Beauty · Example build — prototype scenario

Beauty brand

A beauty brand whose small team spent hours each day on product-fit questions and manual recommendations. The work was repetitive, hard to scale, and left little first-party data behind to act on.

01Business context

A beauty brand whose small team spent hours each day on product-fit questions and manual recommendations. The work was repetitive, hard to scale, and left little first-party data behind to act on.

02The problem

Repetitive support tickets and manual product recommendations were eating the team’s time.

03What we’d build

Built a product-recommendation quiz, a dashboard to read the data, and an email automation flow to follow up — reducing manual triage.

04 — Diagnostic

What the audit would surface.

  • 01Repetitive ‘which product is right for me’ tickets answered manually.
  • 02No structured first-party data captured from those conversations.
  • 03Follow-up emails sent ad hoc, not triggered by behaviour.

05 — Proposed architecture

How we’d build it.

  • 01A product-recommendation quiz capturing structured customer inputs.
  • 02A dashboard to read quiz data and segment customers.
  • 03An email automation flow triggered by quiz results, with human-reviewed templates.
Custom quiz appSupabaseResendReporting dashboard

06 — Implementation roadmap

01

Scope

Define quiz logic, data model and the decisions the dashboard must support.

02

Build

Quiz app, storage and reporting dashboard.

03

Automate

Behaviour-triggered email flow with human-in-the-loop drafts.

Potential impact & risks

Estimated impact: richer first-party data and less support friction. (Illustrative scenario, not a measured client result.)

  • Quiz logic must stay genuinely helpful, not a dark-pattern funnel.
  • Email automation needs consent and clean unsubscribe handling.
  • Recommendations should be reviewed so they stay accurate as the catalogue changes.

This is a example build — prototype scenario. Figures are illustrative and not a guaranteed result — your numbers will depend on your store, traffic and market.

Want a build like this — measured for your store?

Start with an audit. We’ll tell you whether the opportunity justifies the build.