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The Business of Social Games and Casino

How to succeed in the mobile game space by Lloyd Melnick

Month: January 2016

Why Excel is just as bad as Powerpoint

I have written a couple of times about the dangers of using Powerpoint too much but Ron Shaich, CEO of Panera Bread, beat me to warning people about the dangers of Excel. I have no problems with the quality of Powerpoint as software but it often prevents people from actually thinking and having a conversation, to making meetings one-directional.

Slide1Shaich’s post, Stop Managing from the Spreadsheet, shows how too many executives use Excel to replace thinking. Given that many of you have recently finished, hopefully, your 2016 planning cycle, you are probably well aware of the central role spreadsheets take in the strategy process. Many of you have probably spent hours (or days or weeks and maybe even months) studying spreadsheets to see trends in your business. Shaich points out, however, these spreadsheets will not prognosticate the future but just help guide you in the right direction.

Just as every investor has been warned hundreds of times, “past performance does not guarantee future returns,” the same holds even more true for your business. Look at Farmville. For many years, it was growing 20 percent or more year over year. By seeing these trends on your spreadsheet, you would take that information and then think of a way you can add five percent to the growth. What the spreadsheet is not telling you is that the majority of your user base is about to shift from Facebook to mobile devices to consume entertainment and that Supercell is launching a game called Hay Day on those devices. If you just looked at the spreadsheet and your Farmville numbers, you missed a seismic shift in your business. Not until you see the next spreadsheet with a 25 percent drop in revenue do you take action, thus fighting a defensive battle rather than taking steps to pre-empt the competition.

Shaich makes a good point that people rely on Excel because they feel it reduces risk. As he writes, “The future is filled with uncertainty and no one likes uncertainty. Uncertainty implies risk, and we all seek ways to minimize risk. The hard numbers of the spreadsheet make the future seem more certain. However, a spreadsheet is only one possibility of the answer, not the answer itself. A spreadsheet is merely a way to organize data. Its numbers generally capture trends of the past, but it is in no way predictive of what’s to come.”

Solutions to the Excel problem

One solution to this problem, which Shaich recommends, is building ranges for the future into your spreadsheets. Use the spreadsheet to not only predict the outcome, but show what could happen in a positive and a negative case (I hate the phrase best and worst case, because I have seen things get a lot better or worse than people ever would have imagined). You can then plan for different possibilities.

I would add an important remedy to the Excel problem is using more qualitative data. One thing many analysts and executives forget is that qualitative data is still data and should be built into your decision-making. It represents additional data, and I have never seen a model where more data is worse than less data. Thus, the spreadsheet may look great for Farmville, but if it looks like an old game that you no longer want to play, that is an important data point also to take into consideration. In 2013, I wrote about the value of qualitative data in LTV calculations and noted that Billy Beane, the father of Moneyball, had also expanded his scouting department to generate more qualitative data.

Although Shaich does not touch on it, another risk with Excel that you must avoid is changing the numbers to prove your strategy. Too often, when the future does not look positive, rather than struggling to come up with a strategy that addresses the reality, numbers in the spreadsheet are “adjusted” so that the future is more positive. Most of you will realize that changing the spreadsheet does not change the results of a strategy and that the problems you need to address actually may become more severe the longer they are neglected (or “adjusted”). As I wrote in Changing the Numbers does not Change the Reality, “you will only see the benefits of being a data driven company if you look at the numbers objectively and let those collecting the numbers use their best efforts to create accurate analysis.”

Key Takeaways

  1. Spreadsheets too often replace thinking when developing a strategy.
  2. Spreadsheets do not predict the future but are just a guidepost with various potential outcomes.
  3. To avoid the Excel problem, create ranges of projections, incorporate qualitative data and look at the numbers objectively.

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Author Lloyd MelnickPosted on January 27, 2016January 26, 2016Categories Analytics, General Social Games Business, General Tech BusinessTags Excel, Ron Shaich, spreadsheetsLeave a comment on Why Excel is just as bad as Powerpoint

Bayes Theorem Part 7: Kim Kardashian

I have written several times about Bayes Theorem and its application to social and mobile gaming but the reaction to the Kim Kardashian game from Glu reminded me how often it is neglected. Bayes Theorem calculates the probability of something happening based on conditions related to the event, prior probability. The importance of Bayes Theorem is that it takes into account the underlying probability of an event happening so that you are not weighing too heavily a local data point or discrete test (you can see the actual formula in my original post).

Slide1

To illustrate, assume you are trying to determine the chance of a Libertarian candidate winning the US Presidency. You may look at the candidate and see how he checks all the right boxes and could be appealing to the mass market. Based on this information you may think he has a 20% chance of winning. But then if you look at the data of third party candidates overall in the US winning less than 1 percent of elections, you understand that even the strongest candidate at best would have slightly better than 1 percent chance of winning an election.

Reverend Thomas Bayes and Kim Kardashian

Bayes Theorem provides a useful point in not only looking at the success of Kim Kardashian: Hollywood but also applying it to your business. For those not aware, Glu Mobile launched a social/mobile game in 2014 centered around Kardashian. The game was a tremendous success for Glu, with over 35 million downloads, and helped them raise over $125 million in capital.

What is interesting is that this success has created an entirely new category, with multiple companies trying to replicate it, and this is where Bayes’ Theorem becomes important. Glu has signed other celebrities, including Britney Spears, Katy Perry and Nicki Minaj. Demi Lovato is doing a game with Pocket Gems. Rovio develoed a Shakira game. Moreover, virtually every game company and definitely every talent agent is trying to get into the celebrity mobile game business, driving up the cost of using such talent dramatically.

The problem with this approach, however, is that the game companies are neglecting Bayes’ Theorem. Most people inside the game industry agree that 80-90 percent of all games fail (by fail, do not get to ROI positive ad spend and fail to make a profit). This metric is not simply for start-ups but if you look at the major game publishers (Zynga, Kabam, King.com, etc), they deal with the same reality.

Just as having a great candidate for the Libertarian Party does not significantly change the odds of winning the election, Bayes Theorem shows that having a celebrity front a game does not significantly improve the odds of the game being successful.

Back to the Kardashian case, even with an 80 percent chance of failing, there is a 20 percent chance of success. Just because one product, Kim Kardashian: Hollywood, fell into that 20 percent you should not infer that the probability changed.

What it means for your game company

First and foremost, a celebrity does not guarantee success. Rovio’s Shakira game has already failed. Even the Kardashian game is no longer among the top grossing. Thus, a strategy based on celebrity games that does not rely on all of the games reaching Kardashian levels.

Second, everyone knows about the celebrity thing. If it was that easy to make a top-10 game by working with one, the top 10 games would feature celebrities. With so many companies using celebrities, a celebrity will no longer differentiate your product or company. You need to build a product and company strategy that creates a defendable position and compelling value proposition to your player.

Third, you need a good game. A celebrity can lower your user acquisition costs and potentially increase the number of organics, but if the game is not compelling all these new players will not monetize and leave. That does not create any value for your company.

Most importantly, structure the deal to reflect the reality the game probably has at least a 75 percent chance of failing. I know my licensing friends won’t be happy with me, but you need to limit your risk in the deal. With the success of Kim Kardashian: Hollywood, many stars are expecting seven figure royalty guarantees. While you probably do not mind paying millions if you have a top-10 hit, writing a big check for a game that has failed is very painful (and potentially bankruptcy inducing). Structure deals where you and the celebrity share in the upside but you do not bear all the risk. The good news is that and their agent probably are not familiar with Bayes’ Theorem so only expect a success, so they may be open to a revenue share.

Conclusion

Most games fail, so while a celebrity may help it is not a golden ticket to a top-10 game. You still need to deal with the underlying reality that it is a hit-driven business. Thus, it is important to manage your risk if you use a celebrity and build out a robust plan for success.

Key takeaways

  1. Bayes’ Theorem shows that the underlying probability of an event happening drives the likelihood of the event happening, despite changes in the immediate situation. For gaming, as 80-90 percent of new games fail, basing a game on a celebrity will only marginally improve those odds. Thus a game with a celebrity is probably 75-80 percent likely to fail (not formal numbers, just estimates).
  2. Do not build a strategy around the assumption that a celebrity face for a game will make the game a success, you need to still create a product strategy that builds a competitive game.
  3. Structure your deals so that the celebrity receives the bulk of their royalties if the game is successful, so you are not forced to pay millions for a failed project.

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Author Lloyd MelnickPosted on January 20, 2016January 22, 2016Categories Bayes' Theorem, General Social Games BusinessTags Bayes' Theorem, brand, branded social games, Glu Mobile, IP, Kim Kardashian2 Comments on Bayes Theorem Part 7: Kim Kardashian

Get my book on LTV

The definitive book on customer lifetime value, Understanding the Predictable, is now available in both print and Kindle formats on Amazon.

Understanding the Predictable delves into the world of Customer Lifetime Value (LTV), a metric that shows how much each customer is worth to your business. By understanding this metric, you can predict how changes to your product will impact the value of each customer. You will also learn how to apply this simple yet powerful method of predictive analytics to optimize your marketing and user acquisition.

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Lloyd Melnick

This is Lloyd Melnick’s personal blog.  All views and opinions expressed on this website are mine alone and do not represent those of people, institutions or organizations that I may or may not be associated with in professional or personal capacity.

I am a serial builder of businesses (senior leadership on three exits worth over $700 million), successful in big (Disney, Stars Group/PokerStars, Zynga) and small companies (Merscom, Spooky Cool Labs) with over 20 years experience in the gaming and casino space.  Currently, I am on the Board of Directors of Murka and GM of VGW’s Chumba Casino

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