Product pages
01Fix product pages at scale
Find missing product facts, weak PDP content, and catalog issues, then prepare the fix for review.
- PDP audits
- Catalog diagnostics
- Structured data
One place to see where shoppers choose you, and where they don't.
Beseam connects what shoppers see before they visit, what they find on your store, what they do next, and what happens after a change. It turns those signals into a ranked queue of work instead of another set of dashboards to manage.
The shopper question, the evidence, the change, your approval, and the result stay connected.
See the work, not another dashboard.
Beseam turns the strongest findings into one ranked queue: what to change, why it matters, what it affects, and whether it needs your approval before a shopper sees it.
Add the commuting use case to the Urban Shell product page.
Needs approvalQuickTop 5% of your booked sales
Explain how Urban Shell fits over everyday layers.
In motionQuickTop quarter of booked sales
Ask the commuter questions again after the product-page change.
MeasuringQuickNot measured
Illustrative example · not customer results.
ChangeSales shareEffortStatus
Add the commuting use case to the Urban Shell product page.
The shopper asked for a commuting jacket, and the product page never answers whether this one fits that use case.
Explain how Urban Shell fits over everyday layers.
The shopper opened the size guide, and fit over layers is still unanswered at the decision point.
Ask the commuter questions again after the product-page change.
Ask the same shopping question again before saying the change helped discovery.
Every change keeps what Beseam found, the owner, status, and what to check afterward together.
Illustrative example · not customer results.
Capabilities
The jobs you can hand to Beseam.
Use one capability for a specific problem or combine several around the same product, campaign, or shopper journey. The work stays connected to the same store context, evidence, approvals, and results.
Search & merchandising
02Tune what shoppers find
See where store search fails and control which relevant products get surfaced, ranked, or filtered.
- Onsite search
- Ranking & filters
- Merchandising rules
Fit & sizing
03Reduce sizing uncertainty
Measure shoppers, recommend product-level sizes, and see where fit guidance still needs work.
- Foot measurement
- Fit recommendations
- Sizing analytics
Personalization
04Control recommendations
Use shopper and product context to decide which products to recommend, order, and present.
- Recommendations
- Affinity signals
- Decisioning
Experiments
05Test changes safely
Run controlled experiments and keep a baseline so a promising idea does not become an unmeasured rollout.
- A/B tests
- Holdouts
- Experiment results
Store health
06Catch store problems early
Find slow pages, frontend errors, broken flows, and stale connections before they quietly cost purchases.
- Web Vitals
- Errors & alerts
- Reliability checks
Creative studio
07Create product content & media
Turn an approved improvement into the copy, images, video, and store assets needed to ship it.
- Product content
- AI images
- AI video
Campaigns
08Build campaign work from insights
Carry what you learn about products and shoppers into campaign plans, messages, and creative variants.
- Campaign planning
- Creative variants
- Offer inputs
Measurement
09Measure revenue impact
Keep conversion, orders, revenue, and re-checks tied to the change that came before them.
- Before & after
- Revenue impact
- Commerce ledger
More
10+ more across your stack
Bring in specialist signals when the question needs them without turning every integration into another dashboard to manage.
- Session replay
- Attribution
- Integrations
Availability depends on the systems connected to the store. Customer-facing publishing and generated assets remain separately controlled.
One finding, end to end
Keep the question, change, and result in the same loop.
A finding is useful only if it can become a specific decision and be checked again afterward. Here is that loop.
See how the approval and re-check process worksFAQ
Questions about the platform.
Do I need to use every Beseam capability?
No. Start with the storefront and store connection, then turn on deeper discovery, analytics, behavior, fit, personalization, reliability, creative, campaign, or revenue capabilities only when they help answer a real question or execute the work you want Beseam to handle.
What kinds of systems can Beseam connect to?
Beseam can work with commerce and catalog data plus connected analytics, behavior, search, reliability, campaign, customer, and revenue sources. The exact integrations and write capabilities depend on the store and systems you connect.
Can Beseam work alongside tools we already use?
Yes. Existing analytics, replay, experimentation, reliability, advertising, or other specialist tools can remain in place. Beseam can use their evidence where connected and keep it attached to the product, journey, action, and outcome being investigated.
How do findings from different parts of the journey stay connected?
Beseam keeps the original observation, affected product or journey, supporting evidence, proposed change, approval state, and later measurement in the same work record. Discovery, store, behavior, and outcome evidence can contribute without becoming separate inboxes.
What can Beseam apply directly?
That depends on the connected system. Beseam can prepare work across product data, content, merchandising, search, recommendations and personalization, fit, experiments, creative assets, campaigns, and store changes; supported writes can be applied after the required approval, while unsupported work stays as a concrete handoff.
How do Creative Studio, fit, personalization, and campaigns fit into the platform?
They are not separate stories bolted onto an AI-search product. They are capabilities that can use the same product, shopper, store, and outcome context. Availability depends on what is enabled for the store, and campaign capabilities are only available where campaign access is enabled.
How are customer-facing changes controlled?
You set the approval rules. Beseam can keep monitoring and preparing work automatically, but customer-facing changes that require approval stay pending until someone with the right authority approves them.
How is impact measured across different kinds of changes?
Beseam re-checks the evidence appropriate to the original problem: an AI answer, product or store condition, shopper behavior, experiment, reliability signal, campaign performance, conversion, orders, or revenue. Observed movement stays separate from causal claims the evidence cannot establish.
Start with your store. Connect more only when it helps answer a real question.
Start with the storefront and store connection. Add deeper data only when it helps explain a problem, choose the next change, or measure what happened afterward.