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Raptor

From the same storefront to a suitable suggestion.

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Three situations we encounter every day.

Why choose a Raptor partner?

  • Everyone sees the same storefront

    Every visitor sees the same homepage and the same featured products, regardless of what they previously viewed or purchased. In a physical store, no one would do that; online, it’s the standard.

  • Your recommendations are based on manual rules

    The recommendations on your product page were originally set manually, and your product lineup has changed since then. Rules become outdated; behavior doesn’t. An algorithm that learns from actual click behavior remains accurate.

  • You’re not getting much out of customers who’ve already bought something

    A customer buys one product and then never hears from you again, even though you know exactly what would be a logical next step. That’s revenue left on the table from people who’ve already chosen you.

Raptor as the engine behind your personalization

The larger your product range, the smaller the chance that a visitor will find what suits them. Filters help those who know what they’re looking for; the rest need a suggestion.

Raptor is the engine that does just that. It learns from what visitors actually view, add to their carts, and buy, and uses that information to show them what’s a good fit—on your product page, in your search results, and in your emails.

You control the limits. You can exclude items that are sold out or below your margin, so a model doesn’t happily recommend your clearance stock.

What We Do with Raptor

We start by asking whether it adds value for you. For that, you need enough visitors and enough products to identify patterns. With a small product range, good manual combinations are just as effective—and much cheaper.

If it is the right choice, we link it to your product data and behavioral data, and determine what is displayed for each section of your site. The recommendations on a product page serve a different purpose than those in your shopping cart.

Then we’ll test it against the scenario without recommendations. A block that gets clicks isn’t the same as a block that drives revenue, and we want to understand that difference.

Three things you’ll notice in the partnership.

Why choose Redkiwi as your Raptor partner?

  • You’ll see for yourself what it adds

    You’ll see, for each section of your site, how the recommendations perform and what value they add. Every month, we’ll review this together, and you’ll decide what limits to set. You remain in control of the commercial strategy; we’ll ensure the data supports it.

  • Independent advice

    If traffic is too low or your product range is too small, we won’t recommend it, because the return won’t cover the cost. That’s what ownership means to us.

  • E-commerce and personalization under one roof

    We build the online store and manage the product data behind it, so every recommendation aligns with your inventory and your profit margin. You’ll work with a dedicated specialist who knows your product range.

Frequently Asked Questions About Personalization

01/ What does a recommendation engine base its recommendations on?
It’s based on what visitors actually do: what they view, add to their cart, and purchase. This is different from manually set rules, which become outdated as soon as your product selection changes.
02/ How much traffic do I need for personalization?
Enough visitors and enough products to identify patterns. For a small online store with fifty items, well-chosen manual combinations are just as effective and much cheaper. We’ll go over the calculations with you in advance.
03/ Can I decide for myself what isn’t recommended?
Yes, and that’s recommended. You can exclude items that are sold out, items priced below your margin, or items you don’t want to display for other reasons. A model without those limits will happily advertise your clearance items.
04/ How do I know if recommendations actually drive revenue?
By testing it against a scenario without recommendations. A block that gets clicks isn’t the same as a block that drives revenue, because some of those customers would have found the product anyway.