TL;DR
A digital shopalong watches a real online shopping trip happen live, via screen share, so you see exactly where the journey works and where it breaks down. This template covers baseline shopping habits, pre-task intent, a live browse-to-basket walkthrough, and a specific friction point observed on screen rather than recalled afterward. Use the plain-text template at the end to run this study AI-moderated across any e-commerce category.
What a digital shopalong actually tells you
Usability surveys ask people to rate a site after the fact. A digital shopalong watches them use it, live, while they think aloud.
The method depends on separating what people say they like from where they actually get stuck. Participants often praise a site in general terms, then hit a real friction point minutes later that contradicts their own summary. This template is built to capture both, deliberately sequencing a friction-focused question before an advantage-focused one, so the analysis isn't skewed by whichever framing comes first.
The output is a direct read on searching, comparing, and deciding, tied to the exact moment something worked or didn't, not a general impression formed afterward.
What this template covers
Nine questions across one section, built around a live screen-share task. The logic flows in four stages:
Warm up and establish baseline shopping habits and brand preferences
Capture shopping mission and expectations before touching any interface
Run the live screen-share shop, from searching to basket
Isolate a specific friction point, then close on advantages and overall rating
Question five is the framing moment. It captures intent and expectations before the participant touches a screen, so any friction observed later can be judged against what they actually set out to do rather than read as a free-floating complaint.
Question six is the task itself: a live, narrated screen share from search through to basket. Question seven follows immediately, pushing for a specific, observed moment of friction rather than a general opinion. Question eight then asks for advantages, deliberately placed after friction so praise doesn't anchor the whole evaluation.
How to set up this study for your category
A few stetup rules:
Confirm participants can screen share before fielding; this is the core mechanic, and the study does not work without it
Let participants shop the site or app they normally use, not one you assign. Real behavior on a familiar interface is the point
Brief participants to record their screen before switching tabs, so the walkthrough is captured in full
Where digital shopalong research goes wrong
Three failure modes to watch for:
Asking about advantages before friction. If participants praise the site first, they tend to downplay problems that surface later. Keep the friction question first, as this template does.
Accepting a general opinion instead of a located moment. "The search was confusing" is not enough. Push participants back to the exact screen and moment where it happened.
Assigning a site instead of letting participants choose their own. Real behavior only shows up on an interface participants already know and trust. Forcing an unfamiliar site produces artificial friction that isn't representative.
Running digital shopalongs with Conveo
Conveo's AI moderator manages the screen-share task in real time, prompting participants to narrate their thinking as they browse and reminding them to record before they switch tabs.
The moderator sequences the friction and advantage questions automatically in the order that produces the most balanced read, without needing manual script adjustment
Screen recordings are analyzed alongside the transcript, tying what participants said to exactly what was on screen at that moment
Thematic analysis surfaces recurring friction points across participants and sites without manual coding
Want to see how this template runs inside Conveo?
