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How to start using LuckData’s e-commerce API?

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Popular Articles

Competitive Product Monitoring System in Action: How to Detect TikTok/Douyin Promotions Within One Day

In industries such as fast fashion, personal care, and consumer electronics, launching and promoting new products simultaneously has become the norm. If a company can detect in real time whether a competitor is launching, advertising, or live streaming on platforms like TikTok or Douyin, it can gain a first-mover advantage in both exposure and conversion. This article explains how to build a high-frequency, low-latency competitive product monitoring system using LuckData APIs.1. System Architecture Overview[Competitor Keyword List] ↓ [Douyin Trending API] ← [TikTok Video Search API] ↓ [Video Info + User Profile + Content Trends] ↓ [Matched New Product/Promotion?] → [AI Auto-Tagging] ↓ [Product Detail / Livestream Page Match] ← [Lazada/Pinduoduo Product APIs] ↓ [Abnormal Promotion Detection] → Alert System + Report Push 2. Real-Time Competitor Detection with Douyin Trending + Video Detail API✅ Douyin Trending Content API (LuckData Douyin Trending API)GET https://luckdata.io/api/douyin-API/get_xv5p? city=310000&type=rise_heat&start_date=20241223&end_date=20241224&page_size=20 Regularly pulling trending videos on Douyin helps capture rapidly rising content. When matched with target brand keywords, these videos become strong indicators of new product launches or promotions.✅ Video Detail API (includes trends, author, tags)GET https://luckdata.io/api/douyin-API/get_pa29? type=items,cnt,trends,author&item_id=7451571619450883355 Combining tags, author info, and trend data helps identify whether the video is official brand content or influencer collaboration, giving insights into the type of promotion.Python Example Code:import requests def fetch_hot_douyin_videos(city_code="310000"): url = "https://luckdata.io/api/douyin-API/get_xv5p" params = { "city": city_code, "type": "rise_heat", "start_date": "20241223", "end_date": "20241224", "page_size": 20 } res = requests.get(url, params=params) return res.json()["data"] def get_video_detail(item_id): url = "https://luckdata.io/api/douyin-API/get_pa29" params = { "type": "items,cnt,trends,author", "item_id": item_id } res = requests.get(url, params=params) return res.json()["data"] Use brand names and SKU keywords such as "Vaseline Cream," "Anker Power Bank," or "Banana Underwear" to match content relevant to competitor products.3. Track Competitor Videos and Livestreams Using TikTok APILuckData’s TikTok API allows keyword-based searches to detect new videos and profile activity on TikTok, providing cross-border market signals.✅ Video Search by KeywordGET https://luckdata.io/api/tiktok-api/searchVideoListByKeywords? keyword=anker&region=us&page=1 Set region and pagination to extract brand-related short videos.✅ Check If a Profile Recently Went LiveGET https://luckdata.io/api/tiktok-api/userPostVideos? user_id=xyz123 By checking the latest posted videos and isLive field, you can detect whether a brand account has been livestreaming.Example Output:BrandLive StatusLive TimeVideo Title Keyword MatchAnker✅2024-12-23"New Charging Product"Vaseline❌-None4. Track New Product Listings on E-Commerce Platforms (e.g. Lazada)LuckData offers e-commerce APIs to detect product launches, promotional tags, or multimedia changes such as added short videos or TikTok widgets.✅ Product Search via KeywordGET https://luckdata.io/api/lazada-online-api/gvqvkzpb7xzb? page=1&site=vn&query=vaseline Returned fields can indicate whether a product is marked as “new,” has experienced recent price changes, or includes embedded videos.Such data supports identifying launch timing and multi-platform promotional alignment.5. Build an Abnormal Promotion Detection ModelDefine anomaly rules based on historical benchmarks to detect and flag significant changes in promotion activity.MetricAnomaly RuleVideo Count>5 new videos for a brand in a single dayVideo View Spike>300% increase for the same SKU vs. previous dayEngagement SpikeRapid rise in likes/shares/commentsTikTok Search VolumeKeyword-related videos exceed defined thresholdNew SKUs>3 new SKUs listed in a single dayUse Python scripts, scheduled jobs, and webhooks to send alerts to Slack or enterprise messaging systems.6. Sample Output: Daily Promotion Monitoring Report{ "date": "2024-12-24", "brand": "Vaseline", "platforms": { "Douyin": { "new_videos": 6, "top_keywords": ["Moisturizing", "Winter Skincare"], "suspected_launch": true }, "TikTok": { "new_videos": 4, "region": "US", "is_live": false }, "Lazada": { "new_SKUs": 2, "lowest_price": "19.9", "listing_time": "Last 24 Hours" } }, "status": "High Attention", "action": "Sync with marketing team to evaluate launch cadence" } ✅ SummaryBy using LuckData’s Douyin, TikTok, and Lazada APIs, you can monitor competitor product launches and promotional activity in near real-time.Douyin trending content and keyword matching help surface new content quickly.E-commerce platform data supports evaluating product launch frequency and SKU rollout.Anomaly detection combined with alert systems enables “within-a-day” discovery of competitor movements.Articles related to APIs :Insights into Emerging Markets: Leveraging Social and E-commerce APIs to Track Consumption Trends in Lower-Tier CitiesOne-Week Build: How a Zero-Tech Team Can Quickly Launch an "E-commerce + Social Media" Data PlatformCross-Platform SKU Mapping and Unified Metric System: Building a Standardized View of Equivalent Products Across E-Commerce SitesPractical Guide to E-commerce Ad Creatives: Real-Time A/B Testing with API DataIntegrated Brand Sentiment Monitoring: Smart Consolidation and Early Warning System for Multi-Platform Keywords and Competitor ReviewsAPI + AI: Building an LLM-Powered System for Automated Product Copy and Short Video Scripts

Insights into Emerging Markets: Leveraging Social and E-commerce APIs to Track Consumption Trends in Lower-Tier Cities

From “Pinduoduo’s 10-Billion-Yuan Subsidy” to “Douyin Group Buys Reaching County-Level Markets,” lower-tier cities (tier-3 and below) have become the new growth frontier for brands. The rapid and fragmented consumer trends in these regions are difficult to capture using traditional methods. This article introduces how to utilize API tools from LuckData to conduct high-frequency monitoring, identify viral content, and analyze product conversion trends to help brands seize emerging opportunities.ObjectivesUse Douyin API to extract trending videos from tier-3 and tier-4 cities to identify consumer content signalsIntegrate e-commerce data (Pinduoduo + Lazada) to analyze product sales trendsBuild a dashboard combining “city + product category + trend insights”1. Key Features of Emerging Market DataCompared to top-tier cities, consumer behavior, content preferences, and platform usage in lower-tier cities differ significantly:DimensionDescriptionE-commercePinduoduo, Douyin Group Buy, Xiaohongshu E-commerce, LazadaContent StyleUtility-driven, lifestyle-focused, agricultural and hardwareChannel PowerShort video commerce > Search-based shopping > Traditional brandingPrice SensitivityHigh; concentrated in low-price ranges (¥19.9, ¥39.9)These traits demand new approaches in product design, pricing strategy, and marketing pacing for brands targeting these regions.2. Extracting City-Level Content Trends Using Douyin APILuckData’s Douyin API allows filtering video hotlists by city, enabling rapid identification of local trending topics.✅ Example API Endpoint (using city parameter):GET https://luckdata.io/api/douyin-API/get_xv5p? city=610100& # Xi’an (tier-2 city) type=rise_heat& end_date=20241224& page_size=10& start_date=20241223 Using different city codes (e.g., Chongqing, Luoyang, Ganzhou, Yichang, Nanyang), users can retrieve localized hotlists to monitor regional content shifts.✅ Example Python Script:import requests def get_city_douyin_hot(city_code): url = "https://luckdata.io/api/douyin-API/get_xv5p" params = { "city": city_code, "type": "rise_heat", "start_date": "20241223", "end_date": "20241224", "page_size": 10 } res = requests.get(url, params=params) return res.json()["data"] data = get_city_douyin_hot("511700") # Suining for video in data: print(video["title"], video["like_count"], video["author_name"]) This API helps dynamically track hot content by city, offering early signals for marketing and product decisions.3. Analyzing Product Sales with Pinduoduo DataLuckData provides Pinduoduo sales data through sample fields or simulated inputs. These can be extended using crawlers or public rankings to model product trends.Sample data format:{ "title": "1.5L Automatic Thickened Glass Health Pot", "price": 39.9, "monthly_sales": 8523, "area_trend": { "Guilin, Guangxi": "High sales", "Zunyi, Guizhou": "Continuous growth" } } This structure allows for clustering of popular products by region and further validation of “content → conversion” effectiveness through Douyin signals.4. Building a Viral Product Detection Model for Lower-Tier MarketsTo effectively identify viral products in lower-tier markets, one can align content trends with product visibility, focusing on regional sales concentrations and price brackets.✅ Step 1: Match Content Popularity with Product ExposureVideo Title: “Village Aunt Makes Corn Crackers, Everyone Wants Some” → Matched Product: “Box of Corn Crackers, ¥19.9 Free Shipping” → Platform Performance: Over 10,000 sales on Pinduoduo, price < ¥20 ✅ Step 2: Define Key Market Heat IndicatorsMetricDescriptionCity Hotlist ScoreNumber of videos trending in a city / Total videos from that cityProduct Localization IndexPercentage of sales from tier-3 and below cities (>70% considered high)Price Tier DistributionHigher share of items < ¥50 indicates alignment with local preferencesLocal Engagement SignalsComments mentioning dialects, local place names, etc., suggest strong local spreadThis framework enables effective detection of high-potential local products and content combinations.5. Suggested Dashboard DesignBased on the above insights and data sources, the following dashboard structure is recommended for quick reference by field teams or product strategists:CityHot CategoryTrending VideosViral Product NameMonthly SalesPriceZunyiKitchen Goods21Multi-functional Electric Lunch Box9800¥35.0YichangAgricultural15Farmhouse Dried Chili (per kg)6200¥28.8XinxiangWomen’s Footwear19Summer Soft Indoor Slippers12400¥19.9This dashboard serves:Field operation teams planning local marketing strategiesMerchandisers leveraging rural e-commerce opportunitiesBrand owners evaluating market penetration in emerging regions✅ SummaryLuckData’s Douyin API supports city-level hotlist extraction, ideal for insight into lower-tier marketsPinduoduo product data can be simulated or collected to supplement e-commerce trend analysisA “content → product → region → conversion” model helps brands detect viral opportunities and deepen market penetrationArticles related to APIs :One-Week Build: How a Zero-Tech Team Can Quickly Launch an "E-commerce + Social Media" Data PlatformCross-Platform SKU Mapping and Unified Metric System: Building a Standardized View of Equivalent Products Across E-Commerce SitesPractical Guide to E-commerce Ad Creatives: Real-Time A/B Testing with API DataIntegrated Brand Sentiment Monitoring: Smart Consolidation and Early Warning System for Multi-Platform Keywords and Competitor ReviewsAPI + AI: Building an LLM-Powered System for Automated Product Copy and Short Video ScriptsEnd-to-End Automation for Short Video E-commerce Monitoring (Powered by Luckdata API)

One-Week Build: How a Zero-Tech Team Can Quickly Launch an "E-commerce + Social Media" Data Platform

High technical barriers, limited manpower, and fragmented data are common challenges when building a data platform. This article provides a “Minimum Viable Data Platform (MVP)” solution that even non-technical teams can implement to launch a real-time monitoring system across e-commerce and social media platforms within one week.Core ObjectivesLightweight data platform architecture designed for small teams without backend engineersIntegrate product and social data from Douyin/TikTok, Pinduoduo, and LazadaFast deployment: no backend or only basic use of Google Apps Script / Python1. MVP Architecture Design: Simplest Viable SystemThis architecture combines existing tools into a complete data platform:ModuleToolPurposeData FetchingLuckData APICollect product, video, and comment dataStorageGoogle Sheets / ExcelVisualization and data archivingData ProcessingApps Script / PythonScheduled pulling + lightweight ETLVisualizationData Studio / StreamlitBuild dashboards, filters, and alertsNotificationsFeishu / Slack / EmailAuto-push key data2. Step-by-Step: Fetching Data into SpreadsheetsBelow is a sample of collecting Douyin trending videos and Lazada product prices into Google Sheets.✅ Example: Fetch Douyin Trending Videos into Google Sheetsfunction fetchDouyinRankings() { var sheet = SpreadsheetApp.getActiveSpreadsheet().getSheetByName("Douyin"); var url = "https://luckdata.io/api/douyin-API/get_xv5p?city=110000&type=rise_heat&end_date=20241224&page_size=10&start_date=20241223"; var response = UrlFetchApp.fetch(url); var data = JSON.parse(response.getContentText()); var videos = data.data; sheet.clearContents(); sheet.appendRow(["Video Title", "Likes", "Author", "Publish Time"]); for (var i = 0; i < videos.length; i++) { sheet.appendRow([ videos[i].title, videos[i].like_count, videos[i].author_name, videos[i].create_time ]); } } Use Google Apps Script’s trigger function to schedule automatic daily updates.✅ Example: Fetch Lazada Product Data into Spreadsheetfunction fetchLazadaProducts() { var sheet = SpreadsheetApp.getActiveSpreadsheet().getSheetByName("Lazada"); var url = "https://luckdata.io/api/lazada-online-api/gvqvkzpb7xzb?page=1&site=vn&query=airfryer"; var response = UrlFetchApp.fetch(url); var data = JSON.parse(response.getContentText()); var products = data.data; sheet.clearContents(); sheet.appendRow(["Product Title", "Price", "Link"]); for (var i = 0; i < products.length; i++) { sheet.appendRow([ products[i].title, products[i].price, products[i].url ]); } } 3. Real-Time Dashboard Building (Optional Tools)Option 1: Google Data StudioData Source: Google SheetsVisualizations include:Product price trend chartsLike count trends for videosCross-platform comparisonsBenefits: No-code, easy collaboration, quick to launchOption 2: Rapid Prototype with Streamlit (Python)import streamlit as st import pandas as pd df = pd.read_csv("douyin_data.csv") st.title("Douyin Trending Dashboard") st.dataframe(df) Easily build a frontend for your data and host locally or online.4. Set Up Alerts: Push Notifications via Feishu/SlackFor example, price alerts that compare today's and yesterday’s data:function priceChangeAlert() { var sheet = SpreadsheetApp.getActiveSpreadsheet().getSheetByName("Lazada"); var rows = sheet.getDataRange().getValues(); for (var i = 1; i < rows.length; i++) { var priceToday = parseFloat(rows[i][1]); var priceYesterday = parseFloat(rows[i][2]); if (Math.abs(priceToday - priceYesterday) / priceYesterday > 0.2) { sendFeishu("Price Alert: " + rows[i][0] + " has changed by more than 20%"); } } } You can also use Slack or email APIs to notify team members of anomalies.5. Suggested Project Folder Structure/project/ ├── douyin_fetch.gs # Fetch trending videos ├── lazada_fetch.gs # Fetch product search results ├── alert_logic.gs # Price alert logic ├── dashboard.gsheet # Visualization spreadsheet └── README.md Clear modular design makes future maintenance and expansion easier.✅ One-Week Implementation TimelineDayTaskDay 1Set up API flow and register on LuckDataDay 2Connect Google Sheets and Apps ScriptDay 3Schedule automated data pullingDay 4Build basic dashboards in Data StudioDay 5Set up Feishu alertsDay 6Standardize fields and data formattingDay 7Upgrade dashboard with Streamlit or BI toolsConclusionThis architecture requires no servers or databases, and no full-time engineers. With just spreadsheets and lightweight scripts, any team can begin building their own “e-commerce + social media” data platform. Perfect for startups, product selection teams, and marketing departments aiming for data-driven decisions.Articles related to APIs :Cross-Platform SKU Mapping and Unified Metric System: Building a Standardized View of Equivalent Products Across E-Commerce SitesPractical Guide to E-commerce Ad Creatives: Real-Time A/B Testing with API DataIntegrated Brand Sentiment Monitoring: Smart Consolidation and Early Warning System for Multi-Platform Keywords and Competitor ReviewsAPI + AI: Building an LLM-Powered System for Automated Product Copy and Short Video ScriptsEnd-to-End Automation for Short Video E-commerce Monitoring (Powered by Luckdata API)In-Depth Analysis of Pinduoduo Group Buying Data: How to Use APIs to Discover High-Converting Low-Price Bestsellers

Cross-Platform SKU Mapping and Unified Metric System: Building a Standardized View of Equivalent Products Across E-Commerce Sites

Core ObjectivesBuild a cross-platform product database to associate identical products across multiple e-commerce platformsStandardize key metrics such as price, inventory, and sales volume into a unified KPI poolDevelop SKU-level monitoring dashboards with real-time alerting (e.g., sudden price increases or stockouts)Step 1: Collect Basic Product Data Across PlatformsUsing Lazada, Pinduoduo, and Amazon as examples, we fetch product details via the LuckData API to prepare for matching and data consolidation.Lazada Product Data Retrievalimport requests def get_lazada_product_detail(site, item_id): url = "https://luckdata.io/api/lazada-online-api/x3fmgkg9arn3" params = { "site": site, # Supports "vn", "th", "ph" "itemId": item_id } res = requests.get(url, params=params) return res.json() lazada_data = get_lazada_product_detail("vn", "2396338609") print(lazada_data["data"]["title"], lazada_data["data"]["price"]) Pinduoduo Product Data (Simulated)Data can be obtained via custom web scrapers or LuckData’s Pinduoduo interface.pdd_data = { "title": "Bear Electric Lunch Box, Double Layer", "price": 129.0, "sku_id": "pdd_948571", "image": "https://cdn.example.com/pdd.jpg" } Amazon Product Dataamazon_data = { "title": "Bear Electric Lunch Box, 2-Tier Food Steamer", "price": 34.99, "asin": "B09XY1234L", "image": "https://cdn.example.com/amazon.jpg" } Core Algorithm: Matching and Aggregating Identical SKUs✅ Method 1: Title Similarity MatchingUse FuzzyWuzzy or RapidFuzz to determine if product titles indicate the same item.from rapidfuzz import fuzz def is_same_product(title_a, title_b, threshold=80): score = fuzz.token_sort_ratio(title_a.lower(), title_b.lower()) return score > threshold matched = is_same_product(lazada_data["data"]["title"], amazon_data["title"]) print("Same product:", matched) Weighted scoring is recommended:Title similarity (70%)Image hash similarity (15%)Brand/model similarity (15%)✅ Method 2: Standardized SKU SchemaCreate a unified SKU ID for each logically identical product and map corresponding entries from each platform:{ "sku_id": "SKU_001", "standard_title": "Bear Electric Lunch Box 2-Tier", "platforms": { "lazada_vn": {"item_id": "2396338609", "price": 135000, "url": "..."}, "pinduoduo": {"sku_id": "pdd_948571", "price": 129.0}, "amazon": {"asin": "B09XY1234L", "price": 34.99} } } This serves as the data model for metrics aggregation and dashboard construction.Unifying Metrics: Price, Inventory, and SalesBuild a Standardized Daily Metric TableSKU IDPlatformProduct TitlePriceInventorySalesDateSKU_001Lazada_vnBear Electric Lunch Box135000543202025-05-21SKU_001PinduoduoBear Electric Lunch Box (CN)129.0684802025-05-21SKU_001AmazonBear Electric Lunch Box (EN)34.99238902025-05-21Sample Dashboard Display OptionsTools you can use:Streamlit + Pandas: Lightweight web-based dashboardsGoogle Data Studio: Integrate with Sheets for fast deploymentPowerBI / Tableau: Enterprise-grade visual analyticsAlerting and Smart Monitoring✅ Example: Price Fluctuation AlertMonitor for abnormal price changes beyond a defined threshold (e.g., 15%) and trigger an alert.def price_alert(sku_id, price_today, price_yesterday): delta = abs(price_today - price_yesterday) / price_yesterday if delta > 0.15: return f"[Alert] SKU {sku_id} price fluctuated over 15%" Use scheduled tasks (e.g., Airflow / CRON) to automate monitoring and push alerts to channels like Slack or Lark.Future Roadmap: Enhancing Matching CapabilitiesStageFocus AreaV1Title similarity + manual SKU mappingV2Image hash comparison + rule-based parsingV3AI model for "image + title" product matching and clusteringThe evolution moves from simple title comparison to multimodal AI-based identification of identical products.✅ SummaryUse APIs to quickly build multi-platform product datasets for Lazada, Pinduoduo, and AmazonApply similarity metrics to construct a unified SKU repositoryConsolidate metrics like price, inventory, and sales by SKUEnable price monitoring, competitor comparison, and real-time alertsLay the groundwork for intelligent, cross-platform product operations and analysisArticles related to APIs :Practical Guide to E-commerce Ad Creatives: Real-Time A/B Testing with API DataIntegrated Brand Sentiment Monitoring: Smart Consolidation and Early Warning System for Multi-Platform Keywords and Competitor ReviewsAPI + AI: Building an LLM-Powered System for Automated Product Copy and Short Video ScriptsEnd-to-End Automation for Short Video E-commerce Monitoring (Powered by Luckdata API)In-Depth Analysis of Pinduoduo Group Buying Data: How to Use APIs to Discover High-Converting Low-Price BestsellersShein, Temu & Lazada: Practical Guide to Cross-Border Fast Fashion Sourcing and Compliance