How Does Team Performance Affect How Fans Spend At The Match?

As a QPR fan, I’m used to inconsistency. Although my match day routine is largely the same, the result invariably effects the minor details of my day, from my general mood to the locations I spend my time in. For example, if we win or draw I’ll head to The Springbok on South Africa Road for the atmosphere whereas it might be The Colton Arms when we (often) lose because of the outdoor space and the food.

Anyway, my point is that my evening is defined by the result: what bars I go to, what I drink and how I act - and I’d bet most sports fans are the same. The last-minute drop goal or penalty heartbreak is going to change a lot about the fan experience, and this was highlighted to us recently when analysing data from an Elite League Ice Hockey team’s matches.

LiveStyled’s nerdy intrigue for all things data was stirred when we found out that app revenue at ice hockey games last season was over 20% higher in games where the home team lost.

The graph above demonstrates the consistently higher revenue taken on the app in games where the home team is losing. We’d expected to see the opposite, with fans spending more when their team was winning and were presumably happier, so a 20% revenue uplift definitely surprised us.

Now, before we get ahead of ourselves, there are some qualifications to be made. Higher profile games, in which a team is more likely to lose, are often scheduled for Fridays & Saturdays, when spend is understandably higher & attract larger attendances. However, even taking gate receipts into account, the average spend per head regularly soars when the team loses.

Maybe the explanation lies in the euphoria of winning – quite simply, fans are spending less at the bars as they’re enjoying the game more. After all, you’re more likely to look at your phone and purchase food & drinks when you’re not as invested in the action taking place in front of you.

So, our next step was to breakdown the purchase habits of customers at these games, leading to yet another surprise.

2 different offers were shown to customers simultaneously, one providing a 25% total discount and one worth 33% off. Contrary to the rational choice argument, the data above suggests that the majority of users went for the bundle, offering a lower discount.

But why does any of this matter? Well, understanding what makes our users tick is LiveStyled’s goal, and our data team are now well on the way to predicting how a specific group of users are going to react to the live score. This can then define the content we field to that customer group, such as promoting high value bundle offers when the team is losing and we know conversion rates for that offer will be higher.

Sports fans are a strange lot, there’s no doubt. There’s not much point basing our marketing strategies on expected logical behaviour because these fans probably don’t work like that. So instead, we make our decisions based on the data in front of us, trying to understand our users and show them the most suitable content at a given time.

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