Carol Munar

Product Designer

Say Hola!
alphin

AI-Powered Review Replies for Local Businesses

Year 2023 - 2025
Industry B2B, B2C · SaaS · AdTech
Scope Lead Product Designer
Alphin dashboard — review reply interface

Problem

Restaurant owners were drowning in Google reviews. 20–50 reviews per week, 15 minutes per response. But here's what surprised me: they weren't just slow at responding—they were actively avoiding negative reviews.

Through Hotjar recordings and owner interviews, I watched the pattern repeat: scroll past the 2-star review, hope it goes away, respond to the easy ones with templates. The result? Unanswered negative reviews eroding trust faster than the review itself.

The real problem: Alphin's sales team couldn't sell the platform. It felt like more work, not less.

The Brief

Make responding to reviews effortless—including the uncomfortable ones—without feeling generic.

Alphin — review list with negative reviews Alphin — dashboard stats and activity panel

Solution

I designed an AI-assisted reply system embedded in Alphin's dashboard. When a review arrives, the AI generates a tailored response. The user edits it, adjusts tone, switches language if needed, and publishes. One click.

Key Decisions

Full editability.

The AI suggestion appeared in an editable text field from the start—never locked. Business owners needed to feel the words were still theirs.

Tone and language control.

Users could adjust warmth, formality, and directness. For Berlin restaurants serving international crowds, responding in the reviewer's language became a differentiator.

Making negative reviews approachable.

A pre-filled reply for a difficult review removes the emotional friction of staring at a blank box. Users started responding to reviews they'd previously ignored.

I also worked with sales to reframe the pitch: from "AI feature" to "protect your reputation, free up your time." That narrative shift drove adoption.

Alphin — analytics and impact Alphin — tone control feature

Impact

Metric Before After
Response time 15 min 3 min
Response rate baseline +28%
New client acquisition baseline +4%

Users stopped writing from scratch. They started with the AI draft every time—not because the product forced it, but because the output earned their trust.

We tracked response time, response rate, and new client acquisition rate as primary success metrics. Specific numbers are under NDA, but the directional results were strong enough that the feature became a core part of Alphin's sales pitch within the first quarter after launch.

Alphin — language and tone controls

Learnings

AI features are trust problems, not technology problems.

The AI worked from day one. The hard part was making users comfortable putting their name on it.

Design impact extends beyond the screen.

The biggest leverage wasn't the UI—it was reframing the sales narrative.