From Local Routes to Smarter Growth

We started by centralizing the scattered data. POS records, distributor route logs, and order histories were pulled into a single analytical environment. The first challenge was data quality — route identifiers were inconsistent across distributors, and product codes didn't always match between order systems and the master catalog. We spent the first phase cleaning and standardizing these records before any analysis could begin.

Once we had clean data, we built dashboards for sales leadership organized around three views: route performance (revenue trends, visit frequency, basket composition per route), territory coverage (gaps between assigned stops and actual visits), and product penetration (which SKUs were in which store types, and where white space existed). Each view drilled down from region to route to individual retailer.

The basket analysis was particularly revealing. We segmented stores by type (convenience, grocery, traditional market) and geography, then compared basket composition across similar stores to identify where specific products were underrepresented. This gave the sales team a concrete call-to-action for each route visit: not just 'sell more,' but 'this store type in this region typically carries these 3 SKUs that your accounts are missing.' We also tracked visit frequency against order volume to identify routes where more frequent visits could unlock dormant demand versus routes that were already at saturation.

The dashboard design prioritized actionability over comprehensiveness. Route managers saw their 5 biggest opportunities each week — ranked by estimated revenue potential — rather than a wall of charts. Each opportunity came with specific context: which stores, which products, and what comparable stores in the same segment were doing.