On May 25, GDPR enforcement arrives. But on that date another piece of digital history occurs. Klout, the social media dashboard will shut down. The shuttering of the well-known platform marks a very big shift in martech — the rising capacity for more precise understanding of social media activity and for improved measurement from social media analytics.
Launched in 2009, Klout was designed to measure activity across social media platform and create a "Klout Score", a numerical value between 1 and 100. The score was derived based on activity data from the user’s social networks. A high score indicated that a user had influence, and was sharable so that people would be encouraged to contact others who had a decent score.
Many marketers and social media users questioned how the score was calculated — how does someone truly know that the engagement was meaningful? But it did provide a way for marketers to understand which platform was offering engagement performance on Pinterest that could impact performance on Facebook. Users could view which percentage of activity influenced the score, even if the percentage was from activity rather than response.
At first, people generally responded well to having a single metric — a score — to assess new followers to their social media account. A single metric made user’s choices seemingly easier when deciding whom to follow or not. The single score perspective appealed to influencers — having a high score allowed influencers to claim they understood Facebook, Twitter, and Google Plus well enough to attract endorsement deals.
Related Article: Why Social Media Is So Addictive (And Why Marketers Should Care)
2018 Brings Changes to Social Media Landscape
Fast forward to 2018 and a radically changed social media landscape. Additional services such as video and chatbots augment social media activity and create new factors that were not fully included in Klout’s calculation. Real world responses to public instances combined with increasing number of fake profiles raised questions if a single score really represented meaningful engagement. These factors ultimately spurred a deeper need to analyze social media influences and revealed the superficial nature of a profile score system.
Moreover, analytics has improved to provide deeper advanced techniques that can attribute the path customers use to with better accuracy. For example, analysts can create a statistical model with R programming or Python to compare Twitter hashtag mentions over a given time period. That comparison can drive a true sentiment analysis to know what campaign around a hashtag was truly effective.
Further, a regression model can be made to compare activity from a social media channel against data from another source, providing further examination if a channel has value. In comparison, many dashboards can only derive clicks and associated activity if a post or tweet has their proprietary URL shortener included. That limits the capability of understanding the true reach and sustainability of a message.
Reliance on a Sole Metric
Platforms still in use should heed Klout’s business tale as a warning about letting a sole metric drive a business decision or an entire business model. A single metric or a tool based on a single metric may seem great for a straight forward simple understanding of how activity is related. But as data sources are added over time, compound metrics that provide a nuanced view and understanding of omnichannels should be developed. Regulation such as GDPR, which places an emphasis on understanding data usage, will ensure that development occurs, probably sooner than what has happened in Klout’s history.
For now, Klout is history. The next social media dashboard will have to incorporate compound metrics more clearly to make history of its own.