Casino Gaming Database Marketing Strategies
August 19, 2011 by Stics·
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No Change in Database Marketing Strategies
Another fact we learned from our casino marketing survey was that most casino properties stuck with their existing db marketing strategies, even with the downturn. Basically, we found that:
- Despite the status of the business, almost 40% (39.1%) of properties are not changing their db marketing strategies.
- About a fourth of the industry is simply adjusting their marketing budget. More properties are increasing spending (17.4%) than decreasing (8.7%) marketing spending as a response to the situation.
- Another quarter (26.1%) are mailing different individuals with the same budget.
- Another 8% of properties are dealing with industry situation by buying new machines.
Strategies for db Marketing
The survey revealed that the gaming industry moved toward more tiering.
- 27% used Three-tiered database
- 42% mail 4- 12 tiers
- 12% mail at least 25 tiers
- 19% did not use or not known
Opportunity to improve mailing sophistication
Stics believes there is a lot of opportunity to database market more effectively. Based on the survey results, campaign effectiveness can be improved by:
- Trying new things (because 40% were mailing same)
- More complexity (because 69% were mailing fewer than 12 tiers)
- More Sophistication (only 23% using predictive analytics)
At a high level we know that loyal customers do come back, they just don’t spend as much. The problem is knowing which customer are likely to have more money to spend and how to bring back less frequent customers. Stics can help with that. Stics can unlock the power of your current database to maximize profitability and marketing effectiveness. For more information, call us today. We are here to help.
Casino Gaming Business Performance
June 10, 2011 by Stics·
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More Up’s than Downs for Casino Gaming
We wanted to know how much the overall business performance in the casino gaming industry has changed in the previous year and our survey reveals that there actually has been more “up’s” than “down’s” as compared to the previous year.
More companies have improved in their performance than those who experienced decline; even so, most businesses yielded flat in their performance. This is vis-à-vis last year; so bottom hit for some.
- Things are better in places than expected (30.8% of businesses are up)
- More are up than down (30.8 up and 23.1 down)
- No improvement for bulk (61.6%) though (38.5% flat plus 23.1% down)
Stics offers predictive analytics to help you derive insights from your current data, make better informed decisions, and ultimately, improve your business performance. Call us if you would like to learn more. We are here to help.
MGM M Life Utilizes Innovative Customer Loyalty Program
January 7, 2011 by Stics·
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MGM Generates Complete Customer Profile Across the Brand
In today’s economy, brands are finding new ways to be smart about attracting customers. Las Vegas casinos have always offered marketing promotions and comps such as free drinks, hotel rooms or tokens to keep customers coming back.
None, however, have gone as far as the new customer reward program from MGM Casinos M Life. This new customer loyalty program for MGM has found an innovative way to reward their customers and build brand loyalty.
Rather than focusing solely on customer’s gambling patterns, MGM tracks members of their reward program across all resorts and all facets of their hotels, including clubs, dining, spas, shopping and gambling. MGM then uses this information to offer its customers perks targeted to their personal interests. For more information on the program visit the M Life site or this recent Las Vegas Sun article about M Life.
Stics is pleased to have a number of MGM properties as Stics Predictive Analytics clients. MGM has a very strong marketing organization and they are always looking to improve their marketing strategies and tactics. As marketing optimization experts, Stics understand the complexities in executing multi faceted marketing program and expect the M Life approach to further enhance MGM Casinos revenue retention while building stronger brand loyalty with high value guests.
Casino Marketing Trends
September 3, 2010 by Stics·
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Casino Marketing Survey
Earlier this year, Stics conducted a preliminary research project to gauge the state of the U.S. gaming industry, from a marketing perspective. We contacted both senior level business executives as well as high to mid-level marketing department professionals to learn more about their challenges and perceptions.
Listed below is a high level summary of some of the more interesting observations.
Top 5 Casino Marketing Observations
- Respondents felt their casino marketing efforts were performing well – despite the down economy.
- Direct mail volume of was up by 10 – 20%.
- Marketers put more value on the website and online programs while business leaders didn’t see value in the websites as compared to direct mail and analysis.
- Business leaders are “likely” to “very likely” to invest in new marketing technologies but marketing teams were “very unlikely” to “unlikely” to invest.
- Marketers were concerned about expenses.
While it is obvious that the economy has taken its toll on casino marketers and the gaming industry as a whole, Stics believes that today’s casino marketers are being asked to do more with less. As a result, they are executing on a large number of campaigns to a wider audience. This presents them with the new challenge of how to profitably reach this wider audience.
Stics is currently conducting a more comprehensive study as a follow up to our preliminary findings. We will keep you posted on other interesting facts when they become available.
Stics helps casino marketers reach a wider, more profitable audience through the efficient and effective use of predictive modeling. If you have any questions about predictive analytics for casino marketing, please give us a call. We look forward to speaking with you.
Probabilities and Statistics Pay-Off for Marketers
August 20, 2010 by Stics·
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Conditioning Probabilities
When observing our customers, sometimes evidence can look pretty persuasive and sometimes it can be down-right compelling. And yet, without proper attention to underlying statistical properties in the customer data, you might form an entirely false impression of your customers. It is not uncommon for marketers to ask this question, at least once in their career.
“How did I make such a wrong conclusion from such compelling evidence”?
The answer lies in its numerical underpinnings, what statisticians call “conditioning”. Conditioning can cause you to reach the wrong conclusions and send lots of marketing dollars down the rabbit hole and take you to the Mad Hatters Tea Party.
The unhappy results of conditional probabilities exist in all facets of animal and human behavior. These are typically complex scenarios of layered assumptions, so I am using this simple example, of one type of casino player, to demonstrate how the application of incorrect assumptions can lead to lost revenue and profitability.
Casino Gambler Example
Let’s assume one percent of the casino gamers who played at your property were cheaters. That percentage might be high (Cheaters = 1%), but this is an example after all. Let’s also assume that when a player is a cheater, he or she will decline to fill out a loyalty Rewards Club card application about ninety nine percent of the time. (If cheater, 99% decline application.)
Now comes the interesting part. Let’s say that you see a suspicious player, approach him or her, ask the player to fill out a rewards application, and the player declines. What are the chances that that player is a cheater?
Intuition vs. Reality
Intuition would suggest a high likelihood of cheating. But the reality is different. There is only about a one in thirty-three percent chance that this individual casino player is a cheater. So consider the statistical probabilities before you decide that the player is not worthy of a revenue generating comp or a coupon.
Here’s a table that describes the situation exactly. You have total players showing up in green. In red are the 1% or 100 are cheaters. 99 of those 100 cheaters were not willing to fill out an application, so your test was very good.
Wrong Assumptions Equal Lost Profit
So here is the big question. If someone refuses to fill out an application (the red boxed group), should you refuse to serve them or market to them? The answer is No for the following reasons.
- First, there is only roughly a 1 in 33 chance (more precisely 99 of 3,399) that the player is a cheater.
- Second, there is a 3,330 out of 3,399 chance that they are a good player who will be profitable.
- And finally, these 3,300 players are likely to be even more profitable than reward applicants.Even when making generalizations about customers, it is essential to understand the effect of your assumptions on your conclusions. Especially when formulating policy, it really pays to know your probabilities and statistics.
If you found this interesting or want to learn more about the power of statistics for marketing, feel free to contact Stics. We are happy to help.
How to Tell What Your Customers Want
August 1, 2010 by Stics·
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Past Behaviors: Misleading Facts
When we make guesses about the future, we usually go off past behaviors. But people change their minds frequently. So even if you know what your customers bought in the past, you cannot necessarily predict what they will buy in the future ― from their past behavior alone.
To illustrate that point, let’s look at Bob, Carol, Ted and Alice. We want to know if we should be marketing SUV’s to these people. From our customer records, we know they bought an SUV in the past.
As you can see from the chart, the traditional SQL (Structured Query Language) a
nswer correlates their past behavior with a recommendation to market to these people. But this approach falls short compared to the deeper statistical answer, because it only evaluates a limited set of the available data.
- For Bob, both the SQL and statistical answers are in agreement, telling us that he is worth marketing to because he is an SUV buyer.
- For Carol, the two answers lead to opposite conclusions. Perhaps she no longer needs one because her kids are grown. Maybe it’s something else that changed?
- Both Ted and Alice have some chance of buying an SUV having never done so previously.
- But Alice has a much higher probability of buying one. Perhaps she is starting a family or taken up a new sport that an SUV would be good for. Without statistical analysis, we would not know that Alice is worth marketing to.
Predicting the Future
The better way to make predictions about future behavior is to use a statistical model. A statistical model can take many complex inputs and produce outputs, like the probability of someone buying an SUV in the future.
The important difference here is that statistical models can respond to all the details within your data. This is superior compared to using generalities or segments of your data, like the “previously purchased” example shown above. By using statistical models rather than a traditional SQL approach, your will gain a better view of your customers and better refine your marketing efforts with increased accuracy and profitability.
This is one of the reasons why Stics statistical models improve marketing performance above other methods. Stics can provide customized statistical insight about your customers – and use less time than traditional segmentation models take to make. Plus, Stics has years of experience and the technological tools to quickly and reliably give you the information you need.
Why Data Segmentation Is Not Enough
People Are More Complicated Than Their Data Segmentation Parameters
When evaluating customer wants and needs, there are many ways of looking at data from the sublime to ridiculous. Commonly accepted ways of looking at customer data include generating a “gut feel” from experience, sampling at random,looking at exceptions, reviewing periodic totals, and SQL selection. SQL, the most common tool used by database marketers, stands for Structured Query Language, but what it boils down to is averages or data segmentation. It gives you general information about groups of people, often by age or income.
Let’s say, for instance, that you want to find people that fit a certain category, such as empty-nesters. To use data segmentation to find these people, you might search for people in the 50 – 60 year age range and within a certain income bracket. SQL would look at your data to find the people who fit both of these parameters.
The problem with SQL is that you’re potentially overlooking the right people. In this example, your data segment would be missing all of the empty nesters who are under 50 as well as those who fall outside your chosen income range. SQL is just a fancy way to put people into buckets. The problem is, not everyone you seek is in the obvious bucket.
People are more complicated than just their income or age, but when analyzing populations, you can become trapped by these segmentation tools and rules.
Where Your Customers Really Are
The truth is that you’re not really looking for empty-nesters within certain parameters (shown in brown on the chart) or even empty-nesters in general. You are looking for people who will be receptive to what you have to offer (shown in yellow on the chart).
To find these potential customers, you need to stop relying on buckets and start looking at the bigger picture. And to do that, you need statistics. Statistics can help you find the best people that correspond to your potential customer base.
Predictive Analytics: Better than Buckets
The most effective form of selection would be to use the most information and use it optimally. With this light, predictive analytics can be seen as the clear winner for selecting target prospects or customers.
Predicative analytics looks at the bigger picture of marketing. It has the capability to consider all kinds of factors, rather than just one of two. It also looks at patterns in behavior, and makes predictions about future behaviors. This lets you more accurately pinpoint your potential customers, as well as stop marketing to people who are not interested in what you have to offer.
That sounds like a much more effective way to do business, right? The problem is that you can’t do it by yourself. Predictive analytics is a science, and it can take years to develop accurate predictive models. You don’t want to make the top 10 mistakes a novice with predictive analytics would make. That’s why turning to a reputable predictive analytics provider can save you time and money.
At Stics, we have spent year’s fine tuning our software and processes so our customers get extremely accurate predictions. We can take your data and give you insightful information about potential customers and the effectiveness of future marketing campaigns. With Stics predictive analytics solutions you can make your business more efficient and cost-effective.
The Data Fact Gap: What You Don’t Know Can Hurt You
June 18, 2010 by Stics·
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What the Data Fact Gap Means for You
Fact Gap Graph
As professionals, we all know that technology has changed the way we do business. Whether you find the increased dependence on new technology as good or bad often depends on how effectively the tools are used. Over the years, this problem has been illustrated in many ways by me and by others. This particular Fact Gap illustration was first attributed to the Gartner Group. It will help me describe how data technologies are, on the one hand, progressing and on the other, creating new data analysis problems.
The Data Fact Gap was created by the explosion of available digital information accumulated in recent years. With technology system advances, increased data storage capacity and Internet usage it is now easy to collect mountains of data. While the volume of retained data has grown exponentially and spread across all industries, so have the data management challenges it created and the even greater marketing opportunity that mostly lays dormant.
This abundance of data creates new problems that force database marketers to devote a lot of time and resources to filtering information into data segments so decision makers can frame a concept, problem or question. While this approach is intuitive to the human brain, it does limit our ability to make a fully informed decision from all available data.
Why You Need Good Data
Intuitively we often think we already know what our customers want. However, that is not always the case. When we make business decisions by filtering our data down to a few variables we miss the more accurate and complete view of the data. Without hard data, there’s no way to be sure truly objective decisions are being made. Worse, because we think we’re making objective decisions, we often don’t seek outside an perspective.
What we really need is an objective analysis, wielding as many customer factors and data points as possible. This approach helps us see the potential hidden below the common database marketing analysis.
Statistical Predictive Analytics Solves the Problem
One way to harness the data explosion and make better marketing and business decisions is to use predictive analytics. Predictive analytics uses the science of statistics and is capable of considering unlimited facets of a situation. Predictive analytics for marketing can increase a marketing campaigns return on investment by ten times compared to a typical SQL analysis that might only evaluates about five variables. It takes the data that you already have and give you information you can use in your marketing campaigns, such as:
- Customers you are currently marketing to, who are unprofitable
- High value customers or prospects you are not marketing to
- More profitable marketing programs
- Respective value of various members in your customer base
Statistical modeling with predictive analytics is proven to help make more informed decisions and increase profit margins.
In my business, we live on the front lines of customer data knowledge generation and have a deep understanding of the problems and opportunities created by the data explosion. For that reason, we discourage installing expensive applications that might not provide quick answers to important questions that drive revenue and profitability. We know that with seasoned expertise, a leading statistical technology platform and focused services like ours, it is possible to bridge the data gap and quickly and easily improve the performance of your marketing campaigns.
Stics offers innovative solutions that provide deeper insight into your customer and loyalty database for greater marketing return on investment. We welcome inquiries and are happy to answer questions.
