Experimentation
CRO & Experimentation Program
Turn your visits into measurable growth
- AB Tasty
- Kameleoon
- Dynamic Yield
- and 3 other tools
Experimentation
Merchandising optimization
Make your list pages sell, proven by the test
Optimize the content, ranking and product recommendations on your listing pages and search, proving every change with an A/B test before rolling it out.
The need
What you tell us
« My list pages and search drive most of my sales, but banners, sorting and merchandising rules are managed by feel. I want to optimize content and ranking algorithms, and prove every gain through A/B testing. »
- « I want my listing pages to sell more »
- « I want to move beyond gut-feeling merchandising »
- « I want to truly leverage Algolia / Dynamic Yield »
- « I want to prove the effect of each merchandising rule »
Our response
- Merchandising audit: content, sorting and recommendations
- Optimization of ranking, recommendations and banner content
- A/B tests: every change proven
Method
Our method in 5 steps
Our stance
Every merchandising rule tested
Every sort, banner or merchandising rule is treated as a hypothesis and tested before being rolled out.
- Ranking
- Content
- Proof
Step 01 : Audit
Analysis of the performance of your listing pages and search, review of sorting, rules and existing content, and study of navigation paths to isolate quick wins.
- Performance of list pages and search
- Sorting, rules and content in place
- Navigation journey analysis
- Quick wins identified
Step 02 : Ranking & recommendations
Definition of a composite scoring system (Algolia) and product recommendation strategies (Dynamic Yield) fueled by your stock, margin and performance data.
- Composite scoring (Algolia)
- Product recommendation strategies (Dynamic Yield)
- Data to inject: stock, margin, performance
- Special cases and seasonality
Step 03 : Banner content
Creation of conversion-oriented listing content, optimization of placements and formats, and asset production plan aligned with your campaigns.
- Conversion-oriented list content
- Optimized placements and formats
- Consistency between campaign and category
- Asset production plan
Step 04 : Implementation
Deployment of merchandising rules, connection of your BI data, sorting QA and performance monitoring.
- Merchandising rules in production
- BI data injection connected
- Testing of sorting and rules
- Performance monitoring
Step 05 : A/B tests
Testing of each evolution on your traffic, statistical reading by segment, generalization of winning variants and capitalization in a merchandising learnings base.
- Every change tested on your traffic
- Statistical reading by segment
- Rollout of winning variants
- Merchandising learnings database
Customer reviews
Ce qu'en disent nos clients
We particularly appreciated our collaboration with Welyft. The team combines professionalism, availability and a strong solution-oriented approach. Communication is simple, transparent and efficient, even during the more complex phases of the project. A smooth and constructive collaboration that we highly recommend.
- CRO
- Tool : Dynamic Yield
Margaux Genevey
E-merchandising Manager
Deliverables
What you get
Merchandising diagnostic
Prioritized opportunities.
Ranking & recommendation strategy
Scoring and strategies documented and set.
Optimized rules & content
In production.
A/B test reports
Proven gains through iteration.
Who is it for?
Who is this offer for?
Tools used
- Algolia
- Dynamic Yield
- AB Tasty
- Kameleoon
- Contentsquare
- E-commerce with a large catalog and high traffic on listing pages
- Search and merchandising tools in place (Algolia, Dynamic Yield)
- Sponsor: Head of E-com, Merchandising Manager, CRO Manager
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Drive decisions with reliable data
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Give every customer their own journey
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