- Like Post
How can analytics help grocery retailers win in a rapidly-changing market?
Grocery retail under pressure
Over the last few years, the U.S. grocery store market has seen slow growth – a trend that’s expected to continue for some time, with a forecast CAGR of just 0.8% through 2022. Several factors have contributed to this continued low growth, but one of the biggest has been the rise of online grocery shopping (a market expecting a much healthier 6.7% CAGR over the same period).
While the online boom has hit footfall in grocery stores, the big supermarket chains that dominate the market are now also under growing competitive pressure from a variety of sources, including retail giants like Walmart and Costco.
More than most sectors, the grocery market is at the mercy of economic factors that have an enormous impact on profitability – from low margins and falling prices to and high labour costs. Grocers find themselves facing newer challenges as well, from changing consumer behaviours and attitudes, to aging technology that’s struggling to keep up in the digital age.
Alongside the traditional pressures of national and regional chains competing for market share with each other and with independents, new players are disrupting the dynamics of the U.S. grocery market. Discounters are expanding, home-delivery meal kits are getting more popular, dollar stores and pharmacy chains are taking market share, and online retailers are growing their offline presence.
The hidden competitive advantage
Despite all these pressures, traditional grocery retailers have an important hidden advantage in the battle to remain competitive: they’re sitting on a goldmine of customer data.
Grocers already own vast quantities of data on everything from category sales in different locations and demographics to customers’ transaction history, product preferences, and buying patterns.
But it requires advanced analytics to turn all this data into meaningful insights. And it requires human expertise to turn these insights into real-world actions that make a tangible difference to revenue and profitability.
With the right analytics tools, however, grocers can counter the rise of the challenger brands, adapt to changing shopper behaviours, and make the best use of modern technology to increase profitability.
Data + analytics = actionable insights
In our latest white paper, we set out a range of practical applications of data analytics for retailers, including:
- Analytics for customer experience
- Analytics for store size/location and product range
- Analytics for shrinkage reduction
We also share illustrative examples where maximising use of data and advanced analytics has delivered tangible business benefits for our retail clients, plus an analytics success factors checklist to help retailers take the next steps on their data usage journey.
You can also read a detailed case study about how The Smart Cube works with a leading UK retailer as its primary analytics partner.
Nisha is an advanced analytics and consulting professional with over 12 years of experience in retail, CPG and pharmaceuticals. In her current role, Nisha is responsible for managing large analytics accounts, designing and developing data science and analytics solutions for retail and consumer goods. She is an expert in marketing strategy, CRM, measuring promotion and campaign effectiveness, test and learn, forecasting, time series analysis, and driver analysis.
When Nisha isn’t helping clients solve business problems, she can be found reading books, or in the kitchen trying out new recipes. She also enjoys travelling, meeting people of different cultures, and exploring new places.