity: 0.9;">🎯 Стратегии ценообразования:</div>
2337 <div style="display: grid; grid-template-columns: repeat(3, 1fr); gap: 8px;">
2338 <div style="background: rgba(239, 68, 68, 0.3); padding: 8px; border-radius: 6px; text-align: center;">
2339 <div style="font-size: 11px; opacity: 0.8; margin-bottom: 4px;">🔥 Захват рынка</div>
2340 <div style="font-size: 18px; font-weight: 700;">${marketCapturePrice} ₽</div>
2341 <div style="font-size: 10px; opacity: 0.7; margin-top: 2px;">-15% от базовой</div>
2342 </div>
2343 <div style="background: rgba(16, 185, 129, 0.3); padding: 8px; border-radius: 6px; text-align: center;">
2344 <div style="font-size: 11px; opacity: 0.8; margin-bottom: 4px;">⚖️ Оптимальная</div>
2345 <div style="font-size: 18px; font-weight: 700;">${optimalStrategyPrice} ₽</div>
2346 <div style="font-size: 10px; opacity: 0.7; margin-top: 2px;">базовая цена</div>
2347 </div>
2348 <div style="background: rgba(245, 158, 11, 0.3); padding: 8px; border-radius: 6px; text-align: center;">
2349 <div style="font-size: 11px; opacity: 0.8; margin-bottom: 4px;">👑 Премиум</div>
2350 <div style="font-size: 18px; font-weight: 700;">${premiumPrice} ₽</div>
2351 <div style="font-size: 10px; opacity: 0.7; margin-top: 2px;">+25% от базовой</div>
2352 </div>
2353 </div>
2354 `;
2355 }
2356
2357 html += `
2358 <div style="background: #10b981; padding: 5px 10px; border-radius: 6px; font-size: 13px; font-weight: 600; display: inline-block; margin-bottom: 10px;">
2359 ✨ ОПТИМАЛЬНАЯ ЦЕНА
2360 </div>
2361
2362 <table style="width: 100%; border-collapse: collapse; margin-top: 8px; font-size: 14px;">
2363 <thead>
2364 <tr style="border-bottom: 2px solid rgba(255,255,255,0.3);">
2365 <th style="text-align: left; padding: 6px; font-size: 14px; opacity: 0.9;">Показатель</th>
2366 <th style="text-align: right; padding: 6px; font-size: 14px; opacity: 0.9;">Текущая</th>
2367 <th style="text-align: right; padding: 6px; font-size: 14px; opacity: 0.9;">Рекомендуемая</th>
2368 <th style="text-align: right; padding: 6px; font-size: 14px; opacity: 0.9;">Δ</th>
2369 </tr>
2370 </thead>
2371 <tbody>
2372 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2373 <td style="padding: 8px 6px; font-size: 14px;">Цена реализации</td>
2374 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentPrice} ₽</td>
2375 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2376 ${optimal.price} ₽
2377 <span style="color: ${priceChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2378 (${priceChange >= 0 ? '+' : ''}${priceChange}%)
2379 </span>
2380 </td>
2381 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${priceDiff >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2382 ${priceDiff >= 0 ? '+' : ''}${priceDiff} ₽
2383 </td>
2384 </tr>
2385 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2386 <td style="padding: 8px 6px; font-size: 14px;">Фактическая цена</td>
2387 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${Math.round(currentActualPrice)} ₽</td>
2388 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2389 ${Math.round(optimal.actualPrice)} ₽
2390 <span style="color: ${actualPriceChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2391 (${actualPriceChange >= 0 ? '+' : ''}${actualPriceChange}%)
2392 </span>
2393 </td>
2394 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${actualPriceDiff >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2395 ${actualPriceDiff >= 0 ? '+' : ''}${actualPriceDiff} ₽
2396 </td>
2397 </tr>
2398 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2399 <td style="padding: 8px 6px; font-size: 14px;">Прибыль/день</td>
2400 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentDailyProfit} ₽</td>
2401 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2402 ${optimal.estimatedDailyProfit} ₽
2403 <span style="color: ${profitChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2404 (${profitChange >= 0 ? '+' : ''}${profitChange}%)
2405 </span>
2406 </td>
2407 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${profitDiff >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2408 ${profitDiff >= 0 ? '+' : ''}${profitDiff} ₽
2409 </td>
2410 </tr>
2411 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2412 <td style="padding: 8px 6px; font-size: 14px;">Выручка/день</td>
2413 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentDailyRevenue} ₽</td>
2414 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2415 ${optimalDailyRevenue} ₽
2416 <span style="color: ${revenueChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2417 (${revenueChange >= 0 ? '+' : ''}${revenueChange}%)
2418 </span>
2419 </td>
2420 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${revenueDiff >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2421 ${revenueDiff >= 0 ? '+' : ''}${revenueDiff} ₽
2422 </td>
2423 </tr>
2424 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2425 <td style="padding: 8px 6px; font-size: 14px;">Продажи/день</td>
2426 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentDailySales.toFixed(1)} шт</td>
2427 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2428 ${optimal.estimatedDailySales} шт
2429 <span style="color: ${salesChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2430 (${salesChange >= 0 ? '+' : ''}${salesChange}%)
2431 </span>
2432 </td>
2433 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${salesDiff >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2434 ${salesDiff >= 0 ? '+' : ''}${salesDiff} шт
2435 </td>
2436 </tr>
2437 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2438 <td style="padding: 8px 6px; font-size: 14px;">Маржа %</td>
2439 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentMargin}%</td>
2440 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2441 ${optimal.profitMargin}%
2442 <span style="color: ${marginChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2443 (${marginChange >= 0 ? '+' : ''}${marginChange}%)
2444 </span>
2445 </td>
2446 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${marginChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2447 ${marginChange >= 0 ? '+' : ''}${marginChange}%
2448 </td>
2449 </tr>
2450 <tr style="border-bottom: 1px solid rgba(255,255,255,0.1);">
2451 <td style="padding: 8px 6px; font-size: 14px;">Прибыль/шт</td>
2452 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentProfitPerUnit} ₽</td>
2453 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2454 ${optimalProfitPerUnit} ₽
2455 <span style="color: ${profitPerUnitChange >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2456 (${profitPerUnitChange >= 0 ? '+' : ''}${profitPerUnitChange}%)
2457 </span>
2458 </td>
2459 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${profitPerUnitDiff >= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2460 ${profitPerUnitDiff >= 0 ? '+' : ''}${profitPerUnitDiff} ₽
2461 </td>
2462 </tr>
2463 <tr>
2464 <td style="padding: 8px 6px; font-size: 14px;">Комиссия %</td>
2465 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentCommissionPercent}%</td>
2466 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2467 ${optimalCommissionPercent}%
2468 <span style="color: ${commissionPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2469 (${commissionPercentChange >= 0 ? '+' : ''}${commissionPercentChange}%)
2470 </span>
2471 </td>
2472 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${commissionPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2473 ${commissionPercentChange >= 0 ? '+' : ''}${commissionPercentChange}%
2474 </td>
2475 </tr>
2476 <tr>
2477 <td style="padding: 8px 6px; font-size: 14px;">Доставка %</td>
2478 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentDeliveryPercent}%</td>
2479 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2480 ${optimalDeliveryPercent}%
2481 <span style="color: ${deliveryPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2482 (${deliveryPercentChange >= 0 ? '+' : ''}${deliveryPercentChange}%)
2483 </span>
2484 </td>
2485 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${deliveryPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2486 ${deliveryPercentChange >= 0 ? '+' : ''}${deliveryPercentChange}%
2487 </td>
2488 </tr>
2489 <tr>
2490 <td style="padding: 8px 6px; font-size: 14px;">Себестоимость %</td>
2491 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentCostPercent}%</td>
2492 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2493 ${optimalCostPercent}%
2494 <span style="color: ${costPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2495 (${costPercentChange >= 0 ? '+' : ''}${costPercentChange}%)
2496 </span>
2497 </td>
2498 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${costPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2499 ${costPercentChange >= 0 ? '+' : ''}${costPercentChange}%
2500 </td>
2501 </tr>
2502 <tr>
2503 <td style="padding: 8px 6px; font-size: 14px;">ДРР %</td>
2504 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">${currentDrrPercent}%</td>
2505 <td style="padding: 8px 6px; text-align: right; font-weight: 600;">
2506 ${optimalDrrPercent}%
2507 <span style="color: ${drrPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px; font-weight: 700; margin-left: 4px;">
2508 (${drrPercentChange >= 0 ? '+' : ''}${drrPercentChange}%)
2509 </span>
2510 </td>
2511 <td style="padding: 8px 6px; text-align: right; font-weight: 600; color: ${drrPercentChange <= 0 ? '#10b981' : '#ef4444'}; font-size: 13px;">
2512 ${drrPercentChange >= 0 ? '+' : ''}${drrPercentChange}%
2513 </td>
2514 </tr>
2515 </tbody>
2516 </table>
2517 `;
2518
2519 if (alternatives && alternatives.length > 0) {
2520 html += `
2521 <div style="margin-top: 12px; padding: 8px; background: rgba(255,255,255,0.1); border-radius: 6px; font-size: 12px; opacity: 0.8;">
2522 💡 Анализ: ${allResults.length} вариантов цен. Уверенность: ${Math.round(optimal.confidence * 100)}%
2523 </div>
2524 `;
2525 }
2526
2527 resultsContent.innerHTML = html;
2528 resultsDiv.style.display = 'block';
2529
2530 setTimeout(() => createPriceChart(optimization), 100);
2531 }
2532
2533 // Create price analysis chart
2534 function createPriceChart(optimization) {
2535 const oldChart = document.getElementById('price-analysis-chart');
2536 if (oldChart) {
2537 oldChart.parentElement.remove();
2538 }
2539
2540 const canvas = document.createElement('canvas');
2541 canvas.id = 'price-analysis-chart';
2542 canvas.style.cssText = 'width: 100% !important; height: 250px !important;';
2543
2544 const chartContainer = document.createElement('div');
2545 chartContainer.style.cssText = 'margin-top: 12px; padding: 12px; background: rgba(255,255,255,0.1); border-radius: 8px; max-width: 600px; box-sizing: border-box;';
2546 chartContainer.innerHTML = `
2547 <div style="font-size: 14px; margin-bottom: 8px; opacity: 0.9; font-weight: 600;">
2548 📈 График зависимости от цены
2549 </div>
2550 `;
2551 chartContainer.appendChild(canvas);
2552
2553 const resultsContent = document.getElementById('results-content');
2554 resultsContent.appendChild(chartContainer);
2555
2556 const sortedResults = [...optimization.allResults].sort((a, b) => a.price - b.price);
2557 const prices = sortedResults.map(r => r.price);
2558 const sales = sortedResults.map(r => r.estimatedDailySales);
2559 const revenue = sortedResults.map(r => Math.round(r.price * r.estimatedDailySales));
2560 const profit = sortedResults.map(r => r.estimatedDailyProfit);
2561
2562 const ctx = canvas.getContext('2d');
2563 window.priceAnalysisChart = new Chart(ctx, {
2564 type: 'line',
2565 data: {
2566 labels: prices,
2567 datasets: [
2568 {
2569 label: 'Продажи (шт/д)',
2570 data: sales,
2571 borderColor: '#10b981',
2572 backgroundColor: 'rgba(16, 185, 129, 0.1)',
2573 yAxisID: 'y',
2574 tension: 0.4,
2575 borderWidth: 2
2576 },
2577 {
2578 label: 'Выручка (₽/д)',
2579 data: revenue,
2580 borderColor: '#f59e0b',
2581 backgroundColor: 'rgba(245, 158, 11, 0.1)',
2582 yAxisID: 'y1',
2583 tension: 0.4,
2584 borderWidth: 2
2585 },
2586 {
2587 label: 'Прибыль (₽/д)',
2588 data: profit,
2589 borderColor: '#ef4444',
2590 backgroundColor: 'rgba(239, 68, 68, 0.1)',
2591 yAxisID: 'y1',
2592 tension: 0.4,
2593 borderWidth: 3
2594 }
2595 ]
2596 },
2597 options: {
2598 responsive: true,
2599 maintainAspectRatio: true,
2600 aspectRatio: 2.2,
2601 interaction: {
2602 mode: 'index',
2603 intersect: false,
2604 },
2605 plugins: {
2606 legend: {
2607 position: 'top',
2608 labels: {
2609 usePointStyle: true,
2610 padding: 12,
2611 font: { size: 12 },
2612 color: 'white',
2613 boxWidth: 8,
2614 boxHeight: 8
2615 }
2616 },
2617 tooltip: {
2618 backgroundColor: 'rgba(0, 0, 0, 0.8)',
2619 padding: 10,
2620 titleFont: { size: 13 },
2621 bodyFont: { size: 12 },
2622 callbacks: {
2623 title: function(context) {
2624 return 'Цена: ' + context[0].label + ' ₽';
2625 },
2626 label: function(context) {
2627 let label = context.dataset.label || '';
2628 if (label) {
2629 label += ': ';
2630 }
2631 if (context.parsed.y !== null) {
2632 if (label.includes('шт')) {
2633 label += context.parsed.y.toFixed(1);
2634 } else {
2635 label += Math.round(context.parsed.y);
2636 }
2637 }
2638 return label;
2639 }
2640 }
2641 }
2642 },
2643 scales: {
2644 x: {
2645 title: {
2646 display: true,
2647 text: 'Цена (₽)',
2648 font: { size: 12, weight: 'bold' },
2649 color: 'white'
2650 },
2651 ticks: {
2652 maxTicksLimit: 8,
2653 font: { size: 11 },
2654 color: 'rgba(255, 255, 255, 0.8)'
2655 },
2656 grid: {
2657 color: 'rgba(255, 255, 255, 0.1)'
2658 }
2659 },
2660 y: {
2661 type: 'linear',
2662 display: true,
2663 position: 'left',
2664 title: {
2665 display: true,
2666 text: 'Продажи',
2667 color: '#10b981',
2668 font: { size: 12 }
2669 },
2670 ticks: {
2671 font: { size: 11 },
2672 color: 'rgba(255, 255, 255, 0.8)'
2673 },
2674 grid: {
2675 color: 'rgba(255, 255, 255, 0.1)'
2676 }
2677 },
2678 y1: {
2679 type: 'linear',
2680 display: true,
2681 position: 'right',
2682 title: {
2683 display: true,
2684 text: 'Выручка/Прибыль',
2685 color: '#f59e0b',
2686 font: { size: 12 }
2687 },
2688 grid: {
2689 drawOnChartArea: false,
2690 },
2691 ticks: {
2692 font: { size: 11 },
2693 color: 'rgba(255, 255, 255, 0.8)'
2694 }
2695 }
2696 }
2697 }
2698 });
2699
2700 console.log('График создан успешно');
2701 }
2702
2703 // Wait for MP Stats widget to load
2704 function waitForMPStats() {
2705 console.log('Waiting for MP Stats widget...');
2706
2707 let checkCount = 0;
2708 const maxChecks = 30;
2709
2710 const checkInterval = setInterval(() => {
2711 checkCount++;
2712 console.log(`Check ${checkCount}/${maxChecks} for MP Stats widget...`);
2713
2714 const mpsWidget = document.querySelector('.mps-sidebar');
2715
2716 if (mpsWidget) {
2717 console.log('MP Stats widget found, creating analysis widget...');
2718 clearInterval(checkInterval);
2719 setTimeout(() => {
2720 console.log('Creating analysis widget now...');
2721 createAnalysisWidget();
2722 }, 2000);
2723 } else if (checkCount >= maxChecks) {
2724 clearInterval(checkInterval);
2725 console.log('Stopped waiting for MP Stats widget - timeout reached');
2726 }
2727 }, 1000);
2728 }
2729
2730 // Initialize
2731 function init() {
2732 console.log('OZON Price Optimizer initialized (v2.0.1)');
2733 console.log('Current URL:', window.location.href);
2734
2735 // Check if we're on a search page and need to extract competitors
2736 if (window.location.href.includes('/search/') || window.location.href.includes('/category/')) {
2737 console.log('Search/category page detected, checking for competitor extraction...');
2738 extractCompetitorsInSearchPage();
2739 return;
2740 }
2741
2742 const productId = getProductId();
2743 if (!productId) {
2744 console.log('Not a product page, skipping...');
2745 return;
2746 }
2747
2748 console.log('Product page detected, waiting for MP Stats widget...');
2749
2750 if (document.readyState === 'loading') {
2751 document.addEventListener('DOMContentLoaded', waitForMPStats);
2752 } else {
2753 waitForMPStats();
2754 }
2755 }
2756
2757 init();
2758})();