L’outil E-commerce que tu dois absolument avoir

Summary

The video is a practical walkthrough of TrendTrack, a tool for discovering e-commerce stores, estimating their growth, and researching competitors’ products, ads, landing pages, and Shopify apps. The presenter’s main principle is to make product decisions using market data rather than intuition, while treating third-party estimates as directional rather than definitive.

Research workflow and playbooks

• Screen for stores that appear to be gaining traction. TrendTrack’s filters let users combine estimated traffic, traffic growth, active Facebook ads, product count, company origin, visitor geography, and Shopify apps.
• Inspect the full product and offer history. Compare a competitor’s current best-performing product pages with earlier versions. The presenter recommends studying failed offers as well as apparent winners to understand what changed.
• Check all competitor ad accounts and pages. A store may advertise through multiple Facebook pages. In the example, TrendTrack identified three pages. Looking at just one showed 52 active ads, while the other pages had 57 and 54. Relying on a single page can miss a substantial share of the advertising activity.
• Analyze creatives and destinations. Review ad formats, landing pages, messaging, audience angles, ad age, and duplication patterns. Use these as clues for testing—not as proof of profitability.
• Translate research into your own tests. If video dominates a competitor’s ads, prioritize video creatives in your initial tests. If ads send substantial traffic to the homepage, examine whether the homepage functions as a product page or offers a deliberate alternative to a product-page destination.
• Broaden competitor research beyond direct rivals. Search by keyword to find stores with relevant products or messaging, even if they sell a different item. Their ads and copy may reveal useful customer language, marketing angles, and audiences.
• Save and revisit searches. The presenter suggests checking regularly for newly rising stores—roughly early in the month after monthly data updates—because speed can matter when entering a product trend.

Case study: nail-serum store

• The example store reportedly rose from roughly 3,800 estimated visits to 173,000 in a month, an increase of more than 4,350%.
• The presenter says the store began testing products around August 30, 2024, but its major traffic increase appeared about six months later. This illustrates how long it may take a product to find a successful offer; it is not a general launch timeline.
• The store had ads across three Facebook pages, reinforcing the need to investigate all pages associated with a competitor.
• On one page, the ad mix was reportedly about 98% video. The presenter takes this as a reason to test video-first creatives, while advising viewers to check the other pages too.
• About 50% of the ads reportedly led to the homepage. Other destinations included educational or persona-specific landing pages. The presenter recommends examining what each destination is designed to achieve before copying the setup.
• A product page was associated with 39 ads. Repeatedly duplicated or relaunched creatives were treated as potential indicators of stronger ads, though the presenter notes that ad structure affects how useful those clues are.
• One pattern showed all 14 of 14 ads still active on a given day. The presenter interprets this as consistent with campaign structures such as CBO or Advantage+, where the platform algorithm may allocate spend rather than the advertiser manually switching off each ad. In that situation, “still active” alone does not identify the best-performing creative.

Suggested TrendTrack filters

The presenter offers these as starting points rather than fixed rules:

• Rising-store search: estimated traffic of 40,000–300,000, at least 30 active ads, no more than 150 products, and around 200% month-over-month traffic growth. This reportedly returned 103 stores in the example.
• A looser growth threshold of 50% reportedly returned 460 stores. The presenter argues that a 50% increase can still be meaningful for a store already receiving substantial traffic.
• Alternative store search: traffic of 30,000–300,000, at least 30 active ads, and up to 300 products.
• Use company-origin and visitor-country filters to explore particular markets. The presenter calls out the US, UK, Hong Kong, Thailand, Indonesia, and the UAE, among others. These are discovery tactics—not reliable ways to establish who owns a business or where its operators live.
• Search by keyword, then add traffic filters. For the “nails” example, a keyword search reportedly found thousands of relevant stores, with a narrower traffic filter returning 218 results.

Metrics, estimates, and caveats

The presenter says he has generated €5 million in revenue across his e-commerce stores and attributes his growth approach to relying heavily on data.

He cautions that TrendTrack traffic figures may be underreported. Based on his experience, he suggests multiplying estimates by roughly 3, sometimes 4. This is a personal rule of thumb, not a validated correction factor.

He also uses roughly €1 of revenue per visitor as a shortcut. Applying both assumptions to the example’s 173,000 estimated visits produces an approximate €519,000 revenue estimate for the month. This is highly speculative: traffic and revenue estimates can be inaccurate, and actual results depend on conversion rate, order value, geography, and other factors.

Other caveats include:

• Geographic traffic breakdowns may reflect travel, team members, or tracking activity rather than the store’s true customer mix. Treat small country shares cautiously.
• Active-ad counts, ad duplication, Shopify app usage, and product-page traffic are research signals, not direct evidence of sales, profitability, or customer acquisition costs.

Tools, plans, and operational notes

• The free TrendTrack Chrome extension can show basic store information, estimated traffic, geographic distribution, and products. Paid access adds more detailed analysis.
• The presenter recommends Dropship.io as a free way to check the Meta Ads Library by domain and identify multiple Facebook pages that TrendTrack’s initial ad-library link may not reveal.
• He prefers the Professional TrendTrack plan for many e-commerce operators, citing access for two users and a limit of 10 tracked stores, which can be managed by removing and replacing stores. He considers the Business plan more suited to agencies or teams needing more tracking capacity.
• The transcript’s plan pricing is garbled and internally inconsistent, so the quoted amounts should not be treated as reliable. The presenter mentions a 10% discount code, ZEZINHO10.

Presenter and sources

The presenter identifies himself in the subtitles as “Zigno,” likely Zezinho, from the Zezinho Ecom channel. Tools and sources discussed include TrendTrack, Dropship.io, the Meta/Facebook Ads Library, Shopify store and app data, and the presenter’s own e-commerce experience.