As preference data continues to collect, it's imperative that the data is thoughtfully interpreted, and that you and your team are on the same page. Moving from preference management implementation to improvement hinges on defined and applied business rules and what meaningful metrics are used. These metrics may range from "hard," measurable key performance indicators (KPIs) to "soft" KPIs that are oriented around baseline customer expectations and customer interactions.
There are five categories of hard KPIs that can be measured when considering preference management performance. Those include:
- Preventing Loss of Customers
- Reducing Costs
- Boosting Revenues
- Centralizing Preference Collection and Availability
- Mitigate Compliance Risks
In this 12-minute webinar, Eric Holtzclaw walks viewers through the ways to define return on investment and success factors with KPIs. Do any of them ring true to you?
Don't forget to consider those soft KPIs, too. Customer conversions are easy to quantify but customer retention, engagement and lifecycle are about qualified perceptions. However with preference management tools in place, tracking soft KPIs becomes much easier. Customers will select useful or timely communications and opt out of ill-conceived campaigns. In the short term, the data will empower marketers to course correct, reducing churn and improving marketing efficiency. Over the long term, that data will represent an actionable sample size from which to make large-scale marketing decisions.
In the following weeks, we'll continue to roll out videos to guide you through interpreting preference data. If you haven't yet explored our Resource Center, you can download the Interpreting Preference Data whitepaper here.