Make sense of your performance
After you've created connected experiences, the next step is to evaluate their impact. K:Service analytics tools help you understand how shoppers engage, where friction still exists, and which improvements will make the biggest difference.
In this lesson, you’ll learn how to read analytics to identify patterns, connect signals across tools, and decide where to refine your experience to drive repeat purchases and loyalty.
Use analytics tools to measure performance
Rather than tracking every metric, which can become overwhelming, focus on insights that help you answer a simple question: Where should I improve the customer experience next?
The dropdowns below group K:Service analytics by the type of decision they support. Expand each one to learn more.
On-site engagement and revenue impact
Customer Hub analytics help you analyze whether overall experiences are building shopper confidence or creating friction before purchase.
Use these insights to analyze:
- Overall revenue driven by Customer Hub experiences, like product recommendations or featured blocks
- Engagement with favorites, content blocks, and recommendations
- Which guided actions shoppers take more or less frequently
If engagement is low, the experience may not feel relevant or clear. If engagement is high but revenue lags, shoppers may still need stronger reassurance or next steps.
Shopper intent and hesitation
Customer Agent insights help you analyze where shopper interest turns into hesitation and what questions are slowing purchase decisions.
Use these insights to analyze:
- Conversation trends and repeated questions
- High-volume queries that signal common blockers
- Knowledge gaps where shoppers need more clarity
Frequent questions often point to missing or unclear information earlier in the journey. These insights help you decide where to improve on-site content, product details, or guidance.
Support efficiency and helpfulness
Helpdesk reports help you analyze where friction persists and how effectively customer issues are being resolved.
Use these insights to analyze:
- Ticket volume and recurring issue types
- Response and resolution trends over time
- Customer satisfaction after support interactions
Recurring issues often signal friction that could be addressed upstream to reduce support demand and improve customer satisfaction.
Evaluate insights across the customer journey
Remember Beantown Coffee, our fictional coffee brand with an online store for beans, merch, subscriptions, and more? As Beantown promotes a seasonal small-batch roast and its monthly subscription, shoppers are engaging with product pages and saving their favorite items. But Beantown notices that online conversion has slowed, and support volume is starting to rise. The team wants to understand where shopper confidence is breaking down and what to improve before launching new campaigns or experiences.
Data is most powerful when viewed holistically. The gallery below walks through an example of how Beantown used insights from Customer Hub, Customer Agent, and Helpdesk to understand a common customer problem and decide what to improve next.
What happened on-site
Customer Hub analytics reveal how shoppers interact with on-site experiences, highlighting where interest is high and where momentum slows.
In Beantown’s case, they found:
- Low engagement with the rewards program content block
- Frequent use of favorites and saved products that rarely led to purchases
- Shoppers explored the subscription content block but often stopped before subscribing
These signals show interest without commitment. Shoppers are engaging with products but hesitating to take the next step.
What the team did:
Beantown upgraded its outdated rewards program into the new Mug Club. The team refreshed branding, clarified membership value with clear perk messaging, and simplified the joining experience. They also refined supporting content to reinforce the benefits.
What customers asked
Customer Agent insights show where shopper interest turns into hesitation and which questions slow purchase decisions.
For Beantown, common conversations included:
- Shipping questions for seasonal blends during busy holiday periods
- Questions about roast profiles and flavor differences
- Concerns about subscription flexibility and delivery timing
These questions revealed uncertainty that on-site content did not fully address.
What the team did:
Beantown used conversation trends to strengthen both on-site content and the Customer Agent knowledge base. The team clarified seasonal shipping timelines, expanded roast and flavor details on product pages, and added guidance on subscription flexibility.
They also updated Customer Agent training using these clarifications, helping the agent provide more accurate, confident responses in future conversations.
By improving both on-site experiences and Customer Agent knowledge, the team reduced repeated questions and helped shoppers find answers earlier in their journey.
Where support was needed
Helpdesk reports highlight which issues drive recurring support requests.
In Beantown’s case, the team identified clear patterns:
- Product questions, such as gluten-free status for items like the Peach Praline scone, drove higher ticket volume
- Flow-related questions, especially during subscription onboarding, focused on managing delivery schedules and pausing orders
- Expectation gaps, such as delivery timing for bulk orders and sampler packs
These patterns showed that support issues often reflected moments where customers needed clearer guidance earlier in the journey.
What the team did:
Beantown used Helpdesk insights to identify where customers needed more guidance and addressed high-impact issues by providing clearer product details, expectations, and targeted FAQs. This reduced repeat tickets and improved the overall customer experience.
Note: The Marketing insights report is rolling out soon. If you do not see it yet, it will be available in an upcoming release.
How Beantown turned insights into action
When viewed together, these insights tell a clear story. Beantown shoppers showed interest in seasonal products and subscriptions, asked similar questions while shopping, and faced repeat questions after purchasing. Reviewing data across Customer Hub, Customer Agent, and Helpdesk helped the team uncover key friction points in the journey. Then they set out to solve each challenge one by one.
In the next lesson, you’ll explore best practices from real brands using K:Service to refine experiences and improve results.