y connects store performance data, customer voice, competitor intelligence, and market research into one clear picture. So you can finally answer why.
Most tools show you numbers. y connects the dots: your store data, what customers are saying online, what competitors are doing, and what research says works. Then it tells you what to do about it.
AI is one of our tools — not the whole story. We combine sensor data, web monitoring, NLP analysis, curated research, and EU-wide datasets into actionable intelligence.
Every insight is built from multiple data sources, cross-referenced and verified.
These aren't hypotheticals. These are the numbers keeping retail leaders awake.
Annual retail shrinkage in the US alone. Organized retail crime up 26.5% year-over-year.
Of front-line retail employees plan to leave within 6 months. Hiring costs spiral.
Of consumers abandon a purchase if forced to queue more than 5 minutes.
Of unhappy customers never complain. They just leave and never return. Silent churn.
y doesn't just show you data. It cross-references all sources — then tells you what to do about it.
Conversion dropped 8%? y checks queue wait times, cross-references staffing levels, finds that checkout #3 was unstaffed, and cites research showing >15min waits cause 18% conversion loss.
y monitors competitor websites with change detection. When a rival launches a promotion, changes pricing, or redesigns their page, you know within hours — with a change score and strategic analysis.
Which display gets attention? Which zone has traffic but people walk right through? y tracks every area — who enters, how long they stay, what catches their eye — per floor, per zone, per hour.
Was last month's traffic dip your problem, or the whole market? y overlays EU-wide economic data — consumer confidence, retail spending, e-commerce shifts across 30+ countries. Your numbers in context.
Before you open your laptop: yesterday's traffic, conversion, revenue. Which stores hit targets. Which didn't and why. New reviews with sentiment. Weather-adjusted forecasts. Staffing recommendations.
When y recommends a change, it cites sources. The knowledge base contains thousands of research documents across 8 categories — from shrinkage prevention to omnichannel strategy.
y adapts to your vertical, your role, and your language.
Track queue times by service type, predict peak load, recommend staffing — while monitoring competitor promos.
Identify zones with high traffic but low dwell time. Find displays that aren't being noticed.
Correlate checkout queues with abandonment, track peak patterns, benchmark conversion against research.
Compare traffic, transactions, dwell time, and NPS to identify advisory vs. full-service branches.
Cross-reference traffic, conversion, reviews, and market data to explain why a store is underperforming.
Flag unusual short-visit spikes, browsing-to-purchase ratio changes, and time patterns preceding theft.
Real structure, anonymized data. Every client gets this every week — automatically.
| # | Store | Visits | Share | WoW | YoY |
|---|---|---|---|---|---|
| 1 | OC Galleria | 4,180 | 37.0% | −8.5% | +3.1% |
| 2 | City Park | 3,020 | 26.8% | −16.2% | −1.4% |
| 3 | Central Square | 1,890 | 16.7% | −11.0% | +5.8% |
| 4 | Riverside | 1,240 | 11.0% | −14.3% | +1.2% |
| 5 | Market Hall | 954 | 8.5% | −9.1% | −3.0% |
Peak: 15:00–17:00 (38% of all visits). Afternoon peak typical for mall-based fashion retail.
| Region | Stores | Visits | Share |
|---|---|---|---|
| Capital | 2 (Galleria, City Park) | 7,200 | 63.8% |
| West | 2 (Central Sq., Riverside) | 3,130 | 27.7% |
| East | 1 (Market Hall) | 954 | 8.5% |
Regular January week. End-of-season winter sales winding down. No holidays or special events. Cold start (−4°C) warming toward weekend (+4°C) — weekend warmth correlates with +80% visit uplift vs. weekday average.
This is a preview. The full report includes data sources, detailed diagnostics, competitor alerts, and customer review analysis.
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y is in early access. We're onboarding retail teams who want to be first to have a platform that actually knows their stores.