Partner outcomes | case study

Scan success and repeat scanning at a GLP-1 provider

Prism Labs

Users achieving a successful scan at a large international GLP-1 provider.

Users with at least one successful result, November 2025 to August 2026.
Aggregate Prism scan data snapshot dated September 10, 2026.
Partner identity withheld.

Source: aggregate Prism scan data, September 10, 20261 / 8
The starting point

A baseline for improvement

November 2025 unique-user success ratio69.6%

151 users with a result out of 217 users who attempted.

November 2025 scan success rate53.1%

181 succeeded, 160 failed. Finished scans only.

The scan-level measure excludes scans that were created but not finished. The user-level measure counts a user with at least one successful result as successful, even if that user also had failed scans.

Source: aggregate snapshot, November 2025; definitions in source inventory2 / 8
A result for more users

More users got a successful result

November 2025 unique-user success ratio69.6%

151 of 217 users who attempted.

August 2026 unique-user success ratio97.8%

2,438 of 2,493 users who attempted.

November 2025 scan success rate53.1%

Finished scans only.

August 2026 scan success rate88.2%

Finished scans only.

What changed along the way

  • Visibility: a partner dashboard made scan outcomes visible for ongoing review.
  • User review: a user-in-the-loop scan review was introduced.
  • Targeted guidance: a written scan-success review provided recommendations, with a request to review pre-scan education and new/returning user flows.

Unique-user success ratio = users with at least one successful result / users with a succeeded or failed scan in that month. Documented interventions accompanied the improvement; their individual contribution was not measured.

Source: aggregate snapshot and documented partner-support history3 / 8
Scan outcomes

More scan attempts succeeded

Scan-level success rateNovember 2025 to August 2026
50%75%100%Nov 2025Aug 202650%75%100%Nov 25Aug 26
53.1%November 2025
88.2%August 2026

Monthly rate = succeeded scans / (succeeded scans + failed scans). Pending scans are excluded. Trend shows observations, not proof of causation. September 2026 is partial and is not plotted.

Source: aggregate snapshot, monthly scan_success_rate4 / 8
Scale

More scans and more active users

Monthly scans createdNovember 2025 to August 2026
022504500Nov 2025Aug 2026022504500Nov 25Aug 26
342 to 3,904Monthly scans created, November to August
217 to 2,507Unique users who scanned in each month

Scans include all scans created, regardless of outcome. Unique users are separately computed within each month and are not summed across months. September 2026 is partial and is not plotted.

Source: aggregate snapshot, monthly scans and users5 / 8
Repeat scanning

First-time scanners become returning scanners

First-time and returning monthly scannersComplete months, November 2025 to August 2026
First-timeReturning
Nov 25
217
Dec 25
246
Jan 26
421
Feb 26
746
Mar 26
1,143
Apr 26
1,251
May 26
1,482
Jun 26
1,854
Jul 26
2,128
Aug 26
2,507

Common scale: bar length is monthly user count. Returning = monthly users minus first-time scanners. Categories are monthly, not a longitudinal cohort.

54.2%3,513 of 6,480 users with a successful scan had more than one successful scan
147Users with 11 or more successful scans

The all-time repeat figures cover successful scans through September 10, 2026. Bars stop at August, the last complete month.

Source: aggregate snapshot, monthly users/first_scanners and repeat_scanning_all_time6 / 8
Observed return

More users returned the next month

Month-to-month returnNovember 2025 to July 2026
0%30%60%Nov 2025Jul 20260%30%60%Nov 25Jul 26
15.2%November 2025 cohort, 33 of 217 users
54.5%July 2026 cohort, 1,160 of 2,128 users

Share of users who scanned in month M and scanned again in month M+1. August does not have a complete next month in this snapshot. This is an observed cohort return measure, not a prediction of future retention.

Source: aggregate snapshot, month_to_month_return7 / 8
Activation hypothesis

Differentiate onboarding with body scanning

1. Show the value

Offer a body-composition scan as a distinct reason to begin, beyond a weight-only check-in.

2. Deliver a first result

Make the first scan easy to complete and explain what the result means in a wellness context.

3. Invite a return

Provide a clear reason to scan again and compare progress over time.

Illustrative interfaces and example values.

Activation lift is a hypothesis, not measured in these scan records. Test onboarding conversion and first successful scans before making a performance claim.

Source: Prism scanning reference designs; adapted illustrative interfaces8 / 8