Lessons from the casino industry on engagement metrics and lifetime value

Great book covering the modern casino industry
I recently stumbled on "Winner Takes All," which is a great overview of the modern casino industry starting with Steve Wynn, Kerk Kerkorian, and Gary Loveman. It starts out mainly talking about the amazing vision of Steve Wynn, and how he was able to create some of the world's more expensive and opulent casinos, including the Mirage and the Bellagio. In it, they also talk about a bunch of techniques that the casinos use to maximize on revenue, including vertical integration, in which they build "cities within cities" at a casino, so that you can eat, sleep, shop, entertain, and gamble all without leaving a single complex.

(scroll below for more)

Harrah's, the casino run by quants
The big story for me was the formation and operations of Harrah's, which mostly constituted lower-tier casino boats for much of their history. They were decidedly unglamorous, and seemed uncompetitive to the entire high-touch Vegas scene. Think of them as Wal-Mart of casinos, versus Wynn's Prada of casinos. Whereas the Vegas casino scene was very focused on "art" and the creating massive experiences, Harrah's was run by the numbers and very methodical about how they grew their business.

Harrah's eventually became the largest casino company in the world, and is led by Gary Loveman, who got his PhD in Economics from MIT. And they grew their business like a business run by a quant. Here were the major steps they took, as outlined from the book:

• First, they created a loyalty card to centralize identities and create consistent experiences
• They created a granular calculation of LTV for their customers
• Then, Harrah's segmented their key clients based on usage, and then based on "lifecycle"

All in all, a very interesting approach - I jotted down a couple notes as I was reading the book, and wanted to share some of these thoughts below:

Building a single identiy - the loyalty card
Unlike on the Web, it's not easy for businesses to keep track of their customers - this becomes a big problem in an industry like gambling, where a small % of your customers make up a big % of the profits (aka, these guys are the "whales"). So if a gambler went to their regular Harrah's casino, people would recognize them and they'd get differentiated service - but if they went to a different Harrah's, for example on vacation, their history didn't follow them. That way they couldn't differentiate between the $100k spender versus the casual looky-loo, which was bad for business.

So Harrah's introduced a series of loyalty cards called Total Rewards, which were used for "comps" and other free stuff. For the games folks out there, notice that you can "level up" as a member from Gold, Platinum, Diamond, Seven Stars, and for one member - Harrah's "best" customer - there's a Chairman's Club card. They go so far as to fly you around, give you free hotel and accomodations, and other great perks.

This loyalty card gave them the underlying data which they could now use to drive the other parts of their data strategy.

LTV on a per-user basis
The next step once they had all this data was to create models against the lifetime value (LTV) of their customers. This was done in two ways - first, you can imagine a visit to a casino, where a customer comes in, plays cards/slots/whatever, and then leaves. Based on their actions, a "theoretical win $" is calculated, which is an expression of what the casino should expect to get from that person. Combining this number and other services consumed and comps, you end up with a net profit calculation. You can imagine that this number is a rolled up view of:

• How much money that person brought with them
• What games they played, in what mix
• How long did they play for
• What other services did they consume
• etc.

Once you can value an individual session, then you can also chain together multiple visits to calculate an aggregate value. This means that you can now tell the approximate difference between a rich customer that visits every July 4th, once a year, versus someone who plays frequently but also spends less money.

Targeting based on customer lifecycle
Josh Kopelman from FirstRound Capital recent wrote a great blogpost called Lifecycle Messaging that I'd encourage you guys to read. It basically talks about the lifecycle of a customer, and how you want to send them differentiated messaging based on what stage they're in.

Harrah's did exactly this - once they had the ability to model out a customer's LTV, then when new customers arrive, you can start to put them into buckets of profiles that are already "like" them, in order to predict future LTV. Then based on LTV and their stage in the lifecycle, you can start to do some very interesting things: For new high-value customers, they can try to engage them quickly and get them highly personalized service right away, so that they'll stick. For low-value customers who don't fit the Harrah customer profile, it may be better to ignore than group than spend too much cash chasing it.

One of Harrah's most profitable customer segments turned out to be older, retired gamblers who came by very often, and mostly played slots. They called these guys Avid Experienced Players (AEPs) and targeted this group for both new customer acquisition as well as retention. This group was not the "whales" of the Vegas casinos, but had a similar financial heft to the company.

Conclusion
There's a ton to learn from external industries, and I'd like to add casinos as an interesting place to extract lessons for Web entrepreneurs. It has an interesting blend of quantitative data, in gambling transactions, as well as the qualitative, which drive the emotions behind why people prefer the Bellagio to other hotels. It's one of the industries that is at a fascinating intersection of both, and like the social web, you need both perspectives in order to thrive.

Comments

[JP]

Thanks for the post Andrew.

Thinking about this model within the web world for a moment, how do you see the model fitting in subscription based web-business? Take for example Major League Baseball's Online Service (provides 12,000 baseball games a year online). There was a great Fast Company article (http://tinyurl.com/2fozwk) last month about this $500 M a year business.

A few initial factors stuck out to me. I will use the three supporting points you make for organizing my comments.

In subscription businesses:
1. Customer segmentation to gain a greater share of wallet comes later (if ever). Major League Baseball just added a $3.99 feature for mobile highlights to their $89.95 yearly subscription. They are 8 years into the business. Your customers are already "in the casino for the year". Retain them.

2. LTV is less about what a customer spends in aggregate sessions over time and more about their viral coefficient (how many additional members do they bring to your business). Identify "connectors" (to use Gladwell's language). These connectors may even be worth paying to participate.

3. Lifecycle points are more internally (business) determined. Each year there is a make or break point when members decide to renew their membership. Consequently, interaction with your customer is focused on delivering upon "one event" as opposed to several key moments.

Would love your thoughts...

[Q dub]

Great post! I'd add that for online businesses, LTV is further complicated by a user's role as a net-promoter and a content creator. Otherwise, LTV should be easier than ever for online businesses vs offline--you have direct access to customer demographic and value data, and creating differentiated outreach is easy as pie.

Problem is, given the state of the web today, we're still struggling with finding value, period. Segmenting by non-existent LTV may be a moot point for many startups.

[James Hall]

Along this train of thought, I came across this blog http://headrush.typepad.com/creating_passionate_users/2007/01/add_a_little_mo.html by Kathy Sierra a while ago. It is about the Serendipity curve and the effect of random reward in a product. I have read other articles that attribute it to the success of gambling.

[casino insider]

unfortunately you (like so many others) have been snowed under by the harrah's hype machine

mr loveman and his gang certainly talk a great game... but their results never match the hype

this is why during the entire tenure of mr loveman as coo and ceo of harrah's, harrah;s financial results -- the data that actually matters -- massively lagged all of harrah's presumably less-sophisticated peers (e.g. MGM, Penn, Las Vegas Sands, Boyd et al).

and the data sifters that matter -- wall street and other financial traders and analysts -- noticed, big time. and despite that the media and some silicon valley types swoon over loveman and harrah's story, harrah's stock price massively lagged all of its presumably less-dazzling peers. in fact, harrah's was the worst performing large casino operator stock of the the last ten years. (that is, had you invested in any other large casino operator stock -- e.g. MGM et al -- you would have done vastly better than had you invested in harrah's.)

and of course harrah's was bought out and taken private by TPG and Apollo, two super smart private equity firm who never -- never -- buy out market leaders (because they are either fairly priced or overpriced.) no TPG and Apollo make money by buying out laggards and fixing them. and sure enough, immediately after the harrah's buyout deal was announced, essentially all of loveman's senior team rode off into the sunset.

of course mr loveman is still there, but heck, its the highly regulated casino industry, and most industry observers agree that the deal would never have been approved by regulators had the company been delisted AND switched CEOs at the same time...

[Niki Scevak]

Excellent analogue Andrew. Another fantastic one for online advertising are the credit card companies and how they run their businesses.

They are also one of the largest spenders on direct mail (closest equivalent to direct response display advertising offline)

Jay Weintraub always has excellent posts and here is one on credit cards: http://www.jayweintraub.com/2008/04/new-strategies.html

[Douglas Galbi]

LTV value calculations are a good tool, but they tend to place in the background the "social value" that's central to a lot of new internet businesses. So perhaps you and others who know a lot about social software have some knowledge that you in turn can share with casino business folks.

Perhaps gambling in casinos is highly individualistic. But I'd guess that participants prefer the room to be crowded but not too crowded, and to have some beautiful people who are part of the crowd (not just marked performers). Playing games with others who one finds interesting and fun, word-of-mouth marketing, the negative social value of particular personality characteristics (dour, whiny, griefer) might also be factors with business significance to casinos but that might be overlooked in an individual LTV calculation. Someone in the business should be able to get some data and do some analysis for insight into the quantitative significance of these social factors.

[Rajat Garg]

LTV is more useful when it is tied to customer lifecycle and aggregated by channels (or, whatever is applicable to your business)

e.g. Online retailers think about LTV over 3 year period vs less than 6 months in some other industries.

Also, if you are looking at LTV from an aggregate say, marketing channel acquisition perspective, then you can understand which channels are better e.g. sponsored links or some biz dev partnerships work out better than coupon/deals websites.

Regards,
Rajat Garg