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Search and discovery experiences are vital aspects of any ecommerce solution. With Algolia, you can build the best possible user experiences for the ecommerce use case by leveraging these solutions:

Ecommerce implementation playbook

Through working with thousands of different companies and analyzing their success, we at Algolia learned how companies evolve their search and discovery strategies to drive business results and user loyalty.

We identified three stages in the maturation journey of search and discovery experiences: the Search and Discovery Maturity Model.

Stage 1: Foundational—build a basic search and browse experience

In stage 1, you implement the core technologies of the search and discovery experience for a relevant and fast search. The implementation is engineering-driven and focuses on a rapid launch.

Solution Milestones
Data ingestion

Create data pipeline

Search

Create responsive and accessible autocomplete experiences

Create responsive and accessible product listing pages

Browse

Create responsive and accessible category pages

Create responsive content carousels on landing pages

Relevance optimization

Configure relevance to get the best results in all situations

Filtering and navigation

Add rich filtering and navigation options to front end

Stage 2: Programmatic—use AI and analytics to optimize relevance and for merchandising

In stage 2, you use analytics to integrate business relevance and advanced intent detection programmatically. Stage 2 involves both engineers and business users to focus on an informed maturation of the search and discovery experience.

Stage 3: Smart—use AI for recommendations and merchandising

In stage 3, you unify and converge advanced technologies, such as AI and data science. At this stage, implementations focus innovation-led by business and engineering teams under Executive sponsorship.

Solution Milestones
Relevance optimization

Add and test AI re-ranking

Recommendations

Show recommendations

  • Machine learning-based recommendations
  • Implement recommendations on product detail and checkout pages
Merchandising

Search and category merchandising

  • Inject brand content
  • Inject content in promotional slots
  • Inject array of promotional content between results

AI-based merchandising

  • Inject re-ranked content in promotional slots
Personalization

Personalized recommendations

  • Personalized search suggestions
  • Personalized recommendations on the empty query state
  • Personalized recommendations on product listing pages
  • Personalized browse pages
  • Personalized content carousels
  • Personalized dynamic landing pages
  • Personalized recommendations with notifications
  • A/B test personalization strategies on search and browse pages

Personalized merchandising

  • Inject personalized content in promotional slots

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