We all like to be liked. But obsessing over Facebook “likes” and last-click attribution does not a social media marketing strategy make, nor is it any kind of litmus test for customer lifetime value. An eMarketer.com survey stated that 60 percent of marketers used “the number of people linking as friends, followers, or placing ‘likes’” on a brand’s Facebook page as the means of measuring social media marketing success. But according to Moontoast, only 20 percent of marketers found quantifiable ROI from social media. Coincidence? Probably not. Revenue attribution is notoriously hard and last-touch attribution leaves us with an incomplete set of clues.
In “The Importance of Social Activation and Going Beyond Last-Click Attribution,” Marcus Whitney, CEO of Moontoast, explains that these tactics leave a lot of meaning on the table. He instead recommends trying to understand the “social activation” of your customers.
Social activation is a much more thorough way to measure online revenue generation, because it takes a holistic view of social value across brand awareness, user engagement, and the use of multiple touch points. Whitney urges us to step away from “likes” and last-click attribution, and use something he calls the DITE Framework to drive engagement
- Discovery: Draw casual fans through building brand awareness
- Interaction: Create purchase intent with engaging posts
- Transaction: Drive purchases and email subscriptions by offering high customer value
- Endorsement: Facilitate advocacy with clear calls to action and sharing incentives
According to a Facebook / Datalogix study cited by Whitney, campaigns focused on maximizing reach through social activation saw a 70 percent higher ROI than those that only focused on clicks. That’s not to say I think that this is easy. Revenue attribution isn’t easy to track. This is why a two-pronged approach makes sense. Develop an engagement strategy such as the one Whitney outlines. To properly attribute revenue, however, you’ll need to consolidate all of the consumer's behavior and better assess customer lifetime value. Technologies such as machine learning can help you leverage that data across all channels and touchpoints and give you insight about where your revenue is really coming from.