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Customer Lifetime Value (LTV) is one of the most important metrics when it comes to analyzing customer acquisition strategies.

If you spend less acquiring customers than you make over the long term, you theoretically have a money printing machine.

In most markets it now costs a lot of money to acquire a customer. All things being equal, if you can increase your LTV then you can also increase the amount of money you spend to acquire a customer and this gives you an advantage.

Calculating LTV correctly gets complex so I’ve decided to break this post into series of three digestible parts.

Part 1 – An overview of LTV, links to guides on how to calculate it and examples of campaigns that can increase your average revenue per user.

Part 2 – An analysis of retention and examples of how to increase the retention period per customer.

Part 3 – Examples of advanced segmentation strategies that will help you squeeze extra value out of the examples in the first two parts of the series. I’ll also provide some details on how to effectively implement these campaigns.

 

Part 1/3: Understanding LTV and email campaigns that increase your average revenue per user

LTV = my customers stick around for X periods and pay Y dollars per period.

Unfortunately actually calculating a number that represents your average LTV isn’t as simple as the sentence above.

Fortunately the specifics of calculating LTV have been covered elsewhere thoroughly.

Some great information on the subject:

1. A general thread on Quora

2. Cancellation Rate in SaaS Business Models by Jason Cohen of A Smart Bear/WPEngine

  1. Calculating Your Customers LTV (with code) by Austen Busen over at Startup Foundry
  2. The ‘How To Calculate Lifetime Value’ infographic from the KISSMetrics team

I’m going to refer to the KISSMetrics infographic which clearly explains the logic and maths behind calculating average customer LTV.

For the sake of brevity, I’m only going to pull out the three formulas in question:

  1. 52(a) x t
  2. t(52 x a x p)
  3. m * (r / (1 + i – r)), where m = 52(a) x t

(Refer to the infographic for details on each of the variables)

I’ve highlighted in blue the two common attributes across all of these equations: 

  1. t = the average length of time your customers stay with your product
  2. a = average revenue per customer per period (a month is a pretty standard, especially in SaaS).

All of the variables in these equations are important and often interrelated but for the sake of these posts we’re going to assume that everything except a and t remains equal.

By holding the rest of the variables equal I can provide some examples you can use for inspiration. Whilst they’ll work in most cases you need to think about your own situation and modify the campaigns such that they help youget customers buying the product, or combination of products, that will make you the most profit.

For example, just because a customer buys a more expensive TV or upgrades to a higher monthly plan (a goes up) does not mean that you’ll make more money at the end of the day because p, your profit margin, might go down. Bear this in mind when customizing the strategies below and make them work for you!

With some basics of LTV behind us, the rest of this first post is going to deal with ways to increase a, the average revenue per customer.

As mentioned above, Part 2 of this series will deal with example campaigns that help you increase t, the average retention period.

Increasing average revenue per customer

 

Here are FIVE strategies and example campaigns that YOU can use to increase the amount you make from your customers.

1. Up-sell your customers

Using emails to up-sell or cross-sell your customers is perfect for companies with multiple products or complimentary features.

Here are two approaches that I’ve seen work well for e-commerce stores:

1. In your receipt or thank you emails (post-purchase), include a product recommendation list. There are a growing number of software services that will track your customers’ behaviour and recommend products automatically so you don’t need to hire a data-science team. Here’s an example from ever-amazing Zappos:

Zappos Upselling Strategy

2. Group customers by their purchases or browsing habits and send them a follow-up email featuring a related item that they are historically likely to buy.

Buy.com E-commerce

The example below, from Buy.com, tries to upsell customers interested in cameras on a bundle package with a total of 16 items. Instead of just selling the camera Buy.com is increasing the total revenue earned from that customer by packaging products together.

These two example campaigns work because:

  1. In the ‘real-world’ (offline) sales people often employ this very tactic, recommending add-on products and giving customers discounts on bundles. The net result is a higher average order value.
  2. They can be genuinely useful. Often these sorts of emails provide a form of education. Take men’s fashion: if I bought a suit today and got an email in a few weeks featuring the perfect tie, there is a chance I’ll find the email interesting because it’s actually educating me on which ties go with which suits.

Reviewing your past purchases and customer behaviour and apply the knowledge you have of your product categories to setup similar winning campaigns.

If past purchases showed that customers who bought an LED Samsung TV regularly ordered a Blu-ray player within a month you could use this knowledge and set up an automated email to any customer who purchases a Samsung TV but does not order a Blu-ray player.

Send them the email a week later, include a single call to action and link directly to the Blu-ray player for the best results. The best place to start is your most profitable product category.

2. Pre-empt plan upgrades and ask your customers to pay more

Software as a service businesses generally charge per month, they generally have three tiers and they genuinely have no contracts.

Being a developer first, it’s never been natural for me to act like a salesman but experience has taught me: ask and you shall receive.

There is always a core metric that drives your tiers. In the case of Mixpanel, it’s the number of events you track:

mixpanel

For 37Signals’ Basecamp it’s storage. For HelloFax it’s the number of faxes you send.

Whatever it may be, you should be tracking usage of this metric and using it to send an automated email campaign that gives your revenue per user a bump.

Send an email to your customers when they reach ~90% of the usage for the plan they are currently on. Let them know that they are nearly at their threshold and can upgrade with one click to ensure their service isn’t disrupted in the near future.

In the case of MixPanel they could email users on their ‘Startup’ plan when they reach 400,000 data points for the first time.

This works campaign works because:

  1. People like to have peace of mind that things will continue to run smoothly. They will pay for this peace of mind, particularly in the B2B world.
  2. The customer knows that if they don’t end up hitting the threshold for some reason they can always downgrade – the upgrade will not lock them in. Conveniently, this also means the campaign does not usually have a negative effect on retention.
  3. A powerful call to action can be a big motivator. People usually follow the prompts you give them.

For most SaaS companies, it costs very little more to have a customer on your higher tiers vs. your lower tiers.

This means that the extra money you make from those customers who upgrade is virtually pure profit. 

If you had a SaaS company with a $20/month tier and a profit margin of 40% and a and a $50/month tier with a profit margin of 70% and you get a customer to upgrade to the higher tier three months earlier, that customer would be worth an extra $69 to your business.

Depending on your retention rate and the value of your tiers this could be an extremely valuable increase.

Pro-tip: use extra features to drive upgrades

Sometimes you don’t just use a volume-based metric to differentiate your tiers.

Take SurveyMonkey who provide a number of advanced settings, such as ‘custom redirects’, with their Gold plan.

SurveyMonkey Example

In instances where you have other features available on higher tiers you can setup an email that targets customers who have attempted to access these features or who, based on your analytics, seem likely to upgrade.

In SurveyMonkey’s case the data might show that customers who have been on the Basic plan for at least three months, have designed more than 25 surveys and use the SSL and skip-logic features are the most likely to upgrade to the Gold plan.

Using this information they could setup an automated email that reminds customers they can get these features for just $6 extra per month if they upgrade now.

The general rule to get started is watch what your customers do and ask customers who are near your thresholds to upgrade.

3. Implicitly drive increased usage

Both of the examples above help you explicitly drive an increase in the average revenue per customer by asking customers to pay more per period or transaction directly.

An alternative (or complimentary) suggestion is to implicitly drive customers toward more profitable tiers and products.

In the case of a SaaS products this is generally done by educating your customer with regular emails that help them get more value out of your product.

MixPanel, for example, could send educational emails that explain explain why it’s useful to track button clicks on your landing page. This sort of education would not only inform customers of new ways to use the product but get them tracking more data points. This is incidentally the driver that decides which tier a customer subscribes to: the more data points they track, the more they ultimately pay.

If you have a SaaS product one easy way to do this is to implement a series of welcome emails that go out after a customer signs up (or subscribes).

We have recently implemented a series of welcome emails that do just this. Early results suggest they have increased our activation rate by 30-40% andhad a measurable affect on the number of campaigns customers are creating. This will have a positive affect on engagement and the average revenue per user.

So you can get a head start, here are some of the subject lines I’ve been using.

[Vero] Email remarketing vs. display remarketing by the numbers

[Vero] An email you can send before a customers trial ends that really works!

[Vero] A/B testing isn’t just for your landing page

The goal here is to educate, remember! Don’t just sell your product.

4. Give a discount to new or loyal customers

This is a tried and true example used by e-commerce retailers all over the world.

This example from Rocket GmbH’s The Iconic is sent when a customer joins their newsletter:

The Iconic E-commerce Example

This can encourage a customer who would otherwise spend nothing in their first month to spend something as well as incentivize them to join your email list for future sales and up-sells.

Another application of this concept is to email users who abandon a SaaS free trial with an offer to extend their trial. By giving customers the chance to activate you have the chance to turn them into a paying customer and earn something from them, increasing your revenue per customer.

Given that they would otherwise be worth $0 to your company and that you’ve spent money to acquire them you should make the most of it. Spotify sent me this email  when I first signed up and it’s a prime example:

spotify sales cycle

5. Use social recommendations

I have not seen this done very well in the wild but I’d like to.

We are in an age where we have the unprecedented ability to track connections between our customers, our product and their friends. Social recommendations are a great way to drive action as social proof is an extremely powerful motivator.

People trust their friends.

Outside of e-commerce stores, one instance where this could work is in social games that have in-app purchases. Anything by Zynga, TinyTower, even games like World Of Warcraft could use this tactic. By emailing customers with updates on their friends’ actions and purchases they could likely increase the number of in-game purchases from their customers, increasing the average revenue per user per period.

The best example I have seen is from Twitter. Although it doesn’t necessarily drive ‘direct’ revenue it is a great example of social recommendations via email:

Social Recommendations via Email

Stay tuned

 

Hopefully these examples and suggestions have given you some ideas on how you can increase the average revenue per customer per period, permanently.

Permanently moving the needle on your revenue is a BIG deal.

In the next part of this series we’ll discuss some further campaign ideas to help you increase how long your customers stick around, the t part of the equation, and decrease your churn rate.

When you put all of these ideas together you should be able to increase your LTV and make the investment well worth it.

Put your email down below and look forward to part two of the series next week!

 

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