A more useful web metric: lifetime value of a visitor


Publishers spend lots of time and money on complex web analytics to increase audience engagement. But they're reporting the wrong thing – page views. What should be reported is the lifetime value of visitors and what contributes to increasing lifetime value.

Why Lifetime Value Matters

Lifetime value of a visitor is the expected monetary value of a visitor’s engagement with a site.   For paid content, it is the expected subscription revenue.  For media, it is the expected advertising or lead generation revenue.  For some publishers, it is a combination of both.

In editorial, sales, and marketing decisions, lifetime value of a visitor matters because it’s the measure directly correlated to a publisher’s business model.  Is a visitor important to the business model?  Which audience segments make increase business model productivity?  Where would investment improve size of most valuable audience segments?

Behavior Analytics Predicts Lifetime Value

The function of behavioral analytics is to generate scores that rank visitors relative to each other for the likelihood that they will repeat a desired action. Any action can be profiled – click-throughs, registration, topics read, and so on. High likelihood to repeat equates to a high score and if tied to an economic activity translates to high future value. Low likelihood to repeat means low score and low future value. Behavioral analytics is that simple.  Behavioral analytics has been employed by ad networks for almost a decade to increase conversions, but it can be used by publishers as well.

In any publishing business model, the future or lifetime value of a visitor goes up when a visitor  will return and the frequency of the visits increases. Predicting the likelihood and frequency of a visitor’s return is at the heart of behavioral analytics.  By analyzing rather than reporting page views, behavioral analytics can look for patterns in usage that predict the future actions of a visitor or audience segment.

Step 1: Creating Lifetime Value Scores

The first step is to decide on an algorithm to scoring visitors.  The scoring system typically varies for paid content vs. media. There are several consistent and repeatable calculations for measuring lifetime value, though I'm partial to my company's Demand RatingTM.  A demand rating is a visitor’s demand for content expressed as a single number that indicates the likelihood the visitor will return and consume more content.

For paid content, a demand rating is computed by comparing how much content was consumed by the subscriber to how much he paid for it—consumption divided by cost. The ratio between the two normalizes all the variables associated with multiple rate plans and results in a quantifiable indicator of demand for each specific visitor.

When subscription rate plans are not a factor, a different scoring system is used for demand ratings.  For ad-based content, a demand rating is computed through a weighted scoring of the recency of the last visit, the frequency of visits, and the average duration of a visit.

Step 2: Recording Lifetime Value Scores

During a visit, each page view event is recorded along with URL, time, date, visit, visitor, and other data.  Additionally, you may record custom data such as content metadata, circulation/registration data, and of course the lifetime value score.

Step 3: Reporting Lifetime Value Scores

To gain insights into content and visitor segments, web analytics provides rich pivot table capabilities to slice and dice the data stored with page views. When the lifetime value score of a visitor is available, your web analytics can be directly correlated to your business model.  You'll be able to pull actionable insight from your web analytics in a way you probably could not before.

Web Analytics Transformed

What matters most to your highest value visitors?  The most popular page report doesn’t tell you this.  On the other hand if pages were sorted not by page views but by average lifetime value score, you might find that content with low page view volume contributes the highest-value visitors.  In this case, ensuring the quality and growth of that content will retain your best visitors.

Are there high value segments with more growth potential?  Large numbers of "drive-bys" coming from search engines are likely to be low value visitors.  These page views can drown out smaller high value segments in your audience that could be grown if only you knew they were there.  Rather than searching for the visitor segment with the most page views, you want to find the visitor segment with the highest average lifetime value score.

Are you spending time and resources on content that has low economic return? This is yet another instance where the most popular page report falls short.  If content with high page views is associated with visitors with low lifetime value scores, you need to reassess the importance of that audience segment and that content.

There are many other pivots to examine your business model.  Is the value of your audience going up over time?  Is the value better than last year?  What is contributing to increasing or decreasing value?  By storing the lifetime value score of a visitor, web analytics are transformed from mere context to being core in understanding and managing the health of your business.

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