Archives For LTV

I am a huge proponent of using analytics and other metrics to drive business decisions, but I repeatedly see people making a huge and avoidable mistake. Instead of using the data to determine the best strategy, they use data to justify their intuition. A good analyst can use data to draw virtually any conclusion and if the analyst is pushed in a certain direction by the business leader, all the data does is provide people with cover for the decision rather than leading you in the optimal direction.

The same situation applies to financial analysis. I have seen people frequently manipulate numbers, often with the approval or even encouragement of the target audience, to tell the story people want to hear. I have seen this manipulation in sales, in corp dev and in internal forecasting. In all situations, it is actually just a rationale to make a decision the person already wants to make.

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Data manipulation

The first part of the problem is manipulating the data. I am not talking Enron here, but more subtly and maybe not even intentionally. People will often select the data that supports their position while discounting the other information. If you want to greenlight a certain feature, you may look at the impact on retention while neglecting the impact on monetization and rationalize it by saying it is a retention feature. Regardless of whether it is a retention or monetization, your goal is to optimize lifetime value (LTV) so you need to look at the data holistically.

Another way to manipulate data is to only look at certain cohorts. If you are deciding whether to invest further in a project, you may focus on your best users and make the argument that you scale that particular cohort you will make $500 million. The problem is you are looking at a small group that is not indicative of performance at scale. This type of manipulation is particularly prevalent when companies are pursuing investment or a sale. It overvalues the metrics the game will have at larger numbers and thus justifies a higher valuation.

Another area where you can manipulate data that is close to my heart is LTV. I have written many times how central LTV is to the success of the product and how it should drive user acquisition. Because of its importance, however, there is a large incentive to manipulate this metric. If you calculate a higher expected lifetime value, it justifies spending more on user acquisition. It could also mean the difference between keeping a game live and sun-setting it. As it is such a complex forecast, it is also easier to manipulate. If you change the expected life of a user, or the monetization curve, that would have a major impact on expected lifetime value (remember, lifetime value is a forecast, not a calculated result). So if an analyst is pressured to change the projection of how long a user will stay with a product, they can change the entire LTV projection.

There are many other areas where metrics can be manipulated, from virality (who is counted as a viral user versus an organic user) to retention (are you counting users separately who play the same app on multiple devices) and even monetization (are you using gross or net numbers, are you forgetting chargebacks, etc.) and the purpose of this post is not to provide a framework to manipulate data. The important issue is identifying ways that data is being manipulated, either intentionally or unintentionally, and then removing those biases so you can again let data drive optimal decision making.

Numbers manipulation

Analytics are not the only area open to manipulation, as spreadsheets and other financial reporting are frequently “adjusted” to provide the results people want rather than the information they need. Spreadsheets have an aura of objectivity but they are just as easily manipulated as a Word document. Sales projections, whether for investors or management, might increase by 10, 20 or 100 percent not because the business environment has changed but because they need to tell a different story.

In corporate development (especially M&A initiatives), where companies are risking millions or even billions of dollars, this same type of manipulation is common. If the selling company cannot make a good case for the sale, they adjust their projected numbers. This, however, is easily seen through and expected. The bigger problem is when the acquiring company really wants the deal to go through (either for personal reasons, ego or any number of external motivations) they too adjust the numbers to make the synergies look better (e.g., cost savings, sales improvements) until those synergies justify making the deal.

Just as I wrote with the issues of data manipulation, this should not be taken as an exhaustive list of manipulation of numbers (nor a roadmap) but as a warning of why spreadsheets should not be considered gospel. It is very easy to change a variable or value (sometimes by accident) that changes the entire financial story.

One of the biggest problems afflicting companies

These are issues that companies are dealing with daily. While virtually everyone acknowledges the strength of analytics and strong financial analysis, they are undercutting the value (or even destroying it) by using the numbers improperly. This puts them in the same position as companies that were not or do not use data.

Conclusion

At some point, you need to decide if you want to use metrics and financial analysis to create a great company or as cover to make decisions you want to make. 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. This is also a cultural issue, as even subtle pressure can impact the data and analysis.

As mentioned earlier, it is not always a conscious decision. You may gravitate to the data or analysis that supports your position or initiative while discounting other data. Unfortunately, this course is just as damaging as you may make sub-optimal decisions. The best way to avoid this problem is by deciding a priori what data you will look at to make the decision and what metrics you need to see to move one way or the other.

Key takeaways

  1. One of the biggest issues facing virtually all companies is the manipulation of data and numbers (either subconsciously or intentionally), offsetting the ability to make optimal data-driven decisions.
  2. With analytics, data can be misused by selectively choosing which data to use.
  3. In financial analysis, decisions are often made based on spreadsheets and analysis that can be made to tell any story by “adjusting” the key variables.

A key to predicting and effectively using customer lifetime value (LTV) is to take a long-term view of your data and not just rely on the first month or even first few days. Many marketers will draw conclusions about a new product launch, a new feature or a unique customer cohort based on the initial data they generate. While you cannot wait months or years to make crucial business decisions, understand that these predictions are less reliable and thus making decisions based on this data is problematic.

The challenges

While intuitively more data is always better, there are challenges involved in looking back over a long period. First among these challenges is customer attribution. If you are determining the value of a specific growth channel, do you credit the lifetime spend of a user to the channel you used to acquire them initially or do you attribute the revenue to a channel (Facebook feed, email, A2U notification, etc.,) that brought the user back after a long period of inactivity.

The second issue is the sheer quantity of data. If you have millions of customers or players and years of data, it becomes quite a challenge to process all of that data. You may have multiple interactions with that user every day, literally for years. Think of how you interact with Amazon and consider they track all the products you look at, how often you visit, what you purchase, what you purchase instead, etc. You need the software, data warehousing and systems so that you can actually analyze this data quickly. Continue Reading…

As this is my nineteenth post about customer lifetime value (LTV), I obviously think it is very important, but I wanted to take some time to provide examples of how it can impact almost any business. Even if the examples do not cover your initiative, they will hopefully help you see how understanding, marketing and designing for LTV is crucial to any company’s success. Examples range from tech companies to business types that have been around longer than the United States. The breadth of companies that LTV is critical for shows its central importance.

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Mail order catalogs

Catalog companies, from the days of Sears and Montgomery Ward, to the current heavyweights like Restoration Hardware and Crate & Barrel, have always needed a deep understanding of LTV to succeed.

With the cost of printing and mailing catalogs, these merchants need an LTV higher than the shipping/printing costs. Thus, they have to first understand different customer segments (e.g., location/postal code, sex, age) and only send catalogs to those people who will have a higher LTV. If they sent their catalog to everyone, the average LTV would decline and make their efforts unprofitable. In addition to understanding the LTVs of each segment they have to optimize along the three key LTV variables: Retention, monetization and virality. If a person reads through the catalog once, makes an order and never picks up the catalog again, it is hard for their value to be higher than the costs of shipping them the catalog. If they, however, keep the catalog and place ten orders in a six-month period, the LTV is likely to exceed to costs of sending them a catalog. Monetization is also critical. If they love the catalog, keep it on the coffee table, but never make a purchase, the merchant loses. Even if they make very small purchases the merchant proposal loses. Successful direct marketing companies succeed by getting larger shares of wallet from their customers. Finally, virality is important even for a non-digital good. If the person shows the catalog to ten family members or friends (who have an equal potential to buy), then the costs of sending a catalog are effectively one tenth as you are reaching 10X people. Continue Reading…

I have written many times about customer lifetime value (LTV), but primarily from a theoretical framework. In this post, I will use Groupon to exemplify many of the key principles at work with LTV. Groupon is very well known, particularly in the United States, as a coupon or discount-deal website that normally offers 50 percent off deals with local merchants, particularly restaurants, spas and similar retailers. Started in 2008, it went public in 2011 and currently has a market cap over $4 billion.

The Groupon problem

One of the biggest issue Groupon has run into the is the perception that most retailers who run Groupon promotions find them highly damaging, and there are frequent stories of Groupon promotions that have put companies out of business. It is easy to see how this could happen, as Groupon typically gives customers a 50 percent discount and then keeps 25 percent of the remaining funds. Thus, a retailer only sees a total of 25 percent of the normal revenue they would from the consumer if the person had made the purchase without a Groupon. Since most retailers do not have a 75 percent margin, they will lose money on the Groupon. Moreover, because of Groupon’s strong distribution, they may lose a lot of money.
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If a retailer, however, understands customer lifetime value, it can make the right decision about the value of offering the Groupon and whether it is a positive to their store.

The importance of retention

The first element of LTV that is crucial to Groupon success is retention. If people normally come to your business once and never come back, the Groupon is not going to work. You will lose 75 percent of the check or bill and never see the customer again.

Conversely, if once you get a customer they come back twice a week for six months, then the Groupon is a great marketing tool. While you will lose money on the initial transaction, you will have 48 (2 times per week, 4 weeks per month for 6 months) more profitable transactions, which will more than cover the loss. As I discussed in my post about retention, retention is the key to success in any business and the Groupon examples shows the impact of weak versus great retention.

How virality plays into the equation

Virality is also a key to the success of a Groupon. If people use the Groupon deal but do not tell friends about it, then the Groupon must generate enough lifetime revenue from that user to be a new positive. While this is possible, it increases the risk that the Groupon initiative is not successful if you do not have strong retention.

If you create, however, an experience that people tell their friends about, and then their friends try your establishment and you can retain them, the value to you of offering the Groupon increases dramatically. I have written before about how to create strong word of mouth, and it is more than just offering a good product, but if you follow the STEPP model (create a product or offering with social currency, triggers, emotions, practical and public) and users bring in more users, the Groupon can have tremendous impact.

Let’s say someone buys the Groupon and comes into your store. Because of the discount the purchase is a net wash and the consumer value is no more or less than the cost of servicing him/her with the Groupon. If, however, the consumer persuades five friends to also visit, and each of those friends adds $20 of profit, then the Groupon has generated $100 in profit for you.

Why segmentation by LTV is so crucial

The other key lesson regarding LTV that is exemplified by Groupon is the necessity for understanding different segments of your user base and how Groupon users fit into these segments. Many establishments (let’s use restaurants for this example) have found out that Groupon users do not fit the same model as their other customers. While they may normally see great retention and virality, Groupon customers just go to wherever they have a coupon and do not revisit or talk about establishments. Thus, a restaurant may normally have a very high LTV for a typical user, say $100, so if the Groupon cost them $50 per user, long-term they would still make $50 from the promotion. However, if the Groupon customer exhibits different traits and only uses the Groupon and never comes back, the restaurant loses $50 per customer. In many ways, Groupons can be looked at as the equivalent of incentive installs in the app space; while there is a role for this channel you must measure the value of these installs differently than other marketing channels.

Thus, it is important to see how the Groupon demographic normally behaves for the establishment. If you expect the Groupon to generate male users with an average age of 25,  with a low income, look at the LTV of that user segment when estimating the impact of the Groupon rather than the LTV of all your customers. Also, do a test (limited number of offers) and get data on how Groupon users perform compared with other marketing channels, and divert your resources where they will have the greatest yield between marketing cost and lifetime value.

It is not about tricking your customer

One thing that you will notice I did not discuss is the common practice of trying to trick users of Groupons into spending more to lessen the cost of the Groupon. You can adjust the amount of the Groupon so the typical session cost or restaurant check is not covered, the user spends more, and you either profit from the Groupon or lose less. This technique ignores the underlying issue that you are trying to build a business with a strong long-term stream of profits. Manipulating customers short term could pay a few bills or extend your runway a month, but unless you address the lifetime value issues you will be left with nothing long-term.

The right decision making regarding Groupons

Despite the popular Techcrunch piece, “WhyGroupon is Poised to Collapse,” Groupon is not a loan shark or other immoral business. Rather it is another marketing tool that advertisers will only use successfully if they understand and can optimize their customer lifetime value. If they have a low LTV, nothing is going to help. Their Groupons will fail, but so will their advertising in newspapers or online (or the guy wearing the sign outside the restaurant). If they can create customers with a high LTV, they will see a long-term positive net return from offering Groupons.

Also notice how monetization is not the key driver here of success. It is less about how much you make or lose on the initial transaction that leads to program success, and more about how well you generate virality (and how good your virality is). Even if you improve your margin slightly, the impact of improving monetization tied to the Groupon will be much less than the impact of the other two variables (retention and virality) .

Key takeaways

  1. Groupon promotions showcase the importance of LTV. Despite negative press, Groupons can be successful if you understand and can optimize your customer lifetime value.
  2. Your Groupon promotion will only work if you can generate strong retention or great virality. If customers come back or tell their friends about your business, then the Groupon will have a positive ROI.
  3. Monetization is not a big factor for Groupon success. A change in monetization may make the program cost less but long term success of the program and your business depends on strong retention and virality.