Too much data language
The value needed to move from features to business impact: margin, waste, staffing, and revenue visibility.
Back to proof
Karlota.app case study
Restaurant BI: from data product to operator meetings.
KALMA helped frame Karlota’s AI-enabled hospitality data product around margin, speed, and decisions that restaurant operators understand.
Executive summary
- Reframed “data and dashboards” into a margin and efficiency conversation.
- Defined buyer pains for restaurant operators with limited time and attention.
- Built messaging for meetings with decision makers who own performance.
The challenge
“Operators do not buy analytics because it is smart. They buy when it helps them make faster decisions and protect margin.”
Busy decision makers
Restaurant operators have little patience for abstract AI language. Outreach had to be fast, practical, and useful.
Clear meeting reason
The SDR motion needed a simple reason for operators to accept a meeting and see relevance quickly.
KALMA approach
Focused the motion on operators where better visibility could create immediate management value.
Converted BI language into sharper sales messages around decisions, margin, and daily control.
Created outreach built to close a practical conversation, not explain every feature.
Result
A clearer route from AI hospitality product to meetings with restaurant decision makers.