Product Research & Trends
The most expensive mistake in e-commerce isn't bad marketing. It's picking the wrong product. You can write the perfect listing, run flawless ads, and nail your pricing — but if nobody wants what you're selling, none of it matters.
Today you'll learn how to use AI to find products people are already searching for, spot trends before they peak, and validate ideas before you invest a single pound.
Why most product research fails
Most sellers do product research backwards. They find something they like, source it, list it, and then discover there's no demand. Or worse — there's demand, but 4,000 other sellers got there first.
The old way:
- Browse AliExpress for hours looking for "cool" products
- Check Amazon's bestseller list and copy what's already there
- Follow a gut feeling and order 500 units
- Discover 6 weeks later that nobody wants it
The AI way:
- Identify trending search terms and rising demand signals
- Analyse market gaps where demand exists but supply is thin
- Validate pricing, competition, and margin before committing
- Test with small orders backed by data, not hope
The difference isn't just speed — it's accuracy. AI can process thousands of data points from bestseller lists, search trends, review patterns, and social media in the time it takes you to scroll through one page of results.
Using AI to spot trending products
Perplexity and ChatGPT are exceptional at synthesising trend data from across the internet. Here's a framework for finding products with rising demand:
Step 1: Identify broad trend signals. Ask AI to summarise what's trending in your niche across social media, Google Trends, and marketplace bestseller lists.
Step 2: Dig into search volume patterns. Ask AI to help you interpret Google Trends data — you're looking for products with a rising trajectory, not ones that have already peaked.
Step 3: Analyse seasonal opportunities. Every product category has seasonal peaks. AI can map out 12 months of seasonal demand so you're sourcing in March for a June spike, not scrambling in June when it's too late.
Step 4: Find the gap. The gold is in products where search volume is rising but the number of quality listings is still low. That's your window.
Analysing bestseller lists with AI
Bestseller lists aren't just for finding what's popular — they're data goldmines when you know what to look for. Instead of copying the #1 product, you should be asking:
What patterns appear across the top 20? If 15 out of 20 bestselling yoga mats are 6mm thick and come in neutral colours, that tells you what the market wants. Don't fight it.
Where are the review complaints? The negative reviews on bestsellers are literally customers telling you what product to make next. "Great mat but it slides on hardwood floors" — that's your product brief.
What's missing from the top results? If every bestselling phone stand is black plastic, there's an opportunity for bamboo, marble-look, or colour options.
Ask AI to analyse a bestseller list and it will find patterns a human would miss after hours of scrolling.
Validating before you invest
Finding a trending product is only half the battle. Before you order anything, run it through this AI-powered validation checklist:
Demand validation — Ask AI to estimate monthly search volume and whether the trend is growing, stable, or declining. A product with 10,000 monthly searches growing at 20% is far better than one with 50,000 searches that peaked 6 months ago.
Competition validation — Have AI analyse the top 10 listings for your target keyword. How many reviews do they have? What's the price range? Are the photos professional? If the top 10 all have 5,000+ reviews and professional photography, you're entering a mature market. If they have 50-200 reviews and mediocre images, there's room.
Margin validation — Feed AI your estimated sourcing cost, shipping cost, marketplace fees, and advertising budget. If you can't hit at least a 30% profit margin after all costs, the product isn't worth pursuing no matter how trendy it is.
Differentiation validation — Ask AI: "Given these top 10 competitors, what could a new entrant do differently to stand out?" If AI can't find an angle, neither will your customers.
Building your product research system
Don't treat product research as a one-off task. The best e-commerce sellers run this process monthly:
Weekly (15 minutes): Ask AI to check Google Trends for your top 5 product categories. Flag anything that's spiking or declining.
Monthly (1 hour): Run the full analysis — bestseller trends, seasonal forecasting, competitor gap analysis. Have AI generate a shortlist of 3-5 opportunities.
Quarterly (2 hours): Deep-dive validation on your top picks. Margin analysis, differentiation strategy, sourcing research. Decide what to test.
This rhythm means you're never caught off-guard by a trend, never late to a seasonal opportunity, and always have a pipeline of validated product ideas ready to go.