Ecommerce ops · Production

Algolia Search helps dm-drogerie markt improve conversions and reduce developer bottlenecks

The problem

dm-drogerie markt's search was embedded in a monolithic e-commerce platform with limited extensibility, requiring developer involvement for synonym maintenance and other changes, creating bottlenecks for business users who needed to manage and optimize search independently.

Workflow diagram · grounded in source

Customer search query

trigger

“how users can interact with our offers and find products they are looking for plays a key role”

Dynamic query suggestions

ai_action

“suggestions dynamically calculated based on customer search, with predefined filters including dropdowns, price and, for some products, color”

Brand and category recognition

ai_action

“Algolia automatically recognizes relevant brands or categories in search terms and boosts them in results accordingly”

Business rule routing

routing

“providing alternative products if a customer searches for a particular brand that's not carried or out of stock, or products based on article numbers, or categories of products being replaced with a more general term in search queries. A…”

Search results delivered

output

“they provide merchandising rules, business ranking, and the configuration of facets displayed in the online shop”

A/B testing and analytics

feedback_loop

“We've tied Algolia to conduct A/B-Testing on various custom rankings”

Reported outcome

dm achieved a 2% improvement in conversion rates and a 1.17% improvement in click rates after deploying Algolia, expanded the solution across all mobile apps and online shops by 2022, and reduced developer bottlenecks so business users can define and maintain rules autonomously.

Reported metrics

Conversion rate improvement2%

Click rate improvement1.17%

maintenance costs vs ElasticDecreased maintenance costs compared to Elastic

Reported stack

AlgoliaAlgolia SuggestsAlgolia AnalyticsCMS

Source

https://www.algolia.com/customers/dm-drogerie-markt

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

dm achieved a 2% improvement in conversion rates and a 1.17% improvement in click rates after deploying Algolia, expanded the solution across all mobile apps and online shops by 2022, and reduced developer bottlenecks…

What tools did this team use?

Algolia, Algolia Suggests, Algolia Analytics, CMS.

What results were reported?

Conversion rate improvement: 2%; Click rate improvement: 1.17%; maintenance costs vs Elastic: Decreased maintenance costs compared to Elastic (source-reported, not independently verified).

How is this ecommerce ops AI workflow structured?

Customer search query → Dynamic query suggestions → Brand and category recognition → Business rule routing → Search results delivered → A/B testing and analytics.