Commercial teams often use historical data to measure performance, assess progress toward revenue goals, and learn from past experiences with customers or prospects. And while this data provides helpful insight into the past, it can also be an invaluable tool in preparing for the future.
Propensity models allow commercial teams to predict customers’ future actions by looking at their past behaviors and relating those behaviors to internal and external variables. These models inform data-driven sales strategies and improve sales efficiency by giving sales leaders insights that help them:
In this blog, we’ll outline the various types of propensity models, the purpose of a propensity-to-buy model, and common mistakes to avoid as your organization develops or refines its propensity-to-buy model.
A propensity model is a statistical prediction of the likelihood that a prospective or current customer will take a specific action. These predictive behavior models typically use logistic regression or other advanced non-linear machine learning techniques to model the relationship between multiple independent variables and the likelihood of a customer performing a certain action.
Propensity models use a combination of firmographic, technographic, psychographic, and historical data. They can be used to predict nearly any behavior — from engagement on a specific channel to movement across stages of the customer lifecycle.
Propensity modeling offers a repeatable, data-driven way to predict customers’ future behaviors while also identifying the triggers behind those behaviors. Sales teams can use these insights to inform their targeting efforts and strategic plays, like providing relevant product recommendations to speed up decision-making or taking proactive steps to reconcile with clients at risk of churning.
There are several types of propensity models that can be used to predict behaviors among existing customers. Examples include models that measure customers’ likelihood to:
Along with forecasting the behaviors of current customers, these predictive models help sales teams identify which prospective customers are most likely to buy their products and services via the propensity-to-buy model.
A propensity-to-buy model predicts how likely a prospect is to buy your product or service based on characteristics like their location, industry, and size, along with historical performance data from your organization. These historical data points account for variables like your past sales performance in certain markets, the pre-sales interactions that most often lead to closed deals, and how you perform against your competitors.
Propensity-to-buy models are critical in sales territory design and account planning, as they help commercial teams:
Each propensity-to-buy model requires a robust data set and sound statistical analysis to yield accurate results. Along with deciding what to include in your model, you’ll need to train and test your model to ensure it’s accurate before you start using it as a source of strategic insight. Here’s a high-level overview of the steps in the propensity modeling process:
The success of your organization’s propensity modeling efforts hinges on the data you use to develop them and your commercial team’s ability to access and act upon your results.
Our MoneyMap tool provides your organization with proprietary data and advanced analytics capabilities through a single solution, so you can turn data about your customers, prospects, and competitive landscape into predictive models that inform revenue-focused decisions.
We’ll help you develop a custom MoneyMap that measures propensity to buy by product, territory, and customer segment and provide your sales reps with actionable ways to follow up with high-priority accounts. Then, our expert customer success team will partner with you to refresh your insights and propensity model as your needs evolve or the market shifts.
MoneyMap gives your entire commercial team a single source of truth when it comes to account prioritization, sales capacity planning, and other critical sales activities, empowering frontline reps and bringing your organization closer to its growth goals.
MoneyMap enables sales teams to:
Enterprises across the globe use MoneyMap to expand into new markets and realize their revenue goals in the most efficient manner possible.
See how one technology company powered its commercial growth strategy with MoneyMap and used the insights within it to realize ~$600M in total potential upside.