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Retail analytics and the battle for the shopping basket

This is a contributed piece by Sanjeev Sularia, CEO and Co-founder of Intelligence Node


Big data and the way it is analyzed is not only changing the way we shop for groceries, but the supermarket landscape in general – and a clash of the titans is set to ensue.

Today it seems everyone wants a bit of our grocery spend pie. Suddenly we have an array of places to shop for food and essentials, from cut-price grocery chains, dollar stores and online. Once we were inundated with coupons, now thanks to data analytics we’ve got targeted offers. The Kroger supermarket chain, for example, has been mining data for a long time to push the right offers into the right hands by analyzing billions of shopping trips.

At the same time the discounted price model is growing, and one that shoppers in Europe have been quick to adopt. One name not to be underestimated in the US market is Aldi. The German chain is a control label retail operator selling mostly privately branded versions of established American brands. Aldi has 1,400 stores in the US, with a Southern Carolina branch to open next. A further 45 stores are planned for the region. Aldi plans 600 plus new stores inside two years, while rival Lidl has quietly amassed 1,350 stores in the US, with plans to take this to 2,000 by 2018. Kroger, by comparison, has 2,600 stores across 34 states.

The quick march of Aldi and Lidl is expected to affect traditional supermarket operators Kroger, Safeway and Giant as well as Walmart and Target. Both the German stores are making pricing the very cornerstone of their strategies, offering low prices across the board.

Up until now the $1 trillion grocery market in the US has remained pretty much regional and splintered, despite some consolidation. This has protected it from the shake up the UK market has gone through. But this may be about to change.

Both Aldi and Lidl buy in huge volumes. Reduced costs are then passed on to the shoppers who can save between 20% and 40% on most products. Enhanced data analytics enable the retailers to make snappy business decisions, improving customer satisfaction and the customer experience.

Analysts already believe Aldi will put the cat amongst the pigeons in South Carolina. Pacific Northwest chain is busy rebranding, whilst Wal-Mart and Target are expanding their grocery aisles. Safeway and Albertsons recently merged to get a competitive edge. At the same time Google and Amazon are tagging grocery delivery for expansion.

Aldi’s arrival will trigger “a pronounced price war” in the region, said Burt Flickinger III, managing director of consulting firm Strategic Resource Group. “Aldi has been Wal-Mart’s worst nightmare. It will be tough on Costco as well as all the established food retailers.”


Small, no frills – only technology

The likes of Aldi and Lidl have also made savings on reducing floor space. Their stores are usually around 10,000 to 15,000 square feet, compared with a hypermarket 20 times that size. While coming down in store size reduces costs, investing in megascale distribution centers helps in achieving economies of scale.    

At the same time, they are exploiting business intelligence to make sure they commandeer the shopper’s basket. Good data analytics can tell you what the others are charging, thereby enabling on-the-fly decisions. Robust data technology enables a supermarket to optimize for increased demand, such as Thanks Giving, for example, trends, promotions and regional behavior.

Volume, pricing and revenue goals with automated price adjustments can also be factored in. Brands and retailers have access to historic price and visibility fluctuations of individual items to enable better decision making, whilst being able to offer highly personalized price-sensitive recommendations to shoppers to win their loyalty.


The power of data mining

Business software can also proactively recommend products based on previous purchases, both online and in-store, but can also unlock and apply desired store-level or category-level discounts, as well as those Amazon-style, ‘If you bought this, you might be interested in this’ type recommendations in real time.

Macy’s, for example, has been using ‘Big Data’ analytics to implement customer-centric retail strategies to achieve higher customer engagement, retention and wallet share. Its site, mines through tens of millions of terabytes of data daily in a bid to better understand the customer and their purchasing patterns.

Take, a new name on the block, which already ranks as number four in the marketplace on sales volume, making it larger than Sears, despite only launching last summer. It has achieved such success so quickly by utilizing ‘smart cart pricing’ which intelligently unlocks recommendations and discounts based on a customer’s purchasing and browsing history linked to the brands that give the highest margins.

A prominent feature is a real time pricing algorithm. Customers are being wooed by Jet’s ‘smart cart’ feature which helps them find additional savings when filling their online cart. Items are priced based on their location in distribution centers. For example, if a shopper wants to buy two items from the same distribution center, the price is discounted.


The next step for the grocery industry

Price optimization software is going to be an important tool in the bloody battle that is set to commence in the grocery industry. It isn’t all about being the cheapest on the shelf. Advanced software can monitor customer demand, measure how a price is perceived by the customer and relative to other retailers. This powerful knowledge enables retailers to optimize prices and promotions to their advantage.

Grocery retailers have never been on the leading edge of technology, but this is changing fast as they appreciate the market lead it can give them. They have taken the first step and mined their big data to make themselves smarter. The next step will be to use advanced data analytics to be more proactive and provide customers with a personalized service.


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