So, I’m actually boarding a train that’s been in motion for a while now.. the practical application of data and analytics in the pursuit to succeed as a competitive gamer (solo or team). I preface this post with a word of caution: I’m not a pro-team coach or analyst! This is based on my observations of how the sport is evolving through data and then how I used this knowledge to provide a little bit of extra value to clients I’ve worked with in the past.
One of the conundrums for those investing into esports, or really any other similar form of influencer driven marketing, is in understanding how this translates to some measurable return on your spend (I avoided the three letter abbreviation that starts with R). Nowhere is this more challenging to measure than through the holy-grail of esports marketing vehicles: social media.
I’ve had some great discussions in the last couple of days and have been trying to look beyond the ambiguous fall-back measurements of reach, engagement and likes. They just don’t say enough about the quality of a user base.
So where does game data come in? The rich data available to those following games like DOTA2, LoL and CSGO allow everyone to analyse past trends of professional games and exploit basic trend analysis to create a handful of likely scenarios. You can then assign probabilities to the likeliness of those scenarios and Team X can then hypothetically be better prepared for Team Y. At least that’s the basic premise.
So if teams can better prepare for opponents utilizing basic trend analysis, why can’t we as businesses analyze social media activity and be better prepared for how to deal with the people we talk to through our channels? So here’s a league of legends parallel: Professional analysts might look at the average time per game that a team goes for an in-game objective, let’s say Nashor. To parallel this with our social media customers, I’d suggest identifying the average time in a customers conversation journey where they unlock a desire to purchase.
To highlight the parallel in more detail:
Team X on average takes an in-game objective like Nashor at 25 minutes in (season long data)
Customer X (this would be a data group) on average has to be involved in 3 conversations before he/she makes a conscious decision to purchase from you
The opportunities to analyze this type of data are endless but most importantly, we’ve then got a social media benchmark of sorts in assessing the value of the users belonging to our social channels. So if Customer X takes 3 conversations to convert to sale while Customer Y takes 10 conversations to convert to sale, we then assess the quality of a platform based on the % of total customer population that belong to X.
Again, this is just one piece of data that can be isolated to better communicate the value of your social media platforms to sponsors, investors, marketeers. Once you understand the segmentation of your social channels (data collection phase), you can then determine what the average number of conversations your social team need to have in order for them to successfully engage with your entire network and what probability there is of those customers making conscious purchases from you.
You can try classifying social customers by their Activity level, Second/third degree influence and by emotional/logical buyer-types just by collecting data from the conversations you’re having on your social channels everyday. You pick the groupings you feel are most valuable to your brand objectives and measure your entire user base in accordance with that meaningful metric.
So if you want people to share a lot of your content then you’ll pick 2nd/3rd degree influence as a metric. You want a % of you followers to be influential people. This now means you can set social media goals based on the metric you choose. For examples sake using the above you’d say : I’d like to make 50% of my Twitter channel have active 2nd/3rd degree connections.
In the above example, when you choose who to sponsor/invest in you can define the metric that’s valuable to you and determine whether the channel is worth the price a brand is asking you to pay to access it. Just seeing a big number isn’t where your value lies, its in what amount of those people fall into the category you deem valuable.
Each of these makes it a great deal easier to evaluate the real value of yours and other social networks beyond just reach, engagement and followers.
I wonder what brands in esports are using to evaluate the social media value of the partners they work with. I’d love to join in on any discussions that people are having around this!