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Attraqt Search and Recommendations

Develop by attraqt.com
Free App

AI-powered product discovery and optimization for omnichannel retail success.

Product recommendations
Personalization engine
A/b testing
Merchandising tools
Ai-driven search

About Attraqt Search and Recommendations

Launched May 24, 2021

Categories

Built by attraqt.com

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Description

Attraqt is a leading product discovery platform, offering AI-driven search, merchandising, recommendations, and personalisation.

Attraqt is the growth engine for trailblazers in omnichannel product discovery. Flagship customers include PrettlyLittleThing, TheKooples, Cdiscount, LaPerla, and OKA.

Our app provides:

Proven results:

Built for Peak with over 127 billion queries in 2020, 99.9+% uptime, and regional support in UK, Europe, Australia, New Zealand

Product Discovery is in our DNA

It forms the core of everything we do and how we support you! It's not just the platform and tools we provide, but the customer success strategies that we work hand-in-hand with you on to find joint success.

API-Driven & User Friendly

Built on a headless architecture, we make it easy to integrate and manage using tools and dashboards designed for trading and merchandising teams.

AI-Powered

AI doesn't have to be a 'black box'. We believe in transparency and giving your trading teams visibility into the 'why' so they can make data-informed decisions.

A/B Testable

Test and analyse the performance of your personalisation and merchandising strategies with our simple-to-use A/B testing tool to optimise conversion and engagement.

Pros

  • Proven reliability with over 127 billion queries handled in 2020 and 99.9+% uptime.
  • Strong regional support in the UK, Europe, Australia, and New Zealand.
  • Focus on product discovery as a core competency shared with flagship customers.
  • API-driven architecture that simplifies integration and management.
  • User-friendly tools and dashboards designed for trading and merchandising teams.
  • Transparency in AI-powered solutions, enabling informed decisions by trading teams.
  • Built-in A/B testing tool for optimizing personalization and merchandising strategies.

Cons

  • No specific user reviews or ratings provided to assess real-world experiences.
  • The efficacy of AI recommendations largely depends on the quality of data input.
  • May require a learning curve for teams unfamiliar with headless architectures.

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