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Personal Utility App

Eau Claire Restaurant Picker

A local dining decision helper—filter by mood or cuisine, then randomly pick three Eau Claire restaurants when you can't choose where to eat.

ec-restaurant-picker.vercel.app/
Eau Claire Restaurant Picker redesign preview

Overview

Eau Claire Restaurant Picker is a personal utility I built and use when I want to go out but can't settle on a place. It isn't a review site or a map—it's a lightweight decision tool focused on my actual rotation of local restaurants. The public experience is intentionally minimal: choose a category, get three suggestions, reshuffle if needed. I maintain the restaurant list myself as spots open, close, or shift in and out of favor.

Problem

Deciding where to eat in Eau Claire sounds simple until you've scrolled the same lists, vetoed the same spots, and still have no plan. Group chats stall on "I don't care, you pick," and even a personal shortlist gets stale when mood and cuisine type matter as much as the restaurant name.

Solution

A single-page picker with category filters—pizza, Mexican, Asian, date night, takeout, and more—then a Pick 3 action that surfaces three random options from a curated local list. Pick Again reshuffles without leaving the page, so the app narrows the field first and lets chance break the tie.

Design decisions

  • Hero food photography with a dark gradient overlay—sets context immediately without competing with the picker controls
  • Category grid before randomization so "date night" and "fast food" don't pull from the same pool
  • Pick 3 instead of a single result—enough variety to spark a real choice without reopening the decision spiral
  • Cream background, terracotta primary CTA, and sky-blue active states—warm and appetizing without feeling like a generic restaurant directory
  • Pick Again below results for fast reshuffles when all three misses land at once

Outcome

The app turns a recurring "where should we eat?" loop into a thirty-second ritual—filter, pick, go—while keeping the list personal and current instead of relying on generic recommendation engines.

Qualitative assessment for portfolio demonstration—not based on real analytics or client results.

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