The screen in our hands is now a gateway to entertainment and sports content online and with one of the most exciting Premier League title races in recent memory in full swing, what better to keep track of your beloved team than a series of handy apps?
Sporting apps have never been more popular
According to Google, sports fans have been taking advantage of the new wave of apps to hit the marketplace. Google estimates that we spend on average nearly 50 minutes per day on our favourite sports apps!
(For some perspective, that’s roughly 26 hours per month and according to comScore’s Cross Platform Future in Focus report 30% of the time the average American adult spends on their smartphone every day.)
Now, it doesn’t take a business genius to recognise the tremendous opportunity for football clubs to capitalise on our passion to keep our football knowledge in check.
Analysing customer feedback can be a pretty big mess.
The tricky part, however, is figuring out what aspects of the customer experience football fans love and elements that are making them downright miserable.
Traditionally we’d turn to Customer Experience metrics (think NPS, CES and CSAT), and while essential to monitor, only give a quantitative view of what’s happening. Customer Experience metrics don’t reveal the why behind the score and provide insight into why a particular metric has dropped or improved over time. To get to why we need to listen to our customers and dig deep into their feedback.
When you’re a scrappy startup, every team member digs into the customer feedback with enthusiasm, pumped to find out what customers think about the product and the Customer Experience.
But this process isn’t feasible in the long run. Analysing customer feedback is hard when you have a mountain of feedback coming in regularly — some of it about bugs and other product issues, some of it about video quality — making it all actionable is a tall order.
To make matters worse when companies stop listening to customers, you can quickly lose sight of the customer. Before long your vision for the product or service offering you provide won’t reflect the reality of what customers want — leaving the door wide open for a competitor to build something better.
The challenge is understanding how to organise and prioritise the different types of customer feedback you’re collecting. How can clubs efficiently categorise their feedback from their fans and understand what fans are saying about them and how they feel about their app experience at scale?
Customer Experience Analytics: Understand what your customers think and feel
Enter AI-powered Customer Experience analytics. It’s now possible for a machine to understand human language accurately. It's never been easier for you to analyse the written text of your customers and find out what customers hate and love about your brand.
A machine can now understand different contexts and meanings of words with the accuracy level of you, reading this text right now! That’s a big deal because we severely underestimate how complex the human language is.
Does the word ‘hot’ mean the weather is warm or that a dish is spicy? Consider the multiple ways we discuss the concept of price with our friends. We use a lot of colloquialisms when discussing certain products and their prices. ‘That cost an arm and a leg’, ‘daylight robbery!’, ‘inferior value for money’, the list can go on and on…
So how does this tie back to Premier League Football apps you may be wondering? Well, we know a thing or two about text analytics, and we like to experiment and have fun.
With the rise of sports apps and our appreciation for football in the office, we decided to put our knowledge to the test and analyse Premier League app data to find out which team is providing the best Customer Experience for its fans!
If you want to find out who comes out on top, keep reading!
Methodology
We decided to experiment by analysing all the open source data available on the Android and iOS app store. We gathered thousands of comments across the premier league clubs that have mobile apps and examined them using AI.
For the experiment, we used the metric Net Sentiment to rank how each app performed.
We calculate Net Sentiment by subtracting % negative mentions from % positive mentions across all themes and categories we discovered in the data.
For those of you who aren’t familiar with our terminology on themes and categories, our AI algorithm analyses customer feedback and tags each piece of feedback with one or more themes. Each theme is characterised as either a positive mention or a negative mention. We then group themes under umbrella categories.
The Results
Cool. Now back to the results.
The table below is representative of net sentiment score recorded on 3/04/2019. So if your club sitting at the bottom of the table fear not, the data is live, and Marvin our friendly AI will update the table as fan sentiment changes!
One thing for sure was how well teams perform on the pitch was not the most important correlating factor into how well the apps performed.
For any Tottenham fans reading right now, it’s maybe time to look away as St Totteringham's day has come early...
So what’s separating the winners from the losers?
We can use Chattermill to slice and dice the data to get the full story on why some teams are delighting fans and why others teams seem to be scoring own goals.
Keen to find out more?
Then view our live dashboard here for a limited time period only.
Feel free to start a conversation and someone from Chattermill will be happy to answer your questions.
If you like what you see then to share the dashboard all you have to do is:
- Copy the URL of the dashboard.
- Share in any community, slack channel or email to any colleague.
P.S. If you want to see more industries analysed then leave drop us a message at hello@chattermill.io
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