At the 2016 ASAE Annual Meeting & Expo, Gwen Fortune-Blakely (Enterprise-wide Marketing Director) and Leslie Katz ( Marketing Director) with the American Speech-Language-Hearing Association (ASHA) presented an amazing session on how ASHA is using propensity modeling to move people up the continuum of engagement to drive revenue and membership. Here’s a quick overview of what you need to know about propensity modeling and how it can help your association.

What is Propensity Modeling?

Propensity Models look at past behaviors in order to make predictions about your customers.

It is complementary to segmentation, but different. When segmenting, you cluster customers based on shared traits or behaviors. In marketing, propensity modeling goes a step beyond segmentation by focusing on likely behavior or action. Where segmentation provides insight into customer behavior, propensity modeling provides foresight. It allows you to target customers based on likely behavior as opposed to past behavior.

There are three main types of models: propensity to buy, propensity to churn, and propensity to unsubscribe.

  1. Propensity to Buy model looks at customers who are ready to purchase and those who need a little more incentive in order to complete the purchase.
  2. Propensity to Churn model looks for your at-risk customers.
  3. Propensity to Unsubscribe model looks for those customers who have been over-saturated by your marketing efforts and are on the verge of unsubscribing.

How can Propensity Modeling help your Association?

Think about an association that is about to send membership renewal notices. In the past, they send out a packet of materials by mail to all current members. The packet includes an invoice and an expensive, professionally designed brochure that espouses the value of membership. The association’s retention rate is about 86%, which is respectable but what would happen if the association applied a propensity model to better understand their customers?

  1. Increase Revenue. A propensity to churn model would “score” current members and could help identify those members who are at risk. The association staff can use that information to create customer campaigns for at-risk members. This might include in-person visits or phone calls and other personal touchpoints that would help secure renewal.
  2. Decrease Expenses. Propensity modeling also helps associations determine who to target and how, which can help reduce expenses. In this case, the staff might use the model to identify those members who don’t require a brochure and would simply renew after receiving an invoice. Similarly, a propensity model can identify those customers who need extra attention. It may not be cost-effective to have staff call every member, but what if staff knew which members would likely respond best to a personal phone call?

You can imagine other examples where a propensity model can help your association. For example, associations can use propensity modeling to facilitate market penetration by identifying customers most likely to buy. Or you can use propensity modeling to anticipate how much a customer is likely to spend. This can help determine pricing and product offers.

We often draw inspiration from the corporate world. MasterCard Advisors shared an interesting white paper on how you can use behavioral scoring to add precision to targeted marketing.

How do you get started?

5 step process

At Association Analytics, we follow a five-step process for data analytics, including propensity modeling.

  1. Scope. Define your business objectives and prioritize them. We recommend starting small and focusing on developing a model for one specific objective first. This will keep you from becoming overwhelmed. When you try to fix everything, you normally will end up fixing nothing.
  2. Collect. Spend time with your data before doing any modeling. Inventory your data sources and make sure you understand how data sources will help you answer your questions. Then, integrate data into a central location. We recommend a data warehouse and dimensional data models, but you can directly connect data sources to a business intelligence tool like Tableau.
  3. Clean. Don’t spend time on your model before making sure you have clean, complete data. Be sure to identify data anomalies and then correct any issues.
  4. Analyze. Visualize your data to understand likely behaviors in your model. Don’t get trapped by confirmation bias. Keep an open mind and be open to new patterns or information.
  5. Communicate and Take Action. Share the results of your propensity model with key stakeholders. Take action on the results to improve your marketing efforts and advance your association’s mission.

Propensity Modelling can be a valuable tool in order to better understand your customers and to predict their behavior. It can help you improve their experience with your association.