Ecommerce Merchandising / Product Recommendations Expert - Paid Platform Review (Ongoing Panel)

Ecommerce merchandising / product recommendations expert wanted for a paid review of our recommendation engine. Ongoing panel, US-based preferred.

Personyze is a personalization platform with a product recommendation engine - behavioral, catalog-based and rule-driven recommendations across web and email. We want a senior ecommerce merchandiser or recommendations specialist to evaluate that engine the way you would evaluate any vendor you were about to put in front of your catalog.

You get a test account with a sample catalog, or you can connect your own test store. We want your judgment on: catalog ingestion and feed handling; the recommendation algorithms available and whether the strategy set is complete; merchandising controls such as pinning, boosting, exclusions and business rules; how recommendations are placed and templated on-site; performance reporting and attribution; and cold-start and sparse-data behavior.

Then tell us, ranked, what is missing versus Nosto, Dynamic Yield, Algolia Recommend, Rebuy, or whatever you run today.

Deliverables:
1. A hands-on working session, 60-90 minutes, setting up at least one live recommendation widget end to end.
2. A written review, 800-1500 words, against a rubric we supply. Structured, blunt, specific.
3. A recorded screen walkthrough (Loom or similar, 20-40 min) narrating your first-run experience out loud - where you hesitated, what you expected to find and did not. Unpolished is fine, this is the most valuable part for us.
4. Your ranked top 5 gaps versus the tool you actually use today, with the business impact of each.
5. A 30-minute call with our product team.

This is evaluation, not implementation. We are not asking you to build, write or ship anything. Your job is to tell us where the platform falls short of what a professional in your field needs.

Who this is for: you have owned merchandising or recommendation strategy for a real catalog and can tell the difference between an algorithm that works and a demo that looks good.

Terms: 500 USD fixed for round one, approximately 4-6 hours of work. This is an ongoing panel - we ship features regularly and want the same reviewers back every 6-10 weeks at 400-500 USD per round. A 30-minute interview before any award.

Please answer in your proposal:
1. Which recommendation or personalization platforms have you personally worked in, and for how long in each?
2. One specific example of a merchandising or recommendations program you ran and the measured outcome.
3. What is the single most common reason a recommendations tool loses your team's trust? One paragraph - this is the question we actually read.
4. A link to something public you have made: a case study, teardown, talk or post.