Example scenario, not a customer claimMetric to measureRecommendation engagement Metric to measureRepeated product questions Metric to measureHandoff quality
E-commerce Example Scenario
How a commerce team could use Trigz to reduce repeated product questions.
This example scenario shows how a team can structure a Product Advisor pilot, connect product data and FAQs, configure human handoff, and measure product discovery impact before expanding.
ProblemProduct AdvisorOutcome
Product dataFAQ knowledgeSelected channelHuman handoff
What this pilot should measure.
Recommendation engagement
Track how often shoppers interact with product recommendations.
placeholder - Defined during pilotProduct question reduction
Track repeated product questions before and after launch.
placeholder - Defined during pilotHandoff quality
Track whether human teams receive enough context when shoppers need help.
placeholder - Defined during pilotWorkflow profile
The context behind the workflow.
- Customer type
- E-commerce team
- Industry
- Commerce and retail
- Use case
- Product guidance and product support
- Pilot scope
- One product category or one customer channel
- Template used
- Product Advisor
- Supporting template
- FAQ Assistant
- Channels to evaluate
- Web chat, WhatsApp, Instagram, email
- Knowledge needed
- Product catalog, product FAQs, shipping and return policy
- Metrics to track
- Recommendation engagement, repeated questions, handoff rate
The challenge
Shoppers often need help before they are ready to buy.
In a typical commerce workflow, customers ask repeated questions about product fit, differences between options, sizing, availability, delivery, returns, or recommendations. If every answer stays manual, support volume grows and high-intent shoppers may leave before getting useful guidance.
Why Trigz
Why start with a Product Advisor workflow.
A Product Advisor workflow gives the team a focused starting point: one customer-facing use case, one knowledge set, one recommendation path, and one set of metrics to review.
The solution
Trigz structures product guidance as a measurable workflow.
The team starts with the Product Advisor template, connects product data and product FAQs, defines recommendation questions, configures fallback, and launches in one selected channel. When the shopper needs more help, the workflow can hand off with a summary and context.
Product Advisor
Product data, product FAQs, shipping and return policies
One selected channel first
Recommend, clarify, route, and hand off
Support or sales owner
Recommendation engagement and handoff rate
Workflow architecture
How the Product Advisor workflow works.
The workflow connects a shopper request to product knowledge, recommendation logic, human handoff, and measurement.
Implementation journey
From product guidance idea to measurable pilot.
Selected one product category
The team limits the pilot to a clear product scope.
Prepared product data and FAQs
Product attributes, common questions, and policies are reviewed.
Defined recommendation questions
The agent asks clarifying questions based on shopper needs.
Configured fallback and support handoff
The workflow escalates when product knowledge is missing or judgment is needed.
Tested common product questions
The team tests realistic shopper scenarios before launch.
Launched in one channel
The pilot starts in a controlled scope.
Reviewed engagement and missing knowledge
The team reviews early signals and improves the workflow.
Results and impact
Expected impact areas for this pilot.
Because this is an example scenario, the public page shows measurement areas instead of fake results.
Control and handoff
Where humans should stay involved.
The workflow should route to a person when the shopper needs judgment, reassurance, or help beyond approved knowledge.
Handoff triggers
- Customer asks about unavailable product
- Customer needs personalized help
- Customer asks about refund or payment issue
- Product data is missing
- High-value order or VIP customer
- Customer expresses frustration
Context captured
- Products discussed
- Customer needs
- Questions asked
- Recommendation shown
- Missing details
- Suggested next step
Lessons learned
What this kind of workflow can reveal.
Start with one product category
A narrower scope makes product data easier to prepare and testing more realistic.
Product knowledge quality matters
Recommendations depend on clean product attributes and approved FAQs.
Handoff improves trust
Human review keeps the workflow safe for complex or sensitive cases.
Engagement data guides expansion
Recommendation engagement and missing knowledge patterns show what to improve next.
What powered the workflow
Templates, channels, and knowledge used in this scenario.
Channels
Web chatWhatsAppInstagramEmail
Knowledge
Product catalogProduct FAQsShipping policyReturn policy
Actions
Recommend productAsk clarificationRoute to supportCapture lead or handoff
Integrations
Commerce catalogMessaging channelSupport handoff
Some integrations or workflow actions may require setup review depending on plan and implementation scope.
Customer quote pending approval.
Once approved, this section can include a customer quote connected to product guidance, support workload, or shopper engagement.
Related stories
Explore more workflow stories and pilot examples.
Want to build a workflow like this?
Book a demo and map your first workflow to the right template, channel, knowledge, and success metric.
Start with one workflow. Measure the outcome. Expand with confidence.