Treat favorites as a decision signal, not just a reminder
High-performing teams treat favorites as a moment of decision, and they respond with guidance that helps shoppers move forward with confidence. Harney & Sons, a family-run American tea company, activated this signal by using favorites in Customer Hub to trigger short, targeted "micro-flows" that brought shoppers back into the purchase cycle. In their first quarter using Customer Hub, Harney & Sons generated more than $120,000 in attributed revenue, demonstrating the impact of acting on saved products rather than treating them as passive browsing.
Key takeaways:
- Trigger a micro-flow within a few hours after a shopper saves one or more items to favorites without placing an order.
- Personalize micro-flow content with the exact items favorited and a clear next step back to the product.
- Use supportive language that builds confidence (e.g., sizing guidance, reviews) rather than pressure.
- Reserve discounts for later touches or only if the micro-flow fails to convert.
By activating favorites within a broader, connected experience, Harney & Sons converted high-intent behavior into revenue while reinforcing trust and long-term customer value.
Make logged-in experiences immediately valuable for the shopper
Login behavior reveals far more than account creation alone and can indicate readiness to purchase. Half Magic, a direct-to-consumer beauty brand, used Customer Hub and Klaviyo reporting to evaluate how logged-in actions such as favorites, subscriptions, and order history correlated with repeat purchases and long-term value. Instead of treating account creation as a one-time goal, the team centralized these experiences into a unified logged-in environment and used engagement patterns to personalize product discovery, subscription engagement, and reorder experiences for different shopper segments. This approach contributed to a 5X increase in repeat purchasers and 110% year-over-year growth from flows.
Key takeaways:
- Identify which logged-in actions most strongly correlate with repeat purchases in Klaviyo reporting.
- Prioritize personalized experiences for customers who log in but do not immediately convert.
- Use login behavior to distinguish casual shoppers from high-potential customers.
- Optimize logged-in experiences based on engagement quality and purchase outcomes.
Evaluating login behavior as a signal of customer readiness and intent helped Half Magic create more personalized paths to conversion and repeat purchases, strengthening retention and long-term value.
Turn Customer Agent conversations into a growth signal
Customer Agent conversations can do more than resolve questions. They can help customers choose with confidence and show you where service can support growth. NANUK, a brand that sells waterproof protective cases, used K:AI Customer Agent and Customer Hub to answer repetitive technical questions such as “Will it fit in the case?” and provide 24/7 self-service support. Over a 90-day period, Customer Agent resolved 84% of NANUK’s chat queries, including 100% of product recommendation queries and 100% of return and exchange queries, giving the service team more capacity for high-impact work and VIP relationships while supporting future sales conversations.
Key takeaways:
- Identify repetitive pre-purchase questions that indicate customers need product guidance or reassurance.
- Use Customer Agent to answer technical FAQs and make helpful product recommendations using your connected content.
- Measure performance by conversation intent, not just total volume, to understand which questions are resolved and where customers still need support.
- Use recurring questions to improve product information, on-site messaging, and self-service content.
- Route complex or relationship-driven conversations to human agents so they can focus on high-value customer interactions.
When you treat Customer Agent conversations as signals of intent, you can reduce friction in the moment, improve the path to purchase, and create more capacity for human-led experiences.
Use Helpdesk trends to decide what to fix upstream
Support trends become most valuable when they help teams decide what to fix before issues repeat. Folk Clothing, a London-born fashion label known for premium fabrics and sustainable design, used Helpdesk trends to identify where friction could be removed earlier in the journey rather than focusing only on faster resolution. By analyzing recurring ticket themes across channels, the team automated 53% of support conversations and reduced average resolution time by 75%.
Key takeaways:
- Identify repeat ticket themes that indicate avoidable friction.
- Prioritize fixes that reduce future tickets, not just response time.
- Use Helpdesk insights to inform updates to product display pages, Customer Hub content blocks, FAQ pages, or marketing flows.
- Revisit trends regularly to ensure fixes are working.
By using Helpdesk data to guide upstream decisions, Folk Clothing reduced friction before customers needed to ask for help and improved the overall experience. Remember that the time you save by fixing these issues upstream compounds over time, reducing future support demand while creating smoother, more confident customer journeys.