Mobile ethnography means asking people to record their real lives on a phone, such as cooking dinner, using a product, or walking through a store, so researchers can see context instead of relying on memory. Indeemo-style tools approach this with a dedicated app where people capture moments. CoLab approaches the same goal differently: a multi-day online bulletin board that runs in the phone’s browser, with an app-like feel and camera capture built in. This post explains the difference and when each fits.
What app-based ethnography looks like
In an app-first design, respondents download an application, create an account, grant permissions, and then complete tasks inside it. For a highly engaged panel this can work well. For ordinary consumers recruited for a modest incentive, every extra step is a place to quit. Study invitations get lost between the email, the store page, and the first login.
Why app installs hurt completes
- People must find, download, and open the app before they ever see your first question.
- Storage, passwords, store accounts, and older phones create reasons to give up.
- Respondents on shared or work devices may not be allowed to install anything.
- Each reminder has to survive the gap between an email link and an app launch.
- When someone drops on Day 1, you have paid for recruiting and incentive with no data to show.
CoLab removes that gap. Respondents open a link and begin. There is no store download in the middle of the incentive journey, so tougher samples such as busy parents, shift workers, and less technical participants stay in the study.
App-like feel, camera included
No-install does not mean a clunky web form. CoLab is designed to feel like an app in the browser, with clear progress, simple day-by-day tasks, and camera capture on phones and laptops. Photo tasks can require a live camera capture rather than accepting any file from the photo library, which matters when you need to know a picture was taken for this study.
Screenshots versus camera photos, labeled for you
A common quality problem is a respondent uploading a screenshot or an old image instead of a fresh photo. CoLab labels screenshots and camera photos so researchers can tell them apart at a glance, and captured media can keep device labels when the browser exposes them. That keeps the readout honest when someone asks, “Did they actually take this at home?”
AI image review that flags mismatches
When enabled, AI image review compares an uploaded photo with what you asked for and flags mismatches. If you request the inside of a refrigerator and someone submits a picture of a street, you find out during field, while you can still send a follow-up, instead of discovering it in the final deck.
A day-based structure made for market research
| Study element | CoLab multi-day board | App-first ethnography |
|---|---|---|
| Respondent start | Open a link in the browser | Install, sign in, then start |
| Structure | Days that follow your discussion guide | Task or moment oriented |
| Photo quality | Camera capture, screenshot labels, AI review | Depends on the app’s design |
| Support | Help inside the board | Often outside the app |
| Analysis | AI-assisted themes while fieldwork is open | Varies by tool |
Example: a household-cleaning brand runs a four-day board. Day 1 sets context, Day 2 asks for photos of the cleaning cupboard, Day 3 tests product reactions, and Day 4 wraps up. The team watches early themes mid-week and adds a follow-up about storage because it appears in many photos.
When CoLab is the better fit
- You want to follow a discussion guide with days, stimuli, and probing questions.
- Your sample is general consumers or hard-to-reach groups who will not install an app.
- You need photos you can trust, plus transcripts for any video or audio.
- You want themes forming while the study is live and a debrief ready at close.
- Your agency needs to field the same design repeatedly for different clients.
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