SBC News Simon Lidzén, Fast Track: We're already looking at the future of CRM
Simon Lidzén, Fast Track CEO

Simon Lidzén, Fast Track: We’re already looking at the future of CRM

At a bustling ICE London, Fast Track CEO Simon Lidzén talked to SBC News about a slogan that is so synonymous with the engagement platform, the current state of CRM, the importance of delivering truly unique experiences, what the future holds for the company and much more.

SBC News: What is meant by ‘the future of CRM’ being synonymous with Fast Track, and what drives the company forward?

Simon Lidzén: The future of CRM is what we are doing right now. We’re on a mission to digitalise the igaming industry and have built the Singularity Model, a system that uses self-learning and AI which enables operators to deliver 1:1 experiences to their players.

SBCN: Simon, can you share your perspective on the current state of CRM in the igaming industry and how Fast Track is addressing operator’s challenges?’

SL: In terms of CRM in general and the future, we’re already looking at the future. An operator’s main objective is to win players’ loyalty, and in order to do so we need to be very relevant in terms of how we engage with our players. However, a critical issue soon becomes evident. As CRM becomes more targeted, with additional layers, channels and complexity bonuses introduced, the more exponentially your workload increases.

This old-school or transactional CRM is holding back personalisation and the ability to offer a truly 1:1 experience to players.

When you target one group of players with one offer at a time, it doesn’t scale. What we have seen happen to operators over and over again is that they start being a little bit more targeted in their approach, but soon it becomes out of hand.

This is because you have so many deadlines and so many campaigns that you need to send out to cover all those different segments, that you suddenly lose overview of the entire plan. There are just so many activities going on.

Many times operators don’t even know what’s going on with the players anymore. Fast Tack has found a way of dealing with that complexity.

SBCN: Could you elaborate on how Fast Track’s Singularity Model manages to deliver 1:1 player experiences at scale?

SL: We achieve this by providing operators with tools that enable them to extract what really matters to a player. Coupled with a brand’s core purpose, identity, ambition and trigger points, it subsequently trickles into a solid CRM strategy and customer model.

Looking into that a bit more, we’re going to find different player characteristics that matter to the brand, essentially, what are the different types of parameters and characteristics that you want to weigh in when you build an algorithm for 1:1 experiences?

What we’ve built is a matchmaking algorithm. In Fast Track, you can build your own AI, your own algorithm to drive that level of personalisation. The platform is then based on what you feed it as information, and what the things are that matter to you and your brand.  

It will be able to hand pick which promotion, time, channel, what the content looks like, which images have been used and what the tonalities of that communication are, and these are all pieced together by the platform.

You no longer have to build all of those. What you do is you build up a content bank with all of them and you essentially download your CRM strategy into the platform, and then you let the platform take care of execution for you. It’s going to do a better job than you could ever do with a team in maximising your CRM strategy and getting the most value out of it.

That’s what we call the Singularity Model, and that’s what Fast Track is all about. That is our key differentiator in terms of how we are approaching these things compared to anyone else in the market because no one else has anything like that.

SBCN: There’s been a lot of talk about data science in the industry, can you discuss the significance of data science at Fast Track and how your team uses it to enhance the overall success of your partners?

SL: Data science plays an absolutely critical role for Fast Track. This helps drive a ‘pragmatic approach’ in building a company for success, which is realised through a five-step process. These include freeing up time by onboarding the platform, dedicating this to automation, finding bright spots, becoming insights-driven and scaling with self-learning.

Our data science team works with operators in a very close partnership on developing and overcoming whatever problems that you have in front of you that’s required. This includes machine learning and modelling and that deeper understanding; whether it be developing personas, doing churn prevention models and these types of activity. 

It’s absolutely crucial to our product development and the future success of our partners that we have this big team that is supporting that. It’s something that we bring on board free of charge to the people that are included. It’s more about readiness and willingness to participate in that program. And it’s been so successful so far. We’ve had so much cool stuff coming out of that team.

SBCN: Moving on, can you share more insights into Fast Track’s Predictive Churn Model?

SL: Our Predictive Churn Model allows clients to not only witness the results gained but also foster a deeper understanding of how churn can be predicted and prevented. There are so many prediction models in terms of churn and in many ways that I’ve seen in the past, they can be quite similar to one another. 

However, Fast Track has a complete niche focus on servicing the igaming industry. This essentially means that the vast majority of people inside the organisation have an operator background and they understand layers and they understand the challenges and the terminology and everything that goes with it, which knowledge is reflected in everything we build. 

SBCN: I remember reading about a deep integration between Greco and Fast Track, how prevalent is bonus abuse, and what role Greco plays in addressing this issue.

SL: A little over one year ago Fast Track integrated Greco, an incredibly close partner, in every single regard, and we set out to do something that has never been done before.

Despite running into issues in developing a platform for tackling bonus abuse, such as combatting potentially really costly and dangerous automation, Greco have already made such an impact in terms of solving bonus abuse in casinos, and anyone who hasn’t looked at Greco has to. It’s just become one of those platforms where, when you look at the risk element of a casino, it’s a platform no one should be without right now. 

Everyone should have that equipped, and when having it in connection with Fast Track, it becomes really powerful, because Fast Track gets fed that information so that you can avoid sending bonuses, or crediting bonuses, to the players that prove to be unprofitable for you for various reasons.

Greco adds another piece of value as well. What most operators don’t know is how much of their database is actually made up of value secrets.  If you think about it, If you do a promotion to 100 per cent of your database, and you’re looking at the performance of that bonus, you actually mightn’t know whether the performance is coming from the right player.

The data may seemingly look like the promotion is doing pretty well as an isolated case, but in a wider scheme, it might be abused or players might extract value. All this impacts the decisions you make on how you run campaigns and what you do in your CRM.

SBCN: What can we expect from Fast Track in the coming year?

SL: We’re going to continue to become more and more sophisticated as time passes. The next natural step is that we need to make our mark on how these personalised rewards are being delivered to players. 

Right now the limitation is moved closer to the platform. What are the different bonuses that we are able to send? How well are the APIs formed up? And the data stacks, how well are they compatible with this new future of AI-driven CRM?

This is a very natural step in that direction, which I know is going to be a very relevant problem that we need to overcome next.

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