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.
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.
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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.
Jack and Samantha represent the traditional and advanced data sharing models respectively. The data shared by Jack with research organizations, is part of a high level data dump across the sector which is analysed and reported every quarter. These reports provide generic insights and come too late in the day for manufacturers and suppliers to tweak their strategies in real-time.
On the other hand, with the help of advanced and secure data sharing tools Samantha shares not just data, but contextual retail insights in real-time, giving the suppliers an edge in demand forecasting, and promotion planning. No guesses here on who is ahead in game!
Highly Targeted Promotions and Improved Promotional ROI
With retailers and their suppliers on the same page getting SKU level visibility, the chances of any product going out of stock is virtually nil. The contextual and relevant insights help suppliers in improving their category share by understanding product, category and shopper demand better.
As a result, shoppers experience much more targeted promotions, sales go up, and retailers and suppliers see higher promotional ROI. By directly influencing demand at the point of action, retailers and suppliers can thus drive sustainable growth.
Ease of Adoption and Quick ROI
The ability to mine data and gain contextual insights is the biggest differentiator in the race to stay competitive in retail. As per CGT-RIS Data Share study 2014, over 54% suppliers receive real-time data from retailers and more than 70% of both retailers and suppliers agree that data sharing has improved their sales and promotions while promoting better dialogue. However sharing raw data dumps doesn’t cut it for most suppliers. They will still need to make sense of the data, using analytical tools.
Suppliers could be more interested in accessing granular, packaged retail insights that are easy to consume. If provided through a centralized platform, and it helps them to increase revenue, why wouldn’t they be willing to pay a small fee to access these insights regularly?
Today SaaS based collaboration and data sharing technologies are easy to acquire and quickly integrated to existing ERPs. Available through subscription models, the technology investment in building retail data sharing capabilities, that lead to easy data monetization, is well within the reach of retailers.
Retail data monetization has proved to be a cash cow for many retailers with a vast majority recovering the cost of the data sharing platform in less than six months!
If you were certain to earn 10 dollars just by investing a dollar, wouldn’t you do it? It’s not a magic pill, just the result of intelligent supplier collaboration.