AI Recommendations by Aqurate

Develop by Shopify

Free plan available

AI-driven cross-sell, upsell and other product recommendations

Ai-driven recommendations

Email recommendations

Website integration

Personalized shopping experience

Cross-sell products

App integration

Upsell products

High performance

About AI Recommendations by Aqurate

Launched Apr 24, 2024

Built by Shopify

Address

Spaces, 9 Greyfriars Road, Reading, ENG, RG11NU, GB

Website Support Portal Privacy policy Tutorial FAQ Document

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Description

Improve your conversions, AOV, and customer retention using AI-driven product recommendations

Aqurate Personalize helps eCommerce shops improve the conversion rate, the AOV, and customer retention by offering their visitors a personalized online shopping experience. Using AI-driven technology, Aqurate delivers highly targeted product recommendations to each customer, based on their previous interactions with the shop. Cross-sell, up-sell and similar product recommendations can be displayed on the website (product detail page, cart), app, or sent by email.

Personalize the user journey based on their preferences
Increases your conversion rate and AOV
Fully automated recommendations that take into account stock and new products
Native design with no additional CSS to keep up to date
Great performance without slowing down your website and dedicated support

Pros

Improves conversion rate and average order value (AOV) by offering personalized shopping experience.
Uses AI-driven technology to deliver highly targeted product recommendations based on customers' previous interactions.
Provides cross-sell, upsell, and similar product recommendations on various platforms including website, app, and email.
Automates recommendations by considering stock availability and new product additions.
Maintains native design without requiring additional CSS updates.
Offers great performance without slowing down the website.
Dedicated support for users of the app.

Cons

Reliance on AI might not always capture unique customer preferences accurately.
Effectiveness is highly dependent on the quality of customer interaction data available.
Recommendations might not align with the shop's current promotional strategy or brand positioning.
Integration with certain platforms could present challenges if not fully compatible.