Review analysis for retail: Shopper insights from reviews and social media
By Arber Sejdiji3 min read
Sales, basket and loyalty data tell you a lot about your own shoppers: what they buy, what they buy together and how often they come back. They show less of what shoppers looked for and did not find, what annoys them about a product, or what people who shop elsewhere want. Much of that sits in public sources: product reviews, search queries, TikTok videos and Instagram posts. For merchants and buyers it has always been hard to use, because there is so much of it, spread across many channels.
Why ratings and reviews are the most underused source
Reviews are the most honest product feedback a retailer can get, and they are public, for your products and for your competitors'. Read at scale, they show:
- Unmet needs: "wish it came in a larger size," "would buy a vegan version."
- Quality problems: recurring complaints that explain returns and slow sellers.
- Reasons to switch: why shoppers prefer a competitor's product, or your private label (store brand) over the national brand.
- Words shoppers use: the attributes that matter to them, which often differ from the ones in your product data.
No merchandising team can read thousands of reviews per category every month. An AI agent can, also on competitor websites, and it can link each finding to the products in your assortment.
Search and social: demand before it reaches the shelf
Search trends show demand building before it reaches competitor stores. Social media shows which products, looks and ingredients are picking up and with whom. A shopper insights agent reads Google Trends, Search and Shopping, YouTube, TikTok, Pinterest, Instagram, marketplaces, press and web research, and chooses the sources that matter for each category.
Trend or viral spike?
Judging signals is harder than finding them. A viral spike peaks once and fades. A trend keeps growing across several channels and markets. The agent follows each signal over time across search, social and marketplaces, and how long it watches before calling something a trend is set per company, vertical and season. That keeps your buyers from listing products for a hype that is over before the delivery arrives.
From insight to decision
For a category team, an insight is useful once it leads to an assortment decision. The agent therefore matches every trend and every unmet need against your current products. If shoppers ask for something you don't carry, it becomes a recommendation for the Assortment Agent. If reviews show a price-value problem, it goes to pricing. Your merchants see one list of actions instead of another trend report.
Read more: Shopper Insights Agent · OTTO puts Zenline AI agents to work on the assortment
FAQ
Which data sources does AI use for shopper insights? Search trends, social media, reviews, marketplaces, retailer sites, competitor assortments, price history, press and web research, plus the Zenline Consumer Panel.
How do you tell a consumer trend from a viral spike? A trend keeps growing across several channels and markets; a viral spike peaks once and fades. The agent follows each signal over time.
