FAQ

Questions? Answered.

Still have questions?Talk to us, or go live on Shopify in 5 minutes.
Contact us
01 Why Kainic
What does Kainic do?

Kainic is an AI personalization engine for online stores. It learns what each shopper is browsing and buying, then shows them the products they're most likely to want, in real time.

Why not just use my platform's built-in recommendations?

Built-in widgets usually show the same "related products" to everyone. Kainic personalizes for each shopper and automatically picks the best model for your catalog, so recommendations get sharper as your data grows.

What results can I expect?

One of our fashion customers saw these results after enabling just two widgets:

+63.4%Add-to-cart
+47.9%Checkout
$26back for every $1

Results vary by store. You'll see your own numbers from day one.

How long does setup take?

About 5 minutes on Shopify, with no code. Install the app, let it sync your catalog, and switch on the widgets you want. We also support Zid, Web, Android, iOS and API.

Is my customers' data safe?

Yes. Kainic does not collect or store private customer data. Personalization runs on anonymized behavioral signals, and we're GDPR compliant.

02 Ads vs Recommendations
Aren't recommendations just ads?

No. An ad promotes a product someone paid to push. A recommendation suggests a product from your own catalog because it fits what this shopper is looking for.

AdsKainic recommendations
GoalBring new traffic to your siteTurn existing visitors into buyers
What's shownWhatever the advertiser pays forWhat this shopper is most likely to buy
CostPay per click or view, whether they buy or notPay for usage; the value shows up in your sales
WhereOff your site (social, search)On your site: product page, cart, checkout
Do I still need ads?

Ads bring people in. Recommendations help them find more to buy once they're there. Together, Kainic makes every visitor you paid to acquire worth more.

03 Performance KPIs
Which KPIs do you track?
  • Add-to-cart & checkout rate: are more shoppers moving toward a purchase?
  • Conversion rate (CVR): share of sessions that end in an order.
  • Average order value (AOV): are shoppers buying more per order?
  • Revenue per visitor (RPV): the best single measure of overall impact.
  • Revenue from recommendations: sales attributed to each widget and placement.
  • ROI: revenue gained versus what you pay Kainic.
How do you know the lift comes from Kainic?

We track every widget's full path (impression, click, add-to-cart, purchase) and attribute revenue to the widget that drove it. For a clean side-by-side comparison, we run an A/B test.

Where do I see the numbers?

In your real-time Kainic dashboard. We also send you a monthly performance report with recommended next steps.

04 Pricing
What's the pricing model?

Pay as you go. You only pay for what you use, based on the number of recommendation requests Kainic serves on your store.

Is there an upfront fee or contract?

No upfront cost and no binding contract. Cancel anytime.

How much does it cost?

Kainic starts from as low as $50 per month and scales with your usage.

Is there a free trial?

Yes. You get a 1-month free trial, ending with a performance report and recommended next steps.

How do I keep track of my bill?

Your dashboard shows your request volume in real time, so there are no surprises.

05 A/B Testing
What is an A/B test?

We split your visitors into groups. One group sees the Kainic experience; the other sees your current store (or a different setup). Then we compare the results.

How does it work in Kainic?
  1. Choose what to test: a widget, a placement, or a recommendation model.
  2. Set the traffic split (e.g. 50/50).
  3. Kainic tracks RPV, conversion rate and AOV for each group.
  4. Our significance engine tells you when a result is real, not luck.
  5. Promote the winner with one click.
Why is it useful?
  • Proof, not guesswork: see exactly what Kainic adds versus your store without it.
  • Lower risk: test on part of your traffic before rolling out to everyone.
  • Keeps improving: test new placements and models over time to keep growing revenue.

No matching questions. Try another word, or ask us directly.