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How playing Football Manager could help you with Marketing

19 January 2022


With Jonathan Van-Tam receiving a knighthood for, among other things, his use of footballing analogies for the workplace, I thought it was time for a story about how Umi Digital used (digital) football to improve our client’s digital advertising.

Everyone has their vices that they try to keep hidden from their friends and family lest they are shunned. For me, two of these are Microsoft Excel and, what is basically “Excel: The Game”, Football Manager.

This particular gaming vice started with me still awake at 2 am finishing ‘just one more match’ on weeknights with stinging eyes and the impending self-loathing that sleep deprivation will give you at work the next day. Over time it has actually evolved into a methodology that we could apply to Umi Digital’s clients and campaigns. My methodology has actually helped us to overcome one of the key issues we encounter when creating client campaigns.

A brief introduction to Football Manager

Football Manager is the sort of game where you get out what you put in. For most people, it was a brief entertainment fling and involved reloading the game whenever they lost a cup final or key game in order to get their beloved Aldershot Town to the Champions League in 5 seasons.

For others, it can be a painstaking chore of meticulously scouring the far-flung reaches of Europe and the wider world to find that 6’4” second coming of Virgil Van Dijk that might just be the missing piece to your 2nd division Portuguese teams delicate counter-pressing system. This is the camp that, over the 2021 edition of lockdown (4 or 5..?) I found myself in. But more on that later.

What does Umi do?

My role within Umi Digital is to ensure the success of biddable. I make sure that paid campaigns deliver on their intended KPIs. The first step in the planning process is to look at forecasts and historical data for specific keywords, platforms or audiences. We then analyse the subsequent data points and come back with a plan that will give the campaign the best chance of success. A problem that this often runs into, however, is finding which solution is the best for a specific hotel or campaign.

Finding value in a mess of numbers

Back to Football manager, Excel and the hypothetical Portuguese team on the hunt for a new centre back. One thing you are never short of in the game is data, and once your scouts have gathered enough information on enough potential players for the position you are looking to fill you need to evaluate each of these options for which will be best.

How quick is the player, are they strong enough, will they have the composure to make a last-ditch tackle without giving away a 94th-minute penalty in a hard-fought 0-0 against the top of the league… The list goes on. With this much information, it is often hard to get to the core of what is important and what is just noise. It is also important to find out which attributes are important to the system as a whole. This is where Excel comes in.

By exporting the bright prospects and their respective skills to an excel spreadsheet you are able to start putting different weightings on attributes and ignoring others altogether to leave you with a final value, I chose to give it between 1 – 20 as this is how the game is broken down, for how good a player is for your system. This allows you to make offers on the top few players in this pile, see who you can get the best deal for, sign them up and then pat yourself on the back for a search well executed.

So how does this apply to the problem of what keywords or audiences to bid on?

As we mentioned earlier when researching keywords and audiences there are a lot of data points that you are given; potential CTR, intent, searches, audience size, demographic data, etc… which we can usually put quantitative numbers on depending on how good, or bad each is. If the CTRs in your potential keywords is between 0.1% and 15% you could use this scale to be between 0 – 10 to get a number that you can then compare with a 0 – 10 scale for search numbers.

Once we have done this for each point we have, we then add weightings to each based on how important it is to the KPI, awareness campaigns will want different attributes to conversion-based campaigns.

Finally, we are left with a list of keywords, audiences or whatever you are working on, with a value between 0 and 10 and you are able to then handpick what you would like to bid on.

What’s the point?

Whilst I wouldn’t expect people to sink 300 hours into a game that is essentially data management without consequences, I do think it paints a nice example that everyone on a team has their own hobbies and passions outside of work that just might be able to help you overcome a problem, regardless of how unconnected they might first seem.

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