FT: Frequently Bought Together
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Show add ons product recommendations to upsell and cross sell with an AI-powered personalized engine
Fether is a personalization platform that leverages cutting-edge AI/ML technology and flexible software to create tailored experiences for your customers. With our Personalization Engine, you can display relevant recommendations on storefront, enable customers to add related products to their cart with one click, boosting AOV & revenue. Our AI algorithm is constantly learning from millions of products and orders, your store's historical and real-time data, and refined to optimize conversion rate
- Blend smart AI-driven product recommendations & human handpicks to create bundle
- 2 elegant styles (incl. an Amazon-inspired option), on the Product & Cart pages
- A countdown timer triggers urgency, boosting sales and increasing conversions
- 100% compatible with Shopify's API for automatic discount codes and combinations
- Works seamlessly on mobile and desktop devices. Set up easy, no coding required
- Høydepunkter
- Populært blant bedrifter i USA
- Bruk direkte i Shopify-administrator
- Fungerer med de nyeste temaene
Pakketyper
Priser du kan angi
Lansert
21. april 2023
Språk
Engelsk
Denne appen er ikke oversatt til Norsk (bokmål)
Kategorier
Fungerer med
Shopify FlowOmtaler (334)
I recently integrated the Frequently Bought Together (FBT) app into my online store, and the results have been nothing short of impressive. This tool has not only increased my average order value but also significantly enhanced the shopping experience for my customers.
It would be amazing if you had a Loyalty Program so it should get more amazing for your store I started this application today and applied for a loyalty program let see what happens after getting a loyalty program, I read them and I was amazed.
Best app for adding frequently bought together section with custamized price and discount
Cool idea if I could use it. it's not working very well for me
So far it's been really easy to use and not overwhelming in the slightest which is fantastic. I only put four stars because I've only just started using it and have not much experience using it.
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