4 ways data analytics can transform the retail sector

4 ways data analytics can transform the retail sector

The retail sector in Kenya is projected to be among the greatest contributors to the Gross domestic product in Kenya by 2030. However, over recent years the percentage of GDP contribution from the sector has been declining steadily. Two of the major retailers in the country have run out of business within 2 years. Though the entrance of international brands into the Kenyan retail market has greatly improved competition within the sector, it may, however, eliminate some of the local brands. This article aims to show how data analytics creates a competitive advantage within the retail sector

How is data analytics transforming the retail sector?

  1. Customer Acquisition and retention: Data analytics is helping retail stores answer the following questions;
  • Who are our customers?
  • What do our customers want or like?
  • When and Which mode of delivery do our customers prefer.

By clearly understanding customer behaviors a retail store is able to acquire and retain customers. Thorough customer data analytics enables the retailer to make personalized recommendations, give relevant offers and use customer feedback to improve customer experience.

  1. Sales boosting: Insights of next sell, upsell and cross-sell opportunities determine which promotions to offer to different customers. By personalizing the shopping of repeat buyers, a retailer will definitely increase the sales volume.
  1. Inventory management: This ranges from the positioning of products on shelves to re-order and restocking of goods in the stores. Data analytics gives insights on the impact of repositioning of goods on the shelves, real-time stock situation and sales fluctuations.
  1. Customer Experience: Data analytics helps create an appealing and attractive store layout, online websites and offers customers personalized experiences. Sentiment analysis of social media streams and customer feedback gives important insights on various retail products and services for decision making.

Here are some case studies of retail stores that have embraced data and analytics

1. Netflix vs Blockbuster

Netflix is a media services provider and production company founded in 1997. It started as a video rental-by- mail service provider at a time when Blockbuster had dominated the industry with over 2800 stores around the world. Blockbuster was a brick-and-mortar store while Netflix concentrated on an online platform. However, Blockbuster filed for bankruptcy in 2010 whereas Netflix’s subscribers have risen to over 151 million.

2. How did Netflix outplay Blockbuster?

One of the major reasons why Netflix succeeded over Blockbuster was customer focus and the ability to adapt to change. While Blockbuster was charging late unnecessary fees to its customers, Netflix offered subscriptions to its customers enabling them to watch a video as long as they wanted. This attracted the customers who were annoyed by the late fees charged by Blockbuster. Netflix further increased the ease of access to the videos.

3. How Netflix is using data analytics for growth.

The brand creates a detailed portfolio of its subscribers using data points collected from the customer’s interaction and response to its services. The portfolio is analyzed to discover customer behavior and patterns. These insights are used to customize marketing and make personalized recommendations to each subscriber. The customer feedback program through thumps up vs thumbs down on a particular TV show has significantly increased engagement with consumers.

How has Netflix benefited from consumer data analysis?

  • 75% of Netflix’s viewer activity is based on personalized recommendations.
  • The brand is earning over a billion in customer retention since the recommendation system accounts for over 80% of the content streamed.
  • An impressive 93% customer retention.

4. Amazon vs Toys r us

Amazon Inc. is a multinational technology company that focuses on e-commerce, cloud computing digital streaming and artificial intelligence.  Toys r us was one of the largest children’s toys retailer in the USA, founded in 1948 but filed for bankruptcy in 2018. Despite having market dominance over a long period of time the brick-and-mortar retailer faced stiff competition from online vendors like Amazon which forced her out of business.

How did Toy r us lose to Amazon?

The company didn’t develop its online platform during its 10-year partnership with Amazon thus since most consumers were adopting online shopping, it lost the majority of its clients. Amazon had also included other competitors in its toy retail sector.

Having lost the competition in technology Toys r us began competing on price alone. This approach failed since in a competitive environment there will always be a cheaper alternative. Thus failure to adapt to changing business environments and customer’s preferences greatly contributed to the downfall.

What is Amazon doing to remain competitive?

Through its site, Amazon collets information on how its clients interact with the various elements of the site which processes to improve site performance. It further uses predictive analytics for targeted marketing and personalized recommendations to improve customer satisfaction and loyalty.

Can data analytics save the slowly dying retail sector in Kenya?

Nakumatt and Uchumi supermarkets case study

Despite having dominated the Kenyan retail market for many years, the retail giants were faced with numerous challenges and forced to quit. One of the main reasons was the massive debts they incurred after failing to pay their creditors and suppliers.

Could data analytics have saved the situation?

Data analytics could have been applied to;

  1. Monitor whether products are meeting sales target
  2. Monitor real-time stock situation
  3. Make predictions of future stock orders on certain products.
  4. Monitor sales revenue and make comparisons to costs on stock at specified periods of time
  5. Inform management of any irregularities in finance management.

With the above applications, the retail giants could have survived.


Over recent years, data analytics has proven to be a powerful game-changer in the retail sector. Retailers who have embraced the role that analytics play in customer segmentation, product recommendation, internal operations, and market analysis have gained a competitive advantage over competitors. In Kenya, though majority of the retailers are yet to fully integrate analytics into their operations, the field proves to be significant for most competitive markets. Attracting customer loyalty trust and satisfaction has been a core component for almost all successful brands. This can be achieved through adequate customer data analytics.


  1. Study on Kenya's retail sector prompt payment.


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