A global appliance company wanted to better understand the customer journey of purchasing a coffee machine at Walmart. Traditional focus groups and shop-alongs would have required weeks of recruitment, fieldwork, and analysis. Instead, they used Zibble's generative AI insights platform to simulate customer experiences and identify pain points across the journey, all within hours.
Zibble built personas using over 150 qualitative data points, including motivations, shopping habits, and attitudes toward appliances. Personas were then interviewed on their end-to-end experience, from awareness to post-purchase, interacting with Walmart and the brand. Insights were synthesized into a structured journey map highlighting emotions, barriers, and opportunities at each stage.
Stage 1: Awareness
"I'd heard of the brand before, but mostly through online ads. I wasn't sure how it compared to other coffee machine brands." Brand awareness lacked depth; customers recognized the name but had low familiarity with unique features.
Stage 2: In-Store Search and Consideration
"The shelf was crowded with different machines. The packaging didn't stand out, and I had to spend extra time comparing specs on my phone." Packaging and in-store presence were not differentiated enough, creating decision fatigue.
Stage 3: Evaluation
"I wanted to know how reliable the brand was, but the in-store signage didn't provide reviews or clear comparisons. I left the aisle twice to look things up online." There was a lack of trusted, accessible product information at the point of decision.
Stage 4: Purchase
"Checkout was smooth at Walmart, but I wasn't fully confident I'd made the best choice. I worried I was taking a risk." Lingering uncertainty at the moment of purchase due to limited reassurance.
Stage 5: Post-Purchase Use
"The machine worked well, but the setup instructions were confusing. I had to watch a YouTube video to figure it out." An onboarding gap created friction in the early usage stage.
Zibble revealed five key journey pain points: low brand familiarity despite awareness, weak shelf differentiation, lack of accessible product comparisons, a confidence gap at purchase, and onboarding issues post-purchase.
These insights allowed the brand to redesign packaging for stronger in-store visibility, add QR codes linking to product reviews on boxes, simplify setup guides with step-by-step visuals, and refocus messaging on trust and reliability at the decision stage.
With traditional research, this project would have taken 6 to 8 weeks and cost tens of thousands of dollars. Zibble delivered qualitative depth at 1000x the speed and a fraction of the cost, enabling fast, evidence-based decisions to improve the customer journey. AI personas uncover pain points in real time, delivering scientifically robust insights without the bias, cost, or delays of traditional focus groups.
