Lifetime Value as the North Star to Optimize Your Go-to-Market Offers

SUMMARY: The lifetime value North Star and optimization framework help marketers make critical decisions based on maximizing revenue opportunity.

By Arvid Tchivzhel, Nick Truitt, and Matt Lindsay

April 11, 2022


The LTV Framework: Volume, Revenue, ARPU

This blog post summarizes our latest findings on Digital Subscription Offer Optimization stemming from extensive economic modeling and A/B testing of subscription offers and audience segmentation. In this post, we give an overview of the topic and research approach. Additional findings will be shared in subsequent posts on our developing framework for optimizing go-to-market offers and measuring tradeoffs in short-term vs. long-term goals.


Some media companies have adopted low introductory prices with aggressive increases.


Why lifetime value (LTV) should be your North Star

In developing an acquisition and retention strategy, publishers are often challenged with these questions:

  • How do I grow starts who wont immediately churn?
  • What price will get me both volume and revenue?
  • Should I offer free trials or paid trails?
  • What is the right length of time for the intro period?
  • Once the intro expires, what should the full rate be?

These questions all seek to elevate one metric over another. What is most important: Volume, Revenue, or ARPU?

Of course, this is not a strategic approach to maximizing your subscriber opportunity and is not the right question to ask. Any publisher would immediately want to maximize all of these if only it were that simple!

The relationship between intro price and start volume is obvious, as is the relationship between ARPU and churn. However, these should not be standalone relationships. LTV aligns all subscriber performance metrics under a single north star.

The right question to ask, therefore, is how do I maximize my long-term aggregate lifetime value? By framing the question in terms of LTV, publishers can unchain themselves from the pendulum swinging between volume and ARPU or the pendulum between churn and starts.

Performance indicators like conversion rate, repeat visitors, known users, and churn are indeed still important metrics and should be closely tracked with a clear target each month. Rather than separate goals (or at worst, having competing goals) the parameters and relationships work together with a unified goal across the organization. Decisions about introductory price, introductory term, step-up pricing, etc., all become quantifiable levers and relationships that impact the LTV metric.

How to measure LTV

There are several ways to calculate LTV. Most methods reach similar outcomes even if some of the math and baseline figures may differ.

In summary, LTV is the expected cumulative 3–5-year operating margin from a subscriber, given their introductory price, introductory term length, predicted retention, and planned price changes. Subscriber lifecycle management tactics may influence the expected LTV, such as the frequency and magnitude of price increases, churn reduction tactics, product changes, and digital engagement campaigns.

When optimizing go-to-market offers for subscribers, we hold these other factors constant to isolate the offer parameters (intro price, intro term, full price).

Turning math into decisions

The LTV framework is ideal for forecasting the net outcome of volume, revenue, and ARPU from potential tactics. For example, understanding price elasticity (both acquisition price and renewal price) and the effect of offer terms on retention, enables the optimal balance of conversion rates and average revenue for trial offers (the quality/quantity tradeoff). Using LTV, publishers can understand how the levers they have the power to pull (usually price and term) influence outcomes directly or indirectly.

Furthermore, in the context of offer optimization, connecting the dots between levers, relationships, and outputs requires accurate data and benchmarks to build the LTV framework. Optimization algorithms can determine the best levers and relationships to maximize expected revenue. Mather has developed the LTV framework and optimization algorithms in collaboration with publishers and are actively applying these tools in-market.

Putting it all together

The application of this framework and rigorous testing has led many publishers to adopt low introductory offer prices with long terms and aggressive step-up prices (for example, USD$1 for the first six months that renews to USD$1 per day). The Boston Globe and The New York Times are well-known leaders in this area. A broad survey of publishers adopting this acquisition strategy is shared by Greg Piechota in a recent INMA article.

Several years ago, NRC Handelsblad in Amsterdam found optimal acquisition prices to be lower than their traditional offer though, at least for now, they have not been as aggressive as other publishers with their acquisition pricing. Price is one of several levers’ publishers can use to maximize start volume, and it is often deployed when publishers reach a plateau of subscriber volume using other tactics.


Mather has shared several case studies of applications of LTV over the years including in the hospitality industry and selling long-term subscription offers.


LTV for marketing optimization

Market opportunity and subscription maturity (saturation) are also important to understand when determining what subscriber lifecycle management tactics to consider. For example, in the first year of launching a new digital subscription, publishers may not want to introduce deep discounts until they have maximized starts from the “low-hanging fruit” of loyal readers on their site.

As digital subscriptions plateau, tactics such as more aggressive meters, higher proportions of subscriber-only content, or registration walls can continue driving acquisition volumes while maintaining ARPU.

Beyond the use case of offer optimization, marketers routinely develop marketing initiatives to nudge consumers into changing behavior. In each case, the LTV North Star and optimization framework help marketers make critical decisions based on maximizing revenue opportunity.

Our work with clients in this area is extending the framework as well as the metrics and benchmarks to measure the performance of the optimized go-to-market offers.


About the Authors


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