Treid CX blends all your customer signals and turns them into a per-store score and action plans that get ahead of the drop, not just fix it.
One agency runs the mystery shopping. Another tool measures NPS. Google reviews go unread and shelf photos get lost in a chat. The result: reports that arrive late, don't talk to each other, and don't tell you what to fix.
Each source lives in its own tool and they never talk to each other.
By the time the report lands, the in-store problem already happened.
Plenty of charts, few decisions. The "so what do I do" is missing.
Reviews, shelf execution, complaints, queues: on their own they mean nothing. A single intelligence fuses them into a per-store score. Those signals move weeks before NPS: when they diverge, the owner gets the alert. You don't just fix what already happened: you get there before it does.
With the CX Configurator we define pillars, sub-pillars and questions based on your industry and customer journey.
Field visits, NPS, CSAT, reviews, shelf and context all enter the same platform.
Each source becomes a per-store, per-pillar score, and the AI finds the correlations.
Automatic alerts and action plans that tell each store what to prioritize this week.
Customers don't answer surveys about the shelf: they suffer it. From a single photo of the store floor, computer vision counts facings, detects out-of-stocks and turns what the customer saw into one more signal in the score. We inherited it from Treid-X, the group's trade-marketing operation.
Physical evidence joins surveys, reviews and field data in the per-store score.
A dashboard per client with the experience score, week-over-week evolution, per-pillar performance, alerts and store ranking.
Network view · Week 26, 2026
Network score, evolution and store ranking.
Field visits scored by pillar and sub-pillar.
Voice of customer with trend and correlation.
Google and app stores, with sentiment.
Photos analyzed: display, stock and order.
Critical drops and plans with follow-up.
Pillar and sub-pillar breakdown of the gap.
Build your measurement tree by industry.
The CX Configurator doesn't impose a generic survey. It builds your own tree of pillars, sub-pillars and questions based on your industry and customer journey, and grounds it in recognized customer experience frameworks. Every tree goes through approval before it goes live.
Perfect Store and Voice of Customer usually live in separate tools. Treid CX unites and blends them into one score.
The measurement tree is built by industry and journey, anchored to recognized frameworks. It's not one more survey, it's a defensible system.
Alerts and action plans that get ahead of the drop. Each store knows what to prioritize, not just its score.
Each client sees only its data, with strict platform-level separation. Ready to scale.
Built to run several brands on the same platform, without one seeing another's information. Designed to keep your IT and procurement teams at ease.
Each brand accesses only its own information, with row-level security policies.
Client admin, editors and viewers, each with the right access.
Managed database and continuous deployment, with current security standards.
Four companies covering the full shopper and customer journey: from the point of sale to loyalty, from activation to experience.
Treid CX is the customer experience intelligence platform of Grupo Treid. It blends mystery shopper (field visits), NPS, CSAT, Google and app-store reviews, and AI shelf analysis, and turns them into a per-store score and action plans.
It measures the experience at each store by combining field visits scored by pillar and sub-pillar, NPS, CSAT, digital reviews and computer-vision shelf analysis.
It unites Perfect Store and Voice of Customer into one score, builds the measurement tree tailored by industry with recognized frameworks (SERVQUAL, RATER, NPS, Kano), and delivers early-warning alerts and action plans that arrive before the drop, not just after.
Early signals (reviews, shelf execution, complaints, queues) move weeks before NPS. Treid CX unites them in a single per-store view and alerts the owner when they diverge, so you can act before the indicator drops. On that foundation we're training the models that project each store's score: they activate once your data history allows it.
For retail chains: supermarkets, home improvement, pharmacies, department stores and convenience. It operates in Chile and Peru.
Yes. Each client accesses only its own information, with strict platform-level isolation and role-based access control.
Book a demo and we'll show you how your network looks when every signal talks and you get there before the drop.
30 minutes, online. Pick a time that works for you.
