Circle Insights

How Transactional Spend Data transforms business operations

Valentins Kirillovs


When one of the UK’s largest supermarket chains needed to understand consumer shopping behaviours at a local level to enhance their relevance within existing and new stores, they quickly realised the impact that leveraging customer-centric data could have on achieving these goals.

CACI was selected as their partner to supply them with the consultancy and consumer behaviour data that they felt had been missing from their current data sources. The potential to gain a granular and cohesive perspective of customers with actionable insights to drive change was what encouraged the business to trust CACI to help reach their strategic objectives and better understand and cater to customers.


  • While the business was equipped with some customer-oriented data to begin with, particularly comprehensive loyalty card data and competitor locations, they lacked the granular detail of industry datasets that CACI could supply. These datasets would bolster their understanding of customers beyond the organisation and would facilitate a new, optimal customer experience journey.
  • The external data about customer behaviour outside their organisation which they could access was generally based on small sample surveys and was not robust enough to support their enhanced customer understanding initiatives.
  • Other data sources were overly aggregated, challenging the business’ ability to determine what the result of a major market change in a market might be, such as a store closing or a new store opening, or a major local marketing campaign. This also made understanding how consumer behaviours changed as a result more difficult.


CACI’s data was game-changing for this business as it was based on actual spend data, and what consumers were actually doing versus what they were saying they were doing. The huge and granular sample size in comparison was also tremendously beneficial for the business, as it was available at brand level, ultimately unlocking major potential for them.


CACI’s consultancy and data was able to significantly enhance the current capabilities of the team and allow them to add a significant new dimension to a number of different projects and use cases.

Potential partner analysis

The ‘race for space’ in the early to mid 2000s, combined with the emergence of multi-channel trading and stronger discounter competition, meant that many supermarket operators have been left with stores that are too big for their catchments and, therefore, were not as efficient or profitable as they once were. As a result, many supermarkets had to find ways to fill parts of their stores or car parks with partner retailers that would generate rental income, fill ‘baggy’ space, create a more comprehensive customer offers and help generate sales for the business by bringing in a different type of customer.

CACI’s data helped this business strategically plan for which partners to approach with a data-driven strategy to help those potential partners understand why a particular store or catchment would be suited to their brand.

Understanding competitor performance

Through CACI’s data, they could begin to understand and benchmark performance between their brand and others in a granular way for the first time, rather than using data based on a small sample survey (Kantar) or that aggregated to market rather than retailer (IGD).

Transactional Spend Data helped this business understand competitor performance in detail at local level by analysing trends in market share, transaction numbers and Average Transaction Values.

For example, before a new store opening, the performance of competing brands and what types of customers were shopping with them could be analysed in a way that has never been previously available. They could also understand what happened once the new store opened – which brands won and lost in the market and which types of customers changed their behaviour. This understanding was key to influencing future new store opening decisions that the team could into future forecasting estimates and set expectations accordingly through data-backed evidence.

Defining missed sales opportunities

CACI’s data helped this business understand where customers were cross-shopping with their competitors on the same day as shopping with them.

One example was by analysing customers driving out of the business’ store and past their petrol station but filling up their car at an alternative fuel station on the same day. The business lost trade because the customer drove past the front of the petrol station and chose to buy petrol elsewhere. While it did not necessarily answer ‘why’ a customer did not shop with the business, it did help generate questions and what to look out for in customers’ preferred shopping experiences so they could assess a particular store, determine which competitors were in the vicinity and what the business could do to compete– adjust the price, revisit the convenience of the store’s location and so on to drive improvements backed by data.

Another example was assessing the performance of one store in close proximity to a direct competitor’s smaller store. The business knew that they had been losing trade to this competitor for years, but they did not have the data to prove this loss.

CACI’s data was the solution— it quantified the number of shoppers visiting the business and its competitor on the same day and their respective transaction values.

This insight helped the business formulate strategies for marketing campaigns that would encourage shoppers to return to their store versus to their neighbouring competitor.

Format development

The business assessed quirks in catchments and emerging trends among competitors to conclude whether certain initiatives, such as creating a café space within a store, would be a success with their customers.

CACI’s data helped them define the demand for distinct types of café space initiatives by understanding the likely demand for the various types of Food-to-Go offers in the catchments of the stores.

Ultimately, it provided the business with a different approach to the café format and its offers for customers.

Customer profiles

For this business, customer loyalty cards were paramount to building customer profiles of their own customers. However, understanding the profile of competitors’ customers and how they were behaving was out of reach. This data helped the business understand the profiles of other brands’ customers and how similar or dissimilar they were to their own customers. Most importantly, they gained insight into what their spending patterns and behaviours were and how they changed over time.

To learn more about how CACI can help you leverage data to enhance your business operations, contact us today.

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Valentins Kirillovs