Data and Analytics in the Retail sector

Retail is becoming an increasingly data rich environment as more of the business goes digital, creating many more data capture opportunities. The challenge for retailers is to capture the right data, process at the right speed and take appropriate action.  

For example, there has been a major shift in consumer purchasing behaviour in recent years. According to Google’s Zero Moment of Truth (ZMOT) research, 70% of consumers research online before purchasing in-store. This behavioural change means analytics have to change - store and digital research data sets have to be connected to produce the real insight needed to understand how consumers research and respond to offers. 

Increasingly retailers are focusing on the total customer experience, the end to end journey. This journey sees the customer moving through the organisation with data being collected at every touch point (store, app, website, contact centre, email etc) in ever greater volumes. 

To improve the holistic experience, leading retailers are creating much fuller and richer single view customer datasets, that capture and process all this data in real-time. This data is used not only for insight but to trigger promotions, marketing activity and alerts. 

How is decision making changing in changing in retail as a result of data and analytics?  View the infographic 

At PwC, we use data and analytics to help organisations in the retail sector to:
  • Develop a 360 degree view of each customer
  • Optimise advertising and promotional spend
  • Deliver personalised promotions in real-time
  • Optimise supply with demand
  • Adjust pricing in real-time to maximise sales and/or increase profit margin
  • Detect fraud

Data and Analytics tools for retail:


Case studies

Boosting store profitability for a UK supermarket chain

Our client wanted to identify which operational activities contribute to store profitability and then build a performance management framework to enable store managers to focus on them.

We used predictive data mining techniques to identify profit generating activity from a 14 system source data set. It covered 5 years, intraday data and 150 attributes.

Our analysis identified the store attributes that actually drive performance, whether performance is defined as sales, profit or any other metric. We designed a tailored performance improvement action plan and quantified the commercial benefit that can be achieved in each store.

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A fit for the future IT strategy for a growing retailer

Our retail client wanted to define a new IT strategy to help support its growth strategy. The IT architecture had been built to serve an outdated sales strategy.

The organisation had large amounts of legacy technology and multiple versions of data held in disparate systems across the business. There was a large amount of IT resource required to support this outdated architecture which had drastically reduced flexibility and scalability of the IT function, impacting its ability to support business expansion.

We worked with our client to create a strategic vision of how data contributed to the operation of the business and how information and data is being used across the organization. This analysis helped the client get a deeper understanding of its system requirements and it applied it to its subsequent vendor selection process.

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Delivering robust reporting and greater business insight for a retail firm

Our client was undertaking a significant transformation programme to achieve a more agile decision making process. Due to limited analytical tools, little data could be integrated and used across functions. Users were unable to gain greater insight into customer trends and purchasing habits as spreadsheets were still used for reporting.

Our team developed a Centre of Excellence which drove insight and value through key performance indicator’s (KPIs), supported by a single and consistent view of the data. This improved trust in the underlying data.

The business was able to develop a self-funding model, with projects creating value for the brands, with both financial and operational measures included. The client was then able to build a continuous stream of information improvements through the application of an agile operating

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Contact us

Oliver Bernath

Partner, Consulting Data Analytics, PwC United Kingdom

Tel: +44 (0)7841 804244

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