New study on how the responsible gambling tool Playscan is used

In the article “Usage of a responsible Gambling tool: a descriptive analysis and latent class analysis of user behavior” PhD student David Forsström from the Department of Psychology, Stockholm University, studied how players are using Playscan. He examined the Playscan 3-data of 9 528 online gamblers who used the tool voluntarily and investigated if there are different subclasses of users by conducting a latent class analysis. He observed number of visits to the site, self-tests made and advice used.

 

The study has shown that the tool has a high initial usage and a low repeated usage. Latent class analysis yielded five distinct classes of users: self-testers, multi-function users, advice users, site visitors, and non-users. Multinomial regression revealed that classes were associated with different risk levels of excessive gambling. The self-testers and multi-function users used the tool to a higher extent and were found to have a greater risk of excessive gambling than the other classes.

 

Professor Per Carlbring states, “The low usage of the tool is not a disappointment. As long as the right ones actually use the tool, which is exactly what we found. People with a higher risk level are using Playscan more.”

 

Find the study here

responsible gambling software

Using a hypothesis-driven approach to develop effective responsible gambling tools

The prevention of problematic gambling is a complex issue. We at Playscan know it all too well. But in order to learn about effective prevention initiatives we use the method of validated learning for acquiring new knowledge.

By practising hypothesis-driven development for responsible gambling we see the development of new tools and services as a series of experiments to determine whether an expected outcome will be achieved – or not. With this we challenge the concept of having fixed requirements when we develop new features. Instead, the process is iterated until we reach a desirable outcome.

6 steps toward hypothesis-driven development

1. We make user research and formulate a hypothesis

Let us look at an example: In interviews with users we often ask them to describe their general attitudes toward their risk assessment. We hear players ask themselves: ok, so this is my risk assessment…but what do I do now?

(This is where we get the chance to identify what the user is expecting from us. From this it is our responsibility to design features that address the problem.)

Our hypothesis is:
We believe that if we clearly communicate the answer to the question “what do I do now?”
Will result in more players reducing their risk level.
We will know we have succeeded when we see an X% increase in risk levels.

2. We define targets and points to measure

We base the work on the products Impact Map, a document that help us drive our software development towards effect, meaning delivering the right responsible gambling initiative to the right player.

Example: X% more risk players know what to do in order to lover their risk level. This is measured with an online questionnaire; click through on recommendations and analysis of the gambling behavior.

3. We design an experiment to test the hypothesis

Best practices and research inspire us when we work on a solution. We talk it through with our experts on problematic gambling, write texts and produce real content.

4. We develop the solution

During the process of making the solution alive software developers, UX-designers and copywriters work closely together. Simply because it always gives us the best result. Then we launch it.

5. We validate the use, accept or reject the hypothesis

This is where we collect feedback from the player and can see if the solution delivers the use we expected. Did it work? Or do we need to change anything? Here we learn and iterate and make it even better.

Our most important work: we iterate!

To ensure that we are on the right course, we work in short iterations that are generally two weeks long. We build the system with small additions of user-valued functionality and evolve by adapting to user feedback. Have we stumbled on any mines? Well of course. But it’s a part of the game – we do not even expect to hit the target at the first time. For every experiment we do we always learn something new. Even if we had a great hypothesis (based on good observations or research) sometimes the results are just neutral. But this is why this method is so effective: we can quickly get a hint on what seems to work – and what’s not working.

Winning big can lead to changed behaviour among poker players

lego

 

It is said that a big win, early on in a persons gambling career, could lead to false expectations of future wins. This in turn could lead to increased gambling, which consequently increases the risk of becoming a problem gambler.

We took a closer look at this phenomenon by studying how players behave after a big win.* We compared their gambling activity and how much money they spent gambling, one month before and one month after the event.

FIRSTLY, we found that, after a big win, players increase their gambling activity on average by 30 %, although with big variations.
One could have expected this number to be even greater, or at least we did – the interesting part is that instead of an even higher gambling activity, we see differences in behaviour between different families of games.

SECONDLY, players who prefer games of chance tend to slightly increase their level, but do not increase their betting amounts and therefore manage to keep a big portion of their winnings.

THIRDLY, we note a low correlation between the size of the win and the change in gambling behaviour, with one exception: the poker player. Poker players are more likely to increase their betting amounts and even if some of them actually manage to continue their winning streak, some lose their winnings rather quickly.

So, is a big win a risk factor for developing problems? Well, by analyzing this particular set of data, we find that a big win does have an impact on future gambling behaviour – even if the effect seems to differ depending on what family of games you prefer.

Reaching the right player with the right intervention, at the right time, might be the one of biggest challenges we face in the industry, since we do not wish to disturb players without a cause. However, with this information it is fairly safe to say that one should pay extra attention to the aftermath – and stop players from crashing after a big win. So on we go by A/B-testing specially designed messages; warning players if they suddenly increase their spendings after a big win. We will then study how this information impacts future behaviour – hoping to see more players keeping their scoop after winning. Stay tuned for the results.

 

Do you want to know more? Drop us an email!

 

 

*A “big win” in this case is 50 000 SEK on one gametype in one day.

Playscan has a proven positive impact on at-risk players

PRESS RELEASE
Göteborg, Sweden 2015-07-08

A new research study just published in the journal International Gambling Studies showed that at-risk players who received behavioral feedback via Playscan were significantly more likely to reduce the amounts of money they deposited and wagered – compared with players who did not use Playscan.

The authors, Dr Richard Wood and Dr Michael Wohl, conducted the first study of this kind to use actual behavioral data, from 1,558 Internet players in a real-life setting.

“This is a relatively new area of investigation in the responsible gambling field, but our results suggest that such a tool can be very useful to help at-risk players keep better control over their gambling expenditure,” said Dr Richard Wood.

“The study provides empirical evidence, that helping players to better understand their gambling behavior has a sound practical application as a responsible gambling strategy,” added Dr Wohl.

The research provides valuable insight into how a well-designed player-tool, such as Playscan, can be utilized to ensure players have a more responsible gambling experience.

Playscan is thrilled to have been part of the study and to contribute to a better understanding of how to support responsible play.

 

Access the full research report here

For more information about the study, contact:
Dr. Richard Wood at info@gamres.org

Playscan AB merges into Svenska Spel AB

PRESS RELEASE
Göteborg, Sweden 2015-07-02

The ambition of the Playscan team remains the same, as the development of the tool maintains its progress.

Continuing its work with harm minimization and the prevention of problem gambling, Playscan AB now merges into Svenska Spel AB. Therefore; the product will no longer be commercially available.

Today, there are several variations of responsible gambling tools like Playscan on the market. “Behavioral tracking tools are a recognized responsible gambling methodology, used for consumer protection. Our solution has been ahead of this curve, leading the way, which is really inspiring. However, we see that many operators pursue their own solutions, making demand for an off the shelf solution low.” says Andreas Holmström, CEO of Playscan AB.

He continues, “We will now continue to improve the tool together with Svenska Spel and all our other clients. We are also open for new forms of collaboration with the industry and the research community. We will carry on with educating operators, promote a mutual exchange of knowledge and share best practices on how to prevent problem gambling, throughout the industry.”

Lennart Käll, CEO of Svenska Spel is convinced that all operators using Playscan are contributing to a safer gambling experience for their players. He says, “Playscan is a core component of our responsible gambling strategy, and will remain so. I’m very proud to see how the product has evolved – and the hard work done by the dedicated team behind it. It will be exciting to follow its future development.”

 

For more information, drop us an email!

From 10% to 60% click-though to a RG-tool – why user interface design matters


How do players use a responsible gambling tool – why user interface design matters – talk by Natalia Matulewicz. Presented at the SNSUS Conference, Stockholm, June 2-3 2015.

How do we increase the usage of responsible gambling tools? Is mandatory or voluntary the way to go?

This talk means to inspire and give new ideas to how to increase the players interest and usage of responsible gambling tools. With the help of user interface design guidelines and persuasive technology principles we went from 10% players using the tool up to impressive 60%.

Miljonlotteriet upgrades to Playscan 4

PRESS RELEASE
Göteborg, Sweden 2015-06-02

The latest features from Playscan are now available to players gambling at Miljonlotteriet. The lottery has offered Playscan to their players for more than four years and by upgrading they will now supply players with a new and more detailed view of their gambling behavior.

– What I really like about Playscan 4 is that it is so much more than before, says Ludwig Alholt, CEO at Miljonlotteriet.

He continues:

– The tool is essential not only for the player, but also for the Operator. It helps us understand and evaluate the impact of our overall responsible gambling initiatives.

Every week Playscan analyzes the gambling habits of 4.5 million players globally. Players appreciate the system, they reflect on their habits, perform self-tests and value the fact that it warns them if their gambling behavior changes into becoming more of a risky one. Which means they remain as a healthy player, as well as in control of their gambling habits.

 

For more information, drop us an email!

About Miljonlotteriet
Miljonlotteriet was founded 1964 and is one of the oldest lotteries in Sweden. We offer scratchcards via subscription, online and with retailers and bingo online. Our vision is to be the operator that is known for creating dreams and making reality out of them. Miljonlotteriet is owned by IOGT-NTO and together we have a dream that no one should have to grow up in a world surrounded by addiction. Since 2000, we have contributed with 1,6 million Swedish kroner to the work of IOGT-NTO. Do you want to know more? Please visit: www.miljonlotteriet.se

Measure and improve your RG initiatives with new Playscan services

We use the Playscan Risk Analysis for two purposes. The original purpose is to use it as a basis for interventions and communication to at-risk players – now, we equally use it together with operators and creators of RG. By looking at levels of risk and changes herein, between groups, marketing campaigns, interventions, etc. we measure the effect of what we do. We quantify, instantaneously and at scale, our mistakes and our successes – every day and for everything we do.

Now, we know that these tools and methodologies could be put to more use out in the world.

Therefore, we’ve added an offering to our product portfolio: the standalone Playscan Risk Analysis. If you already have an RG communication platform or already established RG tools that fits your needs and strategy, and instead is looking to add RG metrics to your operations, this is what you’re looking for.

More-so: if you are not yet ready to invest in an integrated,  fully-operational system: we at Playscan now offer our Risk Analysis and methodology as a service called Sustainable Gambling Management.

 

As the basis of it all, you will get a risk scoring for each of your players. From this seed, a multitude of knowledge sprouts:

Measure the effect of new RG efforts

When you’re launching a new initiative, you’d like to know what effect is has – both to understand the business and RG impact. By bringing in Playscan at the early stage of the project, we will help you track and quantify the results, and measure the effect of your new initiative.

Responsible Gambling KPI:s

The Playscan Risk Analysis unfolds nicely into a set of KPI:s. As an initial step, you may want to try out our metrics by looking at previous years of operation, to get a feeling both our metrics and how they benefit your operation today. When you decide to have these as recurring KPI:s, you have a head start of getting an Analysis Engine installation.

Development of your RG portfolio

If you feel like you’ve added all the tools and information you possibly could, but would like to make the most of it, Playscan AB can help you find a fruitful direction and get some early victories off the ground. We will join forces between your strategies and tools, and our day-to-day experience in reaching the at-risk player.

Reaching the right players with your RG tools

On our three-color-scale (green for low risk, yellow for at-risk, and red for high-risk), we see a big difference between green and yellow players. While the latter is not a uniform group of people, they tend to share traits and behavior that relieves us from much of the fear of annoying or even accusing the low risk players. After all, the green majority of players are those for whom the industry should focus on for a good and exciting experience.

In contrast, the yellow players are slightly different. They tend to identify as players, and gambling is a considerable part of their past-time. They often have self-imposed strategies to keep control of their gambling, and while they may never have developed severe problems from their gambling, they can relate to how it can spin out of control.

Now, the difference between green and yellow is vast: not just in terms of the operator walking the balance between business goals and compliance, but also as a divider between those who (yet, at least) don’t need and don’t want to dig deep into the plethora of tools, and those for whom it is both interesting and relevant.

We know how to communicate with increased risk players: let’s set up a strategy, reaching the right player with the right tool at the right time.
To learn more, pop us an email , catch us at one of the events we’re at or shoot us a tweet!

Presenting Playscan Research

Phd student David Forsström presenting results from his studies at SNSUS conference and at the Department of Psychology, Stockholm University.

 

In the first study (to be presented at Stockholm University) user behavior was analyzed  and the main finding was the identification of  five distinct classes of users: Very high usage, high usage, advice users, site visitors and non-users.
 
The second study (to be presented at SNSUS) focuses on how the user experiences Playscan. The main findings are that users want more feed-back from the system and that the type of gambling activity online influences Playscan usage.

 

 

First study will be presented at Stockholm University at June 2, 2015
The second study will be presented at the SNSUS conference in Stockholm at June 3, 2015

Increasing click-through to RG-tools by simple re-design

To make sure you have impact, do quick experiments and redesign things based on usability principles. By doing so, we found out that displaying only one recommendation at the time makes more people click.

A click on a recommendation is a success for Playscan. It means that we’ve provoked a reaction or created interest for taking action.

Sometimes, the little stuff create a big difference. As Thaler and Sunstein writes in their bestseller Nudge: “[S]mall and apparently insignificant details can have major impacts on people’s behaviour. A good rule of thumb is to assume that “everything matters””. With the “everything matters” mindset, the insignificant details can indeed prove fruitful beyond expectation.

Back in the days, Playscan always showed two recommendations to players. The rationale was that this was a trade-off between making sure to give the player more than one choice, to make sure he could find something relevant, but not to overwhelm him with too many. From nothing but our own curiosity, we decided to test whether we were correct.

We randomly divided our visitors into three groups, presenting them with one, two or three recommendations respectively. Next, we measured the click-through rate during a two week period. At the end of it, we realized that we had left a good many clicks on the table.

Our original design with two recommendations proved a 20% click-through, measured as the proportion of players who clicked any tip. The three-tip version showed no significant difference, but our one-tip version did: 36% of players clicked the recommendation. Again: the only change was one vs two recommendations – no other design changes, the same selection of recommendation, no new content – and from this we doubled our click-through!

Lessons learned?

Hindsight is always 20/20, and there is a reasonable explanation for what we found: players are more likely to click through with fewer conflicting and maybe confusing recommendations to choose from. Still, before our test we thought we had an equally good theory of why two recommendations was the way to do things.

So while doubling our click-through on recommendations based only on simplifying things was a big lesson learned, the biggest was without a doubt that “everything matters”. Ideas and hypotheses are a good starting point, but until proven they are just that: hypotheses.

Now, getting people to use our tools is only a first step in having impact. When it comes to recommendations, the next is having relevant ones. How do we make sure that they are? Well, we will test that too.

risk_analysis_playscan

Why it is meaningful to collect and interpret player data from a risk perspective

We tend to talk a lot about consumer protection in the gaming industry. It has become a vital part, and a bit of a buzz in business since a number of online markets have matured and regulatory bodies are challenging the industry into more preventive online actions against problematic gambling.

Therefore there is an urgent need to understand players’ online behavior. Not only for creating a perfect gaming experience: but in the case of consumer protection. But yet, there is still no consistency in what consumer protection really means and the question of “how we protect vulnerable players” has still not been answered. And meanwhile as we discuss all off this, we seem to miss the target.

The player.

The information every player provides to us could give us the answer. This article will argue that if we actually value consumer protection, not only as an abstract concept that we nod at agreeably during meetings – we should make use of information available: player data that is understood from a risk perspective.

 

Identification of high risk gambling in player data

A lot of data is being generated every minute of the day when players gamble both online and within land-based facilities like Casinos or eGaming machines. Purposely designed behavioral tracking solutions can identify patterns of play in gambling data, and with current technology, combined with understandings of problematic gambling; this can be utilized for proactive consumer protection.

 

Many players, with real life problem gambling stories, express that they have experienced “an escalation of their behavior” and before they knew what was happening: they were placing increased bets, and losing more and more money. By identifying these risk factors in player data – Operators get a new dimension in “knowing your customer”.

 

Player data holds a lot of information, such as age, gender, favorite game etc. But player data also holds descriptions of a player’s behavior. Looking at data from a risk perspective means to identify possible negative behaviors or risk factors, such as;

 

  • Start playing more often

  • For longer sessions

  • Constantly changing planned spending limits

  • Chasing losses

 

These are a few examples that relate to user behavior rather than user information. With a risk analysis, it is possible to make players aware of changes in actual behavior.

This information provides direction for effective responsible gambling initiatives at an early stage, preventing problematic gambling instead of treating a problematic gambler. The risk analysis helps segment the player population into “low risk”, “increased risk” or “high risk” – leaving Operators with information for unique opportunities like customized responsible gambling communications.

 

How to understand data

Even if we have spent time on data analyses and even when players with risky gambling behavior are identified – it’s still tricky to answer the question “how can we protect vulnerable players?”

Data describes what players do, how they behave. But not really what they need.

One way to understand it and knowing what to do with data is to humanize and bring these numbers to life. For example: Wilma is a 45-year-old woman who likes gambling, especially online bingo. For the past six months she has gambled at a high-risk level, with few gambling-free days. Late nights with bingo, long sessions with lottery tickets after lottery tickets. She finds herself in a loop of wagering more and continuing to gamble, with higher stakes, even after she just lost.

This was not an ideal situation for Wilma, simply because she couldn’t afford it and lately her risk data indicates that she is trying to cut down on her gambling. For example, she is setting strict limits for her gambling that she has managed to keep within.

Should the Operator take any actions? Well, since Wilma previously has been on a high-risk journey, one thing that she does not need is to receive promotions, bonuses and commercials from her gaming company. This is were the operator can differentiate an out-going customer to one that just wants to control their gambling habits.

With customized communications, it could also be wise to inform Wilma, close to play, if her gambling sessions seem to be escalating again.

 

Why is this all meaningful?

By rethinking the way Operators use data and understand players, they can create meaningful communications that influence and engage the players. By taking the player’s risk level into consideration when communicating with player Operators can better focus on the user’s needs.

Knowing the player’s risk level is valuable through the whole chain of the gambling industry: from game design, marketing and user experience to management and business development all the way to customer support – and the player.

Simply, through understanding risk we avoid “one-size fits all” solutions and then we add true value to the concept of consumer protection. Because the point is that the answer to “how can we protect vulnerable players?” is that it varies according to each player’s risk behavior.

 

 

Risk analysis of gambling behaviour, now a service for all players in two Nordic countries

The Norwegian state owned lottery Norsk Tipping has now upgraded the responsible gambling tool Playscan into its latest version: Playscan 4.2. And they are making it mandatory for all their players. Not far after, Svenska Spel, the Swedish state owned lottery, made the same decision.

Players want responsible gambling tools that are easy to use and integrated in their overall gambling experience. That was the starting point for both Norsk Tipping and Svenska Spel.
Bjørn Helge Hoffmann, Chief Adviser Responsible Gaming at Norsk Tipping explains:

– By upgrading to Playscan 4 we are focused to make Playscan into a service for all, i.e. making Playscan mandatory to all our players. With this, our players are offered integrated communications in regards to changes in their gambling habits as part of their overall gaming experience.

Zenita Strandänger, CSR Manager at Svenska Spel, says that it is important for Svenska Spel to assist their players into making informed and responsible decisions about their gambling. She says:

– The tool promotes responsible gambling behaviors and it plays an important role in our overall consumer protection strategy. Making Playscan to a service for all players is simply a natural next step for us.

– We are very happy that these two Operators now is communicating with all their players that are showing signs of increased risk. That is great news for players and for our continued efforts in consumer protection, says Andreas Holmström, CEO of Playscan AB.

To learn more, pop us an email

5 key elements in your online responsible gambling strategy

What a gambling operator should do when implementing responsible gambling

 

01. Educate all employees about the importance  of responsible gambling. That means all the way from  executives to your customer service team. Probably the most  important thing to do to get acceptance for responsible gambling.

 

02. Train and educate retailers about  the importance of responsible gambling. Retailers meet players all day long. Don’t underestimate their impact on your overall responsible gambling operations.

 

03. Get behavioural insights. Use your gambling data to understand the risk level of your customer. And intervene at the right time to minimize risk of harm and to secure sustainable revenue.

 

04. Customize communication to players needs. Take a critical look at how your gambling site is designed: present your tools and write your responsible gambling information in a way so your players can easily find and use them.

 

05. Talking about being a responsible gaming provider doesn’t make you one. It requires commitment and actions.

 

Big_data_gambling

Technology alone cannot diagnose someone as a Problematic Gambler

 

On Wednesday 10th December 2014 at the Responsible Gambling Trust Harm Minimisation conference a number of findings were presented from recent commissions research ”An investigation into gaming machines in licensed betting offices: exploring risk, harm and customer behaviour.”

The objective of the research was to see if industry data could be used to identify harmful patterns of gambling on machines in bookmakers. By simply analyzing the data and using the Problem Gambling Severity Index (PGSI) score as an index to classify a player as a Problematic Gambler.

But as will be argued in this article, can you diagnose problem gambling through behavioral data by itself, i.e. labeling someone as a problematic gambler– and is the UK gambling market reinventing the wheel in doing this?

 

Technology that provides intervention at the right time.

Vast amounts of data is being generated every minute of the day when players gamble both online and within land-based facilities like Casinos, eGaming machines and retail points of sales. Selectively collating all those data points and combining them with data mining technology, artificial intelligence, gambling psychology and cognitive behavioural modification through targeted communications, provides the player with a unique, player centric solution that offers them an informed choice about the status of their gambling and invaluable player information for the operator and regulator’s.

 

Behavioural tracking provides information back to the operator about their player population, enabling them to be more proactive in reducing potential risks that could manifest itself into problematic gambling. Understanding the player’s journey is paramount, not only understanding where the player is heading but where they are coming from. “Green Marketing” is such a way, identifying those higher risk players and removing them from the operator’s regular sales and marketing campaigns. If a players journey is one of increased ”at-risk” behaviour then implementation of this green marketing process will ensure they are no being bombarded with marketing to increase their gambling, likewise if a player has decided to change their gambling habits and reduce their gambling then the last thing that player needs is frequent reminders and marketing materials to entice them back to gambling.

 

The information provided from these systems enables the operator to show the regulatory bodies how they are working within the areas of harm minimization, and provide full accountability for those actions.

 

Can behavioural tracking identify a player as a problematic gambler?

This becomes almost a semantic question or at least a question of what we put in the words “problematic gambling”, because one very important thing to mention is that behavioural tracking technology cannot identify problematic gamblers reliably enough with data only.

Behavioural tracking solutions can see how you are playing, how you are increasing your various risk levels between different types of games and understand from the player’s own perception of their own gambling behavior, but what behavioral tracking solutions does not know is the players own social or economic circumstances.

Even though it is a big chance that a player with high-risk behaviour is a problematic one, there is still a requirement for numerous other factors to be taken into consideration. What is still unknown about the player is the social, economic and psychological status. For instance the player could be an owner of a company with a high level of disposable income and available time or they could be a minimum income, family person with low disposable income and minimal available time to spend.

Behavioural tracking solutions can only identify changes in risk levels based on their actual gaming data from that operator and players own psychological belief of their gambling habits through the various system Self Reporting methods. Claiming otherwise could be very detrimental in lowering the trust towards these types of tools. There is always a non-trivial risk that any player that is identified as increased or high risk is really not – which is why one must be both cautious and humble.

 

So what wheel is now being reinvented?

This technology has been active within numerous Scandinavian, North America and European gaming operators for nearly a decade now. It has taken many years to understand gambling behaviour, to analyse the data correctly and how to effectively communicate with those individuals who show signs of increased risk. Therefore, it is vital for UK gambling industry in their journey of discovery, to work more closely together with various segments of the industry (such as established technology providers within this sphere, other private operators, state owned operator, researchers and regulators). There is vast information being held in all segments and combining this knowledge will inevitably benefit the industry, players as well as reducing the social impact on families and state.

 

Data answers what – but not why someone is at-risk.

The challenge head lies not in how to identify an at-risk gambler in gambling data; on the contrary we need to understand more about what their journey looks like – and their needs. What circumstances contributed to this? And when we, meaning the operator and regulators, have all this information, what should we do with it?

 

Currently State owned lotteries are leading the way over the private sector in adopting this type of technology and answering this kind of questions, which changes their responsible gambling attitudes from being a reactive one to being more of a proactive one towards the potential harmful effects of gambling.

Some of the positive effects from this are that we finally can discuss and act on topics such as reduced impact on the society, sustainable long-term revenue gain and healthier, informed players in a true, meaningful way.

Making big data actionable by creating user personas

Talk by Natalia Matulewicz at the New Horizons in Responsible Gambling Conference February 2-4, 2015

What do you know about your online player? With anonymous players, customer data is an important factor when making strategic business decisions with limited information. However, big data often becomes a faceless collection of information, rather than a true picture of the players’ wants and needs. One still needs to know how to interpret data and how to combine it with other sources of information.

User Personas brings together big data with qualitative user research such as interviews, field studies and observations to gain an overall picture of a user, their needs, goals and motivation. It also fills the gap between what players claim to act upon compared to their measured actions, which in the context of gambling often differs. Combined with big data, User Personas give the answers to three important questions: what are the main target groups, which target groups should be focused on to make the most impact, and how should communications be designed towards those target groups?

What does the gambling industry know about increased risk players?

 

A while ago we attended a meeting with the customer relations marketing (CRM) team at a gambling company. The team had been working on creating customer segmentations, which within marketing is one well-used idea.
The concept refers to creating groups of people with common behaviors and characteristics that you want to reach with messages or offers. The team we met had done a careful segmentation based on money, game types and combination of games people play and demographics.

 

The head of this project explained that they had identified one segment of players that they chose to call the “high spenders” and that is obviously where most the high-risk players could be found. They continued telling us how they work on helping that group by unsubscribing them from all promotional marketing campaigns.

 

From a responsible gambling perspective this is a reasonable and logical course of action. Not to encouraging a player with risky behavior to gamble more. But the team looked at us and asked: is it really fair to stop sending promotions after just one week in the high-risk zone? What if the high-risk behavior is just a coincidence? Maybe some of these players have saved up some money to gamble, lets say, during The World Cup?

 

The CRM team had raised a very interesting question: When is the appropriate time to intervene?

 

INTERVENTION AT THE RIGHT TIME 

It is true that we find a lot of high-risk players in the high spenders segment. They are a frequently discussed topic at conferences and in research. And the industry is taking great leaps in their work with responsible gambling by offering tools like help and support for these players: self-exclusion, panic-buttons, contact information to help lines and support groups, educated customer support team and so on.

 

The point is that players do not become high-risk players over night.

It is often a long process of escalating behavior and change in attitude, which includes increased tolerance towards gambling.

 

We believe that the key is to meet the needs of a player early on, before they turn high risk and it becomes a problem. The goal should be to figure out what we can do for the increased risk players – so that reactive tools like self-exclusion and blocked marketing are not to be needed in the first place.

 

MOST PLAYERS ARE NORMAL PLAYERS

Chances are that you, much like us, are used to hearing about the big group of normal or low risk players and a small group of high-risk players. Many of the high-risk players are hard to reach with warnings of risky behavior because of the probability that they can’t bring themselves to care about the consequences of that behavior. For these players, offering hands-on actions is more effective and helpful.

 

However, what comes to mind is that we need to keep the low risk players at low risk. We try to inform them, enlighten them, provide them with tools and educate them all about this thing called gambling problems.

 

The problem is that most people are not that interested in talking about what could become a problem – in fact; it is really difficult for humans in general to relate to a “potential problem”. We want normal players to take part of this important information about responsible gambling but at the same time we do not want to scare them away from our gambling site. What makes this really difficult and complex is that normal players are there to play and enjoy themselves and setting limits or reading about problem gambling simply is not that entertaining.

 

So, we have a big group of low risk players that are not truly interested in responsible gambling. And then we have the high risk ones who are already at high risk. What to do? Well, lets look into what happens in-between when the player is at low risk and the moment they turn high risk.

 

Again: players do not become high risk over night.

 

There are more than enough chances to intervene.

 

PREVENTION IS ABOUT GETTING THROUGH BEFORE

Most of the low risk players do have a positive attitude towards responsible gambling tools – they don’t really mind setting a limit for time or money. But as mentioned, they do not necessarily see why they should put their time into it. However, somewhere along the line of a player going from normal to high-risk their level of interest and activity goes up. Some get curious, some get concerned and some just want to know more.

 

And, in fact, we do see that these players are just as active as the high-risk ones. They click around in the interface, examine every bit of information, complete self tests, setup limits, answer surveys and so on. Here is our chance to meet that curiosity, to face their concerns, to provide answers to their questions.

 

Also, this is the group that most urgently needs prevention. It is important to keep in mind that the increased risk player is not necessarily a problematic gambler. In many cases these are the customers an Operator wants. They are active, they are engaged and they play a lot. They are good for business – as long as they stay out of high-risk zone.

 

MEET JOHNNY AND WILMA

One way of understanding the increased risk players is to look into their risk behavior and how it changes over time.

 

Let us explain by introducing Johnny. He is a young, easy-going person that recently started playing online-poker. And he likes it, he likes it a lot. He is learning the rules quickly and winning more and more games. Increasing his bets. Playing longer hours. Staying up late at night. His risk level goes up in just a few weeks.

 

Johnny is not familiar with problematic gambling. He has heard stories of people gambling away their homes, kid’s savings accounts, employers money but that wouldn’t happen to him, right? Johnny would most likely say that he doesn’t have any negative feelings about his gambling.

 

So what does Johnny need? He needs to become aware and convinced about the risk that is associated with his gambling behavior. Exposure of the information is crucial since Johnny is unlikely to search for it himself, he simply does not know what to look for.

 

She knows that she has spent more money on gambling than she ever intended to. Late nights with bingo, long sessions with lottery ticket after lottery ticket. One day she decided that enough is enough and her risk level decreased.

 

What does Wilma need? Well, one thing that Wilma probably does not need is to begin receiving promotions, bonuses and commercials from her gaming company once again.

 

IT IS A COMPLEX ISSUE

The Operator’s marketing team sends out a message that gambling is fun. The selling point being a moment of entertainment, or a dream of the next big jackpot, or the skill of betting on the winning team. But at the same time responsible gambling means taking into consideration that too much of that fun can lead to problems for some players. A marketing message that is appropriate for a low risk player might backfire if the player has an increased risk. The same goes for a promotional banner on the operator’s game site or an appealing headline in a promotional e-mail.

 

We know a lot about the high-risk player, but now we must challenge ourselves to get to know the increased risk player.

 

A first step is to take into consideration the player’s risk level in all forms of communication, throughout all communication channels and within all touch points where a player meets the gaming operator. To succeed with that, the increased and high-risk players cannot stay a headache of the CSR-department alone. The risk level must influence the whole chain within the organization, from game design, marketing and user experience to management and business development all the way to customer support.

 

So, what was our answer to the CRM team that day? Simply this: That in some cases, they should stop sending promotions even before they turn high risk.

prevention_playscan

Players do not become high risk overnight and there are more than enough chances to intervene

 

 

New features in Playscan 4.2: consumption history

User research shows that players are concerned about keeping their gambling under control. An important aid for that is to let the player know how much time and money he or she spends on gambling. Playscan’s new feature will help players keep track of their spending by presenting charts on actual consumption of time and money.

 

Players can view their results, time spent, and monetary transactions on gambling and directly see patterns and trends. This allows them to get an aggregated view of their habits, and the opportunity to make informed choices about their gambling.

 

The feature is integrated into Playscan but can also be placed outside of the Playscan interface, as an add-on.

 

– Transparency is the absolute foundation in responsible gambling. Players ask for this information time and again, and it is our obligation to answer. I am pleased to have this feature in Playscan, and I’m thrilled for the positive response we’ve had from operators, says Henrik Hallberg, CTO Playscan AB.

More highlights with Playscan 4.2:

  • Activation page with higher click-through.
  • Simplified navigation.

To learn more, pop us an email

 

A shorter Self Test: Does not increase completion rate

Summary: Shortening the 16 statement Self Test within Playscan yields negligible improvement in completion rates. The length of the test is not a problem; players either drop off during the first couple of questions or complete the test.

 

A recurring concern about Playscan has been that 16 statements to consider in the Self Test may be too many. The player may grow impatient and abort the test, especially since the questions themselves can be sensitive and draining. We investigated whether a shorter introductory test with “gate questions” would increase the completion rate of tests.

 

When a player clicks into the Self Test, an introductory text is displayed. Here, the player is encouraged to consider all gambling, at all gambling sites, during the past three months. The player is then asked to consider 16 statements, one at a time.

 

playscan_selftest1

 

To investigate the usefulness of gate questions, the results from the Self Tests at Svenska Spel between 2014-07-04 and 2014-10-14 were analyzed. Statistics of these are presented below, showing the completion and drop-off rates.

playscan_selftest_drop_off_rate

 

Looking at the numbers, the completion rate is quite satisfactory; in particular 80% web completion. This high number is likely due to the curiosity that brought the player to Playscan in the first place, and the promise of self-assessment at the end of the process. Self tests in general tend to have a higher completion rate than surveys thanks to the intrinsic motivation behind doing them.

 

The majority of the players who drop off do so at the first question. We also see a difference between channels with a 10% drop-off rate on web and 23% on mobile. The higher drop-off on mobile is hardly surprising, given the users’ attention span in the mobile context.

 

Only 10% of the started tests are dropped between question 2 and 16, regardless of channel. Interesting to note is that the drop-off rate declines as the test continues.

 

This leaves us with a clear answer to the question of gate questions. We would have yielded only 4% more completed tests if the test consisted of four statements. This number is hardly worth chasing at the cost of the players spending less time contemplating their gambling habits or missing out on the nuances that the full 16 statements bring.

 

———

 

 

The research done at Playscan is not academically focused, but aimed at practical application.
We are pragmatists, knee deep in data to explore. Our mission is to help prevent problem gambling rather than to study it, so we spend our time chasing preventive effect wherever we sense it.
We value agility and adaptation.
Where the territory is uncharted, our guiding light is curiosity and making a difference. Our data is local. We sometimes see wildly varying player behavior between operators, not necessarily because the players are different, but because contexts and presentations are. We believe that the research community has lots to learn about the importance of things like wording and design, and what we say will often be framed to show this. Our findings reflect the everyday player experience. This is neither universal nor static. It can change and, more importantly, can be changed.
At the same time, we have the deepest respect for formal research and academics. We welcome critique of our findings, and hope that others find inspiration and ideas to bring into the academic world.  We are happy to help, and love to exchange experience and ideas. Give us a call if you would like to help out!