The Last Mile of Frontline CX
Your location managers are in business for your customers — not for dashboard mining. Without data analyst training or hours to spare, hunting for the one high-value action item each week feels nearly impossible.
Part of the problem is that most insights aren't specific enough to act on. "Food quality" or "cleanliness" names a category, not a task. "Orders are coming out cold on weekday afternoons" tells the manager exactly what to fix. That gap — between a metric and a move — is where a lot of CX value quietly leaks out. But what if your location manager had a data scientist in their pocket? This is where Frontline Recommended Actions comes in.
What Frontline Recommended Actions does
It reads across your experience and operational data and surfaces a short list of hyper-specific, plain-language insights for each location — written for the person who can actually act on them.
- Specific, not generic. Instead of "improve satisfaction," teams see the precise issue, for their location, in words they can act on today.
- Prioritized by impact. It focuses attention on the issues most likely to move what matters for that location — so limited time goes to the few things that count, not the loudest thing on a chart.
- Where your teams already work. Insights appear where your teams already spend their time, whether that’s Location Experience Hub or their go-to dashboard.
- Tuned to your business. Because it draws on your own experience data and models, the insights reflect your brands, formats, and context — not a one-size template.
Who it's for
Multi-location CX businesses where frontline and location managers — and the regional leaders above them — need to turn customer feedback into specific action, fast.
It's in Early Access
Frontline Recommended Actions is open to a small group of customers first, so that we can adapt it to real frontline workflows before broad availability. Please reach out to us if you have frontline locations for your business, and are currently a CX Locations customer, and are interested in joining EA!
Where does the gap between a metric and a move show up most in your program — what’s a category-level number you wish you could turn into an actual task? Comment yours and let’s figure it out together
