Dynamic Yield
Personalization platform for product recommendations, targeted content and tests on large retail sites.
Search and personalization tools decide which products a shopper sees: what comes back for a search, which items appear as recommendations, and how category pages are ordered. On a store with more than a few dozen products, these choices shape sales as much as the product pages do.
On-site search is the most direct of them. Shoppers who search usually know what they want, so a search that handles typos, synonyms and filters, and returns results as they type, catches sales that a basic search box misses. The tools here also let merchandisers pin, boost or hide products for specific queries.
Recommendations cover the familiar slots: related products, frequently bought together, recently viewed and cart upsells. The simpler apps use rules and purchase history. The larger platforms build a profile of each visitor from browsing and orders, change content and ranking for each segment, and test variations against each other.
All of this depends on product data. Clean titles, consistent attributes such as size, color and material, and accurate stock levels give the tools something to work with. Poor data produces odd matches, and no ranking model fixes a catalog where half the products lack a color.
What a featured listing costs ยท from $99 a month
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Start with the slots that are cheapest to try. A recommendations block on product pages and a cart upsell can be added in an afternoon with most apps, and their effect on order value is easy to measure. Full personalization across the site, with different content per segment, takes more setup, more traffic and someone to look after it.
Watch the merchandising rules over time. Boosts and pins set for a sale or a launch tend to stay in place long after they stop making sense, and they push other products down. A quarterly review of active rules keeps search results and recommendations close to what shoppers actually want.
Measure the effect with a holdout. Most personalization tools can keep a small share of visitors on the plain experience, which shows how much the recommendations and tailored content actually add. Without that comparison it is easy to credit the tool with sales that would have happened anyway, especially during busy seasons when every number rises.
Review the search terms that return no results every month. They show missing products, missing synonyms and the words customers use that your catalog doesn't.
When the catalog is large enough that shoppers struggle to find things by browsing, or when your search box often returns nothing for reasonable queries. Small catalogs can usually manage with the platform's built-in search.
Often, especially cart upsells and frequently bought together items, because they raise order value. Test them against the page without recommendations so you know what they add.
Yes. They track browsing and purchases to tailor what each visitor sees. Mention this in your privacy policy and respect cookie consent where your customers live.
A product feed with titles, descriptions, categories, attributes, prices, stock and images. Most tools sync it from the store platform automatically, but gaps in your attributes show up as weak filters.