I watched Social Media Week in Toronto vicariously; though it was literally next door to my hotel, my schedule didn’t permit me to attend live. However, I did check in on the various talks of the day. One key ingredient I saw missing from the event, save for comments by Sysomos SVP Amber Naslund, was measurement.
The Current State of Social Media Measurement
Today’s social media measurement squarely falls in the category of diagnostic analytics. Diagnostic analytics tell us what happened. What trended, what was the popular hashtag, who was influential, etc. – that’s what measurement is today. Sometimes it’s ad hoc, with tools like Sysomos MAP, and other times it’s real-time streaming, with tools like Zignal Labs. These tools achieve the goal of explaining what’s happened in our social media marketing efforts.
The Near Future of Social Media Measurement
“What happened?” is an important question to answer. However, for social media marketers, what’s going to happen is a far more important question. Consider all the “viral” sensations online, from Gangnam Style to Chewbacca Masks, from politically charged tweets to bad lip reading.
What if you were a marketer who could trendspot? What if you knew which trains to hitch your caboose to? What if you could know what the hits were before they happened?
Would you have reached out to Psy to offer a sponsorship and product placement in the Gangnam Style video? Would you have asked a politician to do an account takeover?
The next, short-term evolution of social media measurement is predictive analytics.
With machine learning, with advanced algorithms, we will detect trends as they start. We will know before others what’s going to take off, and can make strategic decisions based on that information.
The Long Term Future of Social Media Measurement
After predictive analytics comes prescriptive analytics. Our artificially intelligent social media platforms will suggest to us what to do. This is different than what we have today; today, some software gives recommendations based on past patterns. My favorite social media scheduling tool, Buffer, uses past patterns of user behavior to suggest days and times, for example, to post.
Prescriptive analytics will go far beyond this. Prescriptive analytics will suggest topics, keywords, images, and rich media based on our predictive algorithms and identified trends/anomalies, and perhaps even prepare our updates for us.
Are We There Yet?
No, kids. Play some VR games. Let the self-driving car do its job of driving us and stop asking it if we’re there yet.
In all seriousness, I believe we’re perhaps a year or two away from the shorter-term predictive analytics, and perhaps 3-5 years from prescriptive analytics. That’s a conservative guess; I did not predict well what’s happened in artificial intelligence in the last couple of years and how much is available even to the individual developer.
What should you be doing while we wait for the future to arrive? Grow beyond competent to outstanding at today’s analytics. Tomorrow’s analytics capabilities will be built on today’s clean, correct, well-chosen data. The better you are at the social media analytics of today, the better prepared you will be for the social media analytics of tomorrow.
You might also enjoy:
- What Is The Difference Between Analysis and Insight?
- AI for Marketers, Third Edition, Available Now!
- How To Set Your Consulting Billing Rates and Fees
- You Ask, I Answer: Best Language for Marketing Data Science, R or Python?
- Why I Stopped Curating Content on LinkedIn
Want to read more like this from Christopher Penn? Get updates here:
Get your copy of AI For Marketers