Lifetime Value Part 11: How to calculate LTV

Last year, I published a series of posts on the importance of knowing your users’ or players’ lifetime value, the key components and how to impact them and techniques to increase the accuracy of your customer lifetime value (LTV) predictions. I intentionally did not publish a formula for calculating LTV—while it is always a factor of retention, monetization and virality—as it is different by product and there are many alternative ways to get to an accurate customer lifetime value. Prompted by an infographic that I came across (see below) I did want to go into some details of the mechanics of calculating LTV.

The first step is to obtain your key variable metrics as averages across all users. The ones I prefer are ARPDAU (average revenue per daily active user), day 1 retention (how many people who use or install your website, app or game come back the next day), day 30 retention and k-score (how many free/organic users does a user bring in). Continue reading “Lifetime Value Part 11: How to calculate LTV”

Why e-mail is still one of your most effective channels

Email icon

While growth hackers are continuously looking for the sexy, new trendy way of obtaining or reactivating users, they often neglect one of the most effective methods: e-mail. A recent article published by McKinsey & Co., “Why Marketers Should Keep Sending You E-mails,” makes a strong case for e-mail marketing. In fact, the article shows e-mail is 40X more effective to acquire users than Facebook and Twitter combines (though maybe 1/40th as cool). The argument is very consistent with what I wrote about Bayes’ Theorem: The underlying baseline data is very powerful in driving results. In this case, the “40X more effective results” assertion states that about 91 percent of US consumers use e-mail daily, and that e-mail prompts purchases at three times that of social media with an average order value that is 17 percent higher than from other sources. Given e-mail’s power to improve your user-acquisition efforts, there are three keys to making it a successful channel.

Focus on the customer journey

Understand the recipient’s journey from the time they receive your e-mail to the final desired action. This action is not opening the e-mail or clicking on a link but it is potentially installing an app, making a purchase, etc. While it is good to optimize every part of the e-mail, from the subject line to the images to the copy, you should focus on optimizing the entire customer journey. Once they click on a link in the e-mail, do not stop optimizing. Rather than taking them to a generic landing page, keep their experience consistent with what persuaded the user to click on the e-mail in the first place. And ensure the experience is just as good on a mobile device, given that 45 percent of all marketing e-mails are opened on a mobile device. According to Google, 61 percent of users are unlikely to return to a mobile site they had trouble accessing and 40 percent visit a competitor’s site instead. Continue reading “Why e-mail is still one of your most effective channels”

How to generate growth through referrals

With the ever increasing costs of acquiring users (either to a game, an app or a retail establishment), the ability to acquire users by referrals becomes increasingly important engine for growth. Jason Bosinoff, an engineer at Airbnb, one of the fastest growing tech companies around, recently posted about how it built its successful referral program.

Airbnb referral screen

Not only does a referral program help you get users, it generates users who usually have a very high lifetime value. This happens because word of mouth is a very directed user acquisition channel, people will refer a product or game only to friends they believe are likely to value the product.

Airbnb’s referral program is pretty straightforward, with both the sender and recipient getting $25 travel credit when the invited user completes their first trip (or $75 if the recipient hosts). One of Airbnb’s keys to success is that users can send and accept referrals on all platforms (web, iOS and Android), a lesson many game companies would be smart to replicate.

According to Bosinoff’s post, there were five steps to creating the successful referral program:

  1. Know what success looks like. The first step is to define success. What metrics are you trying to impact and what would represent a positive result. Create three cases: good, better and best.
  2. Measure. Integrate robust analytics into your program so you can constantly be tracking how you are performing versus the success metrics that you have set. You want to be tracking everything on the customer journey from when they first see the prompt to create a referral to when the accepter rates their experience after using your product. Airbnb built a rich logging taxonomy of over twenty user events that happen during the referral invitation and sign up journey. With this tracking in place they could follow an invitation from invite page impressions to referred users’ making bookings or becoming hosts. They could then easily review an metric or view it graphically.
  3. Test and improve. You then want to test the product on a subset of your user base. This testing both allows you to improve the stability of the referral program and think of additional functionality that could improve metrics. Some functionality that Airbnb added during its testing process included personalized referral codes and landing pages as well as customizing the experience based on what the user clicked to enter the experience.
  4. Go live. Launch your referral program and compare with the results you targeted in step 1. As your analytics are implemented across the product, you should easily see how you are doing compared with plan.
  5. Iterate, iterate, iterate. Compare the analytics you are getting with the plan you established in the first step. Where you are trailing your projections, optimize the referral program to overcome the weakness. For example, if you are seeing fewer invitations per user, increase the incentive for using the program. If you are seeing too few senders, increase surfacing of the program. If you are seeing a weak acceptance rate, change the copy of the referral or increase the benefit to the end user.

Continue reading “How to generate growth through referrals”

How startups should use metrics

I recently came across a fantastic presentation on startup metrics by Andreas Klinger. It is embedded below but given its length I wanted to highlight the key takeaways:

  • The biggest risk for a startup is not failing to create a good product with a market; it is having a competitor come up with something a little better. Great example is Lyft, which I am sure is a little envious of Uber.
  • There are four stages for a startup to succeed. The first is discovery, generating the product idea. The second is validation, making sure the market wants the product. The third is efficiency, being able to supply the product cost effectively in quantity. Then there is scale, delivering the product to millions.
  • To look at it from the user perspective, there are two key elements: finding the product the market needs and then optimizing (the former encompassing discovery and validation, the latter representing efficiency and scale). To find a product the user needs, you need to understand these needs and create something that will be sticky (i.e., that they will return to) and viral (they will talk about). To optimize, you then need to build out the right revenue model and level, and then scale.
  • According to Klinger, 83 percent of startups are in the discovery phase (empathy, stickiness and virality) while most analytics are around revenue and scale.

    Andreas Klinger
  • A/B tests, funnels, referral optimization, etc., are about optimization, not innovation and cannot replace creating a great product that people want.
  • There is a way to get product insights from data to create that innovative product and you can do it with a much smaller number of users. They key is looking at whether people stay on your site or in your app, in other words, whether they are hooked.
  • Focusing on improving metrics creates a false positive, you can always improve ad conversions or funnels but what looks good for investors does not necessarily improve the product. You may be converting or funneling the wrong users.

Continue reading “How startups should use metrics”

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