Making the case for marketing automation - Keeping better score
April 24, 2018Whether a prospect or customer is opening an email, visiting a landing page, filling out a form, attending an event, or logging into a webinar, that behavior matters. It tells you something. It opens a window of insight into what interests a person and how best way is to engage them in the future. But each action by itself is only a small detail in a larger picture. With marketing automation, you can assign each of these behaviors a numeric value that represents their level of interest. You begin to develop a more comprehensive, higher resolution picture that helps you understand the customer’s motivations and interests. When the customer’s activity reaches a specific threshold, the platform will pass their information to sales as a marketing qualified lead. Sales can see which activity the customer has performed and which content they’ve consumed – and they can tailor the conversations accordingly. The result is a richer, more relevant engagement that is more likely to lead to a successful outcome.
Most marketers who do this kind of scoring will tell you that they see a measurable lift in the quality of leads and resulting close rates. The insights generated can be especially helpful in markets with longer, more complex sales cycles that require ongoing contacts with multiple levels and decision makers in the prospect’s enterprise.
Creating this type of engagement cycle isn’t easy, and a scoring model by itself isn’t enough. It requires a lot of lead nurturing and skilled database marketing. In other words, you still need all the campaign components and content that you’re probably developing anyway. The lead tracking and scoring capabilities help you make smarter use of those resources.
Most marketers know that it’s fairly easy to do scoring based on demographic data. But marketing automation systems can help you up your game and score on behavioral data as well. You can assign weights to those activities you know indicate a higher quality of lead and a later point in the decision cycle. One commonly used benchmark is to assign scores that are roughly 30% demographic and 70% behavioral. However, you’ll want to work with your BI expert to help you assign values to the actual behavioral drivers that lead to revenue. Best guesses and intuition aren’t reliable guides. You need the actual data modeling to zero in on the high value content and actions that provide insight into motivations and intent.
The days of spray-and-pray marketing are over. The stakes are too high, the competition is too nimble, and budgets are too tight. Armed with data-driven tactics like lead scoring, marketers can be more precise and focus their limited resources to generate maximum impact.