Data and statistics are integral to the overall experience for the US sports bettor, but with a growing demand for content around more niche markets and specific data sets, creating ways for betting companies to engage with customers can often be a huge task.
So by using machine generated content, Alex Kornilov (pictured centre), CEO and Founder of Betegy, explained how it has been able to serve the needs of the sports betting industry as well as sports media companies as it grows its footprint in the US.
SBC: Firstly, can you tell us a little bit about what Betegy does?
AK: At Betegy, we take the data used by our clients, and then we analyse that information in terms of predictions and analytics, as well as data visualization. The data visualization aspect recently became a growing part of our business, and is now a key driver for us.
What we do is we help our clients to create marketing materials for sports events at scale. So, imagine you have an editor who writes about a game between Chelsea and Manchester United. Instead of going into the statistical feeds and talking to a designer to assemble certain graphical images for his article, they can use our system, select the event, select the type of data they want to visualise and select the different outputs.
For example, if they want an animated video with game projections for YouTube, live images for this event for their article and then a picture with head to head information about those two teams for social media, they can just click click, click and voila! We pull all the data from data providers to generate all of this material in one click.
We also work with betting operators whereby we add to the mix of our data sources by including betting odds. Betting operators can instantly produce tonnes of content for their campaigns, such as banners for every event with statistical information and all ads, landing pages for every single click on those banners.
All of those are dynamic generations of content, which is customised and personalised, and can go to different markets. It can be in different languages. To manage this, betting companies can use our system. It’s a very powerful system, which allows you to automate your content creation in scale for every single sports event.
SBC: And how has this evolved since you started out in 2012?
AK: When we first started in 2012, it was only data analytics. But then in 2016, while working with Yahoo Sports, it became clear that data needs to not only be analysed, but also visualised. Data is needed to be read by humans and used in a way to engage the audience at a new level.
I think sports data is the most exciting content online – it’s always fresh, it’s always exciting and it’s always important to those who follow the sport. So odds and data for these events are super prime content. But, unfortunately it has a short shelf life. What you publish today won’t be relevant tomorrow.
So what is the point of engaging resources to create content, which will be seen by X number of people for x minutes, and then it’s not relevant anymore? Therefore, no one is doing it. But with machine generated content, where we can plug all the APIs and data sources, it creates resources at scale, quickly and without engagement of human resources. This changed everything, because now you’re able to customise and personalise the content.
SBC: How does Betegy plan to differentiate its offer in a US market place that’s currently well populated with data providers? What’s your USP?
AK: This is a very good question because, in general, those are not our competitors. They’re our partners, because they’re making sure that the data they collect is the most accurate. We then take this data and create the engaging experience out of it.
We take the data that they collect and create charts, graphs, banners and landing pages from it. So they are partners, and if there are more of them, it’s better for us – we’re not trying to compete with them in any way. We’re just extending the value of their data for their clients.
So for example, when we work for certain business operators, and we know that they’re providing content, there isn’t like a big company equivalent data provider who provides data to this company, we just take this data on behalf of our client, and make much more value out of it than just API feed. This makes everyone happy.
The provider of the data can focus on what he does best and delivers the data. He and his clients are more engaged in the contract with them, so that they use it in more ways on the front end of their tools, but also for marketing.
Finally, they can send email newsletters with custom scoring odds and infographics for every single player for every single user they have. Another positive is that on our side, we focus on data visualization. So we work with the feeds of those providers and make sure that it’s taken care of.
SBC: Do you need to meet a demand for more complex, in-depth data for the US audience?
AK: What we’re now finding is that the demand is for machine generated content. There’s so many sports you can actually do data content for, and you physically cannot solve this with your hands; there’s a place for machines to take over.
You have to set limits on the things that you can do, and know the certain things which the computer can do. When you want to meet the demands for all of your customers, and generate personalised visual content, you need the help of machine generated content. It can be as exciting as human generated visualization. So here we are answering that by actually applying technology to this to solve this question. It’s perfect to solve this kind of problem.
If we’re taking a broader look at the US, what is interesting is that the audiences are much more statistically driven than the European audience. If we take the basis of the European sport, which is football, it’s way harder to predict and to analyse.
By contrast, American sports are more data driven. There are more scores in each game. But for football, it can be 0-0 or 2-1. The data side is not done wisely, which is why the European market is lagging behind in terms of data, analytics and the visualization approach, therefore, the audience is less prepared.
SBC: Why have you chosen now to enter the US market?
AK: We decided on a board level to enter the US last year. And to do this as a European company, it requires time. That’s why we’re announcing the deal now. A year ago, I met Bill and some other people in the industry, and I started to assemble a financial plan and prepare for an expansion. Then we needed someone to back this plan, which is where JKR Investment comes in.
I think it’s going to become the biggest domestic market in the world, and it makes perfect sense for us to penetrate this market with our solutions for data visualization, because it’s much more needed there. Even though Europe requires data visualization, I think it will be a very quick race between Europe and the US.
SBC: What are the challenges for a European company looking to establish its presence in the US market? If so, how do you plan to overcome these?
AK: I would say the biggest was different business flows. That’s one thing, because deal making in the US has a different approach. The time to close a deal is different to what it is in Europe. In Europe, it’s faster. But in the US, you have more due diligence, the companies have longer history and longer cycles for decision making.
Our solution brings with it new processes for our customers, which requires some time to be adopted. You need to be able to go through the deal and work with your customers. It may take six months, one year or 18 months for a deal to be closed – and then, you have to align your customers with your strategy. Then, when the time is right, you can close the deal.
As a European company, we needed someone to guide us. The US is a new world for us, and even though we already have a US client, it’s still an untouched market for us. When I asked Bill to join our board of directors, he agreed and I was so happy because his advice is unparalleled.
SBC: How will your offering for the US market differ from that in Europe?
AK: The biggest difference is the different sports. So now, we’re looking at sports like NASCAR, tennis etc. We’re now having to change our offering. Even though it doesn’t matter what sports we work with on our system, it still requires time for us to adjust to new sports and learn to understand how to create these data visualizations.
The second part is that in Europe, we mainly work with betting operators and with some media companies. But in the US, we also have the same strong demand for our service from the media companies because media companies in the US are used to preparing to work with more statistics and data. They invest in this data. But in Europe, statistics are considered to be an additional cost.
For example, when we talk to different leagues, or media companies, they already have wonderful databases. They’re all in the proprietary data, which we can work with. So we’re now serving two markets: sports betting and gaming, and the sports media industry.
From the US, we have an equal demand for media compared to media companies. Which is interesting for us to see.