TL;DR
A jobs-to-be-done study reconstructs a real, recent journey in detail, then uses a struggling moment within it to surface why someone chose what they chose. This template walks a specific episode chronologically, grounds the toolkit on camera, and closes on the functional, emotional, and social jobs a solution is really hired to do. Use the plain-text template at the end to run this study AI-moderated across any category.
What a shelf shopalong actually tells you
Most category research asks people to describe how they shop after the fact. A shelf shopalong watches it happen.
Filmed live at the point of purchase, this method captures what actually catches someone's eye, what confuses them, and what tips a decision between a winner and a runner-up in real time, not as a reconstructed memory. That distinction matters, because people are notoriously bad at describing shelf behavior accurately once they have left the store.
The output is a direct read on layout, signage, and packaging effectiveness, plus the specific trade-off that decided a purchase.
What this template covers
Twelve questions across one section, run live in-store. The logic flows in four stages:
Confirm store choice and pre-shop mindset before reaching the aisle
Film the shelf and capture first reactions to layout, signage, and promotions
Narrow to a final pick and the runner-up that almost won instead
Close on purchase frequency and satisfaction with the category range
A screener confirms the participant is on mobile and physically in the store before the interview begins. This is a hard requirement, not a preference, since the entire method depends on live filming.
Questions five and six capture the shelf itself: what catches attention first, and what signage or promotions stand out. Questions eight and nine are the decision moment, isolating not just the winning product but the specific trade-off that beat the runner-up. Questions eleven and twelve close on range satisfaction and advocacy, both structured ratings with a mandatory reasoning probe.
How to set up this study for your category
A few stetup rules:
Build the mobile-and-in-store screener exactly as written. Both conditions are non-negotiable for this method to work
Swap the category name throughout, but keep the live, in-the-moment framing intact
Recruit participants who are already planning to shop the category today, not people asked to shop artificially for the study
Where shelf shopalong research goes wrong
Three failure modes to watch for:
Skipping the screener conditions. If a participant is not genuinely in-store on mobile, the entire method collapses into a recalled description, which defeats the purpose.
Rushing the shelf reaction. Questions five and six need real filming time. If participants film too quickly, you lose the layout and signage detail that makes this method valuable.
Treating the winner in isolation. The trade-off against the runner-up in questions eight and nine is often more useful than the winning pick alone, since it reveals what almost changed the decision.
Running shelf shopalongs with Conveo
Conveo's AI moderator prompts participants in real time as they film, encouraging them to slow down, pan across the shelf, and narrate what they are seeing as it happens.
Follow-up depth adjusts automatically, moving quickly through factual questions and deep-diving on shelf reaction and the final decision
Live video is analyzed alongside the transcript, tying what participants said to what the shelf actually looked like
Thematic analysis surfaces recurring shelf friction points and decision trade-offs across participants without manual coding
Want to see how this template runs inside Conveo?
