The majority of sales generated in the 4.5 trillion dollar US retail market is in-store and the volume of transaction data collected at various points in the trading process is immense. This data is a treasure trove of customer insight as well as product performance. While many retailers mine this data to gain specific insights into understanding their shoppers better, the possibilities that such data analysis opens up is largely untapped.
In an ultra competitive market, retailers can generate an additional revenue stream with proper data monetization techniques.
By sharing the data that otherwise sits idle in their internal systems, retailers can pave the way to a collaborative approach to sustain shopper demand while generating sizeable revenue regularly.
Real-time Granular Data Sharing for Actionable Insights
Jack Hoe, manages the data at a high end supermarket chain. Every quarter he religiously downloads terabytes of retail trade data in reams of excel sheets and shares those with a syndicated data firm. He believes this not only makes him earn a wee bit from an otherwise data dump but also helps build a better informed retail scenario.
Samantha, his counterpart from another major supermarket store has a different approach. She too shares the high volume data, but not with the syndicate. She shares it directly with the suppliers almost real time. Suppliers are willing to pay a fee for packaged insights, since it helps them act quickly and boost category share. She has not only built a steady revenue stream from data sharing, the promotions her stores run and stocks that they manage result in a better shopper experience.