Executive Summary

(if you only have 30 seconds, read this) 

The problem

A leading South African retailer with millions of active customers faced slowing growth and a rise in competition before they reached out to Eighty20 for a solution. They wanted a data-driven strategy to strengthen their position in the market and drive growth.

The Solution

GrowthMap is a data-driven framework designed to unlock sustainable growth for consumer facing businesses, helping them to know where to focus, what to do and how to start.

Our GrowthMap framework provides a comprehensive view of the market landscape, including market size, customer profiles and spending behaviours, and a brand’s imputed share of wallet at an individual customer level. These insights empower our clients with a clear understanding of where growth potential lies and how to achieve it.

As the leading provider of consumer insights, third-party and alternative data in the country, Eighty20 has an accurate understanding of the market – both in terms of characteristics but more importantly, in how valuable a particular audience is to a brand. We then overlay an internal view using first-party data held by the client to define the growth opportunity. This lens gives clients the clearest understanding of who their current customer is, who future customers should be, where value really lies, and the roadmap required to achieve that growth.

The Results

Our intervention turned fragmented insights into a clear, actionable growth plan that would ensure long-term success. We identified how to achieve a R10bn increase in revenue from existing customers and R5bn from new customers over 3 to 5 years.

This roadmap provided clear profiles of existing and ‘not yet’ customer segments where growth could be achieved. We also outlined the targeted value drivers at both a segment and customer level – for example, which customers could be shopping more frequently, which could be increasing their basket sizes or be encouraged to buy up or try new categories and so on. We then suggested strategies to achieve these behaviours and how to track and measure success at a customer level.

Read More Details Below

Our client, a South African retailer, with several million active customers, was experiencing slowing growth and increased competition. Given this challenging context, they wanted to determine a brand, product and customer strategy that would drive sustained growth over the next 3 to 5 years.

Our client already had a single view of known customers but was not leveraging these insights across the organisation to drive strategic priorities. Our team recommended GrowthMap, an innovative, data-led solution designed to unlock measurable business growth. This solution involved 4 steps:

1. External View: How can we grow through acquiring new customers?
2. Internal View: How can we grow by entrenching existing customers?
3. Opportunity View: Identify, size and prioritise key opportunities for growth.
4. Growth Priorities: Execution plan to capture targeted growth.

Please note all values are fictitious, graphs are for demonstration purposes only.

1. External View: Market Overview and Data Enrichment

Market Overview

To gain an understanding of the external and addressable market by segment, we used our Eighty20 National Segmentation (ENS) dataset to map the broader consumer landscape. The ENS fuses and reweights the best data from the most reliable sources to create a comprehensive view of all 43m South African adults.

This process gave us an understanding of how different customer groups behave, spend and engage, especially with ecommerce. With this view of the client’s market, we were able to determine the market size, competitor performance, customer characteristics and observed changes in behaviour over time. Key differences between who our client’s customers are, and who they aren’t were also identified.

ENS Mapping Process

With the appropriate consents, we then used unique identifiers (SA ID, cell number etc.) and mapped each customer to one of our 1,500 ENS microsegments. This process not only enriched the client’s single view of customers with thousands of ENS variables ranging from demographics to retail, financial, digital and media consumption, but also mapped each customer to a robust retail market segmentation.

We used the enriched data to profile both customers and not-yet customers, determine accurate market penetration by customer segment and identify at a high level where the client was performing well or poorly.

2. Internal View: Understanding Value Drivers

We then overlaid internal transactional data to understand how different customers were engaging with the client. Including who their top customers were, what made them different and either more or less loyal.

Value Driver Trees

Value Driver Trees (VDTs) helped identify what was driving sales per segment, category and over time – VDTs break down the value generated into its independent drivers such as frequency, units per basket, price per unit and number of customers per day. This process revealed immediate insights. As an example, although sales were up strongly, they came almost entirely from customer acquisition. Although existing customers were spending more often, their baskets were smaller due to buying down with the notable exception of Heavy Hitters.

Attribution Analysis

Using data science techniques, an attribution analysis uses the VDTs to quantify which combination of value drivers and customer segments are contributing to growth or value erosion. This technique helps to pinpoint the behaviours per customer segment that are needed to drive growth, revealing where to focus.

For example, we saw that acquiring new Mass Market customers was the primary driver of sales growth, while decreases in the average price per unit (APU) of Heavy Hitters and Middle Class Workers was causing value erosion. A reducing APU is an indicator of customers purchasing cheaper alternatives to their traditional items.

3. Opportunity View: Identify, Size and Prioritise Growth Opportunities

The external and internal views provided a detailed understanding of the market and where the pockets of opportunity sat among both existing and ‘not yet’ customers and what behaviours would drive the most value. The Opportunity View then becomes more specific around quantifying the size of the opportunities at both a segment and customer grain, enabling us to prioritise. First, we explored the opportunity among existing customers.

Existing Customers

Because we already knew the microsegment of each customer, we were able to do a look-a-like analysis to determine what a ‘loyal’ customer looked in each microsegment – spend, frequency etc. From this we could then rank every customer in each microsegment to score their level of loyalty or share of wallet.

For example, if we could see that 30% of customers in a microsegment spent at least R250 per month at our client, while the remaining 70% spent less than R250, then we could infer that the maximum spend for that microsegment was R250 (or 100%) and everyone spending less than this had some room to grow. We were also able to identify very loyal customers irrespective of whether they were wealthy and spent R5,000 per month or had less means and were only spending R250 per month.

Overlaying the results from all 1,500 microsegments we were able to see the distribution of loyalty for the client’s entire known customer base. If we then assumed that it was possible to nudge all customers to become slightly more loyal, by increasing frequency, basket or whatever driver was relevant for that customer, we could impute the total revenue that that ‘nudge’ would contribute.

We then looked at the revenue contributions possible by ENS subsegment, split by level of loyalty. This enabled us to identify which subsegments gave rise to 80% of the value – the 80/20 principle applied quite practically.

When considering the size of the opportunity available we considered that low (5%-25%) and medium (25% – 60%) loyal customers are probably easier to nudge than customers that are currently not loyal at all. These insights were used to prioritise specific opportunities, profiling customer interventions that we thought would drive the most value.

Not Yet Customers

By knowing who the client’s customers were, we were able to determine the number, profile and value of customers in the target segments who were not yet customers of our client. To estimate the potential value, we assumed that any acquired customers would exhibit the behaviours of similar profiled low loyal current customers.

4. Growth Priorities: Developing a measurable execution roadmap

By gaining a deeper understanding of our client’s customers and not yet customers, we recommended a strategy to acquire more than R15bn in growth.

Our work uncovered clear opportunities, such as expanding the customer base by specifically targeting Middle Class Workers with value products in key categories, while increasing purchase frequency among Heavy Hitters by emphasizing everyday essentials.

Our detailed profiling provided data-driven recommendations for location-based strategies, product ranging, promotional and pricing strategies, improved customer journeys and hyper-personalisation.

We then used a simple value / ease matrix to prioritise these opportunities in consultation with key stakeholders, developing a clear roadmap to grow revenue. To ensure seamless execution, we refined and aligned these strategies with product, marketing and customer teams.

An Actionable Growth Strategy

Our client started the engagement with fragmented insights, untapped customer data and an unclear strategy. GrowthMap gave them a defined roadmap to target a R15bn growth opportunity.

If you’re looking to unlock similar results in your organisation, let’s talk.

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