Private equity-backed software company | Analytics & AI

Analysis delivers insight for acting on $1.1 billion cross-selling opportunity

Analysis delivers insight for acting on $1.1 billion cross-selling opportunity

$1.1 billion

potential revenue increase in the first two years through cross-selling—including $788 million in year one

$52 million

potential revenue increase by upgrading existing customers

$71 million

potential customer churn risk identified, enabling action to reduce risk

The Challenge

This company aims to increase revenue to $1.5 billion. To introduce a growth plan, the new CEO had to quickly determine the: 

  • Cross-selling opportunity
  • Potential for upgrading existing customers
  • Risk of customer churn
  • Fastest/best ways to grow revenue

The company has grown via acquisitions, making it nearly impossible to build a growth strategy based on data. That’s where we came in—with a proprietary machine learning platform and capabilities designed specifically for this type of analysis.

Project Timeline

Import, cleanse, and normalize client data
De-dupe and match data to create parent and child accounts for analysis
Ingest data into our analytics platform
Conduct analyses, score accounts and develop reports

An Undeniably Different Approach

In a previous role, the CEO saw firsthand how we create financial value—powered by our proprietary predictive analytics tool, Intellio® Predict, which evaluates revenue streams and predicts growth potential with precision.

Our multidisciplinary team was built specifically for this challenge with deep software industry experience as well as data science and management expertise. The first order of business was preparing for analysis by importing and de-duping 28 million rows of raw data—allowing account-level analytics. 

We used our platform to answer the company’s questions. Our credit-score approach for valuing customers analyzed 30 million combinations of customer and product data points to produce 7.74 million scores for 70,000 customers, including 96 cross-selling scores per customer. Each customer also received scores reflecting upgrade potential and churn risk. 

The detailed output:

  • 17 metrics produced from company data
  • Analyses of retention, annual recurring revenue, lifetime revenue, and average selling price
  • Product recommendations for each customer
  • Probability of cross-selling success and expected value for each customer-product combination
  • Prioritized list of customer-product family combinations, with potential value if sold
  • Prioritized list of contracts up for renewal to reduce churn rate
  • Because our platform includes established predictive models and tools, we delivered all of this in just weeks.

Real Results

This software company now has insight for building value in ways that competitors cannot. It can see where cross-selling white space exists and develop strategies to capture it. Our analysis showed that the best cross-selling opportunities exist in three of five business units, and 20% of customer/product family combinations are responsible for 81% of potential cross-selling value. That means the company can make more data-driven decisions and arm salespeople with specific lists of who to call and what to sell. It also now can establish clear accountability for growth targets.  

Additionally, the company knows where to act to maximize upgrade potential and reduce churn. For example, 91% of churn risk resides in 20% of customer/product families—allowing teams to focus retention efforts more precisely. 

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