RETIVORA was created because store performance cannot be understood from a spreadsheet alone. You need to see what happens to the customer, how the team works, how the store is managed and where sales opportunities are being missed.
RETIVORA is built around real store operations: daily sales, team leadership, KPIs, customer situations and the understanding that the same performance problem can have very different causes in different stores.
If the team does not engage, discover needs or close the sale, traffic alone does not create revenue.
Higher-value products can hide weak basket building, limited additional recommendations or inconsistent sales execution.
We test whether traffic is really the problem or whether existing opportunities are not being converted.
Not every business has a traffic counter, detailed POS reporting or an analytics team. We adapt the method to the data available.
RETIVORA does not separate these two sides. We do not try to solve an operational issue with training, or a sales behaviour issue from a KPI table alone.
We look at the whole store: customer movement, team deployment, missed sales opportunities and what the available numbers show.
We examine how store visitors become transactions and how to build a more natural and consistent sales culture.
We examine engagement, needs discovery, recommendation and closing.
We examine whether the team consistently builds the basket through relevant recommendations and alternatives.
Structured observation and manual sampling can still create a useful baseline.
Smaller retailers often do not have dedicated operations, training or analytics teams. That is why the solution must remain practical and usable.
If automatic traffic counting is unavailable, we can use manual observation during selected periods.
Revenue, transaction count and units sold can already provide useful information.
We translate metrics and findings into clear business language.
We do not force the same template onto every store. First we understand what is really happening; only then do we recommend change.