Social media can provide marketers with incredible insight on everything from demographics and psychographic data to emotional reactions in real time, essentially serving as a real-time focus group on any topic. This rich data has the potential to greatly enhance our analytics models and can even help predict business outcomes.
Too often, however, marketers focus a lot of time on vanity and engagement metrics that just look at the health and performance of a single marketing channel. For social, marketers’ focus might be on simply bucketing metrics to align to the purchasing funnel, which is a great first step. Rarely, though, do companies look at the holistic picture to find the relationship of different metrics and their impact/relationship to the end business objective.
By going deeper and looking at a variety of data points as a proxy for consumers’ emotional states, marketers can better understand behavior and drive ROI.
Nielsen ratings determine the fate of a TV show. Entertainment firms know this and spend a significant amount of money on social media advertising to promote shows with the hope of increasing ratings. The challenge is that while social platforms are teeming with data and metrics, much of it is noise.
We developed an approach that ingests social media engagement data from multiple platforms. This data is put into a statistical model that predicts TV ratings based on social media engagement. Using these statistical techniques, we demonstrated that an increase in on-platform engagement, from the number of followers to the number of retweets, is in fact a strong leading indicator of ratings. What’s more, we can now weigh each type of engagement relative to its impact on Nielsen ratings. Then we adjust marketing tactics to influence the most important metrics.
In order to exploit the power of social media metrics, marketers must take the following steps. First, hardwire your business objectives to a concise set of KPIs. Next, talk to your data science team early and often to ensure the analytics solution is aligned to the business need. Third, establish a data collection strategy that consolidates data from multiple platforms into a single database. Finally, employ statistical modeling to establish a causal connection between social media metrics and business KPIs.
The days of a one-size-fits-all measurement plan will soon be in our rearview mirror. And that’s a good thing.
Vanity metrics are not enough. The future will be controlled by marketers who are able to merge social data with other data sets to develop a complete picture of business conditions that can maximize ROI.