Make buying easier. Fix what stops the sale.
A conversion number hides the work customers are trying to do. We combine behavior, customer questions and product facts to improve search, product evaluation, cart, checkout and account experiences with your product and engineering teams.
Sound familiar?
Customers cannot find a fit
Queries, filters and product descriptions leave shoppers unsure what to choose.
The funnel changed
Device, market and checkout behavior diverge beneath an aggregate conversion rate.
The roadmap is waiting
Product and engineering teams have known friction but limited capacity to investigate and ship.
- Best for
- Ecommerce and digital-product teams with a complex range, uncertain funnel friction or an experience waiting on delivery capacity.
- First step
- Bring one buying journey, recent behavior and representative customer questions. We identify the evidence and implementation needed for a useful first change.
- Works with
- Your commerce platform, analytics, site search, reviews and testing tools.
Help customers choose, buy and come back.
Illustrative example
Find where shoppers drop out and what to fix.
TriggerA conversion decline or recurring trading review.
Source
What it draws on
- Funnel events and order outcomes with agreed definitions
- Device, market and product segments
- Customer questions, search behavior and available session evidence
What the team sees
| Journey | Finding | Proposed response |
|---|---|---|
| Mobile product comparison | Key dimensions hidden below the fold | Test a visible comparison module |
| International checkout | Shipping availability unclear | Expose eligible delivery before payment |
| Cart event reporting | Event missing after recent release | Repair measurement and recheck |
What you get
Prioritized findings by page, device, market and funnel step.
Measured by
- Time to locate and explain journey friction
- Purchase and checkout completion in relevant segments
- AI
- AI reads customer questions and journey evidence to separate plausible causes of drop-off.
- Rules and automation
- Event checks confirm the funnel is measured correctly, and segment comparisons show where journeys diverge.
- Your team
- Your team chooses which fixes and experiments to run and how each one will be judged.
Build a shopping assistant that helps customers choose.
TriggerA shopper asks for advice or compares products.
Source
What it draws on
- Approved product facts and compatibility rules
- Current price, availability and channel eligibility
- Representative buying questions and customer support boundaries
What the team sees
- Shopper
I need a washable bag for a weekend trip. Will the compact weekender fit in the cabin?
- Shopping assistant
Which airline or size limit do you need it to meet? The compact weekender’s approved care record says spot-clean only, so it would not meet your machine-washable requirement.
- Shopper
Machine washable matters more. Can you suggest an alternative?
- Shopping assistant
The washable tote is a supported alternative: its approved care record permits machine washing, and the current stock record shows the navy variant available. The stone variant is unavailable. I can show the tote’s dimensions and current price; I would need your airline’s limits before confirming cabin fit.
- Care instructions and dimensions come from the approved product records.
- Variant availability and price are checked against the current selling source.
- Cabin fit remains unconfirmed until the customer supplies the relevant size limit.
What you get
A product-grounded guided-shopping experience with useful next actions.
Measured by
- Recommendation fit and source accuracy on representative questions
- Useful customer next actions and assisted purchase completion
- AI
- AI asks about the shopper’s needs, compares eligible products and explains the recommendation.
- Rules and automation
- Integrations retrieve approved product facts and current price, stock and channel eligibility.
- Your team
- Your team defines product claims and service boundaries and handles questions the available evidence cannot answer.
A product comparison fails on mobile.
An illustrative journey connects search terms, product questions and a mobile comparison screen.
A product attribute changes. The comparison and assistant answer are refreshed from the approved product record.
The handoff
Find unanswered buying questions
Verify comparison attributes
Build and test the relevant screen
Check mobile behavior and product grounding
Measure purchase completion and customer feedback
Built around your tools and team.
How we work togetherEvidence-led diagnosis
Reconcile analytics definitions and connect observations to customer needs before ranking changes.
Customer-facing capability
Build product-grounded advice, search improvements and decision support into the existing web or app.
Delivery with your team
Work through briefs, implementation, real-case QA and experiment readouts alongside product, design and engineering.
How we’ll know it’s working.
We agree the measures and a baseline before building, then compare like with like after launch.
| Measure |
|---|
| Journey completionCompare search success, checkout completion and purchase outcomes in relevant segments. |
| Answer usefulnessReview product accuracy, recommendation fit and useful next actions. |
| Learning and deliveryTrack investigation time, experiment throughput and supported impact rather than counting releases alone. |
Connected work.
More connected work
Help customers take the next step. Turn evidence into a better buying experience.
Prefer to start with discovery?
We reply within one business day.