Site search & AI recommendations that convert
If users don't find what they're looking for, they leave. An intelligent search decides between conversion and drop-off and becomes a digital advisor with AI. From semantic search through personalised recommendations to automated answer generation: search technology that understands what's meant and delivers solutions instead of hit lists.
AI search, AEO & recommendations
More than a search box: search that understands and recommends
Site search decides whether users find what they're looking for or leave. Classic full-text search is no longer nearly enough for that. Modern search architectures combine proven engines like Elasticsearch or Solr with AI-supported approaches: semantic understanding, vector search and knowledge linking. This way, search evolves from a product finder into a context-aware advisor.
Complemented by recommendation engines and personalisation, a search experience emerges that doesn't just deliver results but boosts relevance, guidance and conversion. Whether as a managed solution or deeply integrated into your platform: scalable and consistently high-performing.
LET'S TALK!
From the results list to the digital advisor.
We clarify which search scenarios can be improved in the short term with semantic search and AI recommendations at your organisation, and what data and integrations that requires.
Deploy search, recommendations and personalisation with purpose
Technology that measurably contributes to conversion and customer experience.
Relevant search results
Elasticsearch, Solr or specialised AI engines, configured for your use case. Synonyms, facets, error tolerance and AI ranking ensure your users find what they're looking for.
Personalised recommendations
Recommendation engines deliver individual product and content suggestions based on real user behaviour. Data-driven, contextual, and with measurable impact on basket size and dwell time.
Answers instead of result lists
Generative search via RAG answers natural-language questions directly from your content. A query becomes a consultation with source references.
Search as strategic lever
Search queries reveal what your customers really want. This data can be used for assortment planning, content strategy and lead qualification. Search becomes a business intelligence tool.
Seamless integration
Whether shop system, DXP or content platform: search and recommendation solutions integrate cleanly into existing architectures without compromising on performance or data quality.
References
Search results from practice
Project examples with measurable impact on search, conversion and user experience.
The interesting question isn't how many results your search returns, but whether it understands what's meant. That's exactly where the difference between a results list and an advisor begins.
Your path to intelligent search
Search audit & potential analysis
Analyse search behaviour, zero-result rates and conversion gaps: make blind spots visible and set priorities.
Technology selection & architecture
The right engine for your data basis, scaling and business goal: from proven open-source solutions to AI-driven search architectures.
Implementation & Integration
Clean integration into your system landscape. Agile, documented and coordinated with your teams.
Optimisation & tuning
Relevance tuning, personalisation rules and recommendation logic are continuously refined based on real usage data.
Why search is now becoming strategic
Figures showing where search and visibility are heading.
3 stages
of hybrid AI search
From product finder to context-aware advisor to lead generator
2,15 %
CTR of informational keywords under Google AI Overviews
Down from 2.65% previously: good rankings alone are no longer enough, content must be optimised for answer engines
4 weeks
until first measurable relevance uplift
PLACEHOLDER, TO BE CHECKED: typical timeframe from search audit to first tuning result
KNOWLEDGE TO TAKE AWAY
Insights
Sound knowledge on search, visibility and AI, free to read.
Frequently asked questions on site search & AI recommendations
Site search is the internal search on your website or shop. It decides whether users find what they are looking for in seconds or leave. For extensive catalogues, it becomes the most important conversion lever.
Proven engines such as Elasticsearch and Solr often form the basis. Depending on requirements, specialised solutions such as Crownpeak Fredhopper, search-as-a-service or AI-supported approaches with vector search and RAG are added.
Personalised recommendations measurably increase basket value, dwell time and customer satisfaction. The logic is based on real user behaviour, not static rules.
AI-powered search unlocks its greatest leverage especially with extensive product catalogues, explanation-heavy ranges or multilingual platforms.
LET'S TALK!
Discovery call: from the results list to the right answer.
We clarify which search scenarios can be improved in the short term with semantic search and AI recommendations at your organisation, and what data and integrations that requires.
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