Posted by: Matt Shanahan

I am never surprised when someone says they measure subscriber loyalty only to learn they are really measuring engagement.  How and why a subscriber engages can be a loyalty driver, and understanding these drivers can help paid-content providers create loyalty programs.

When it comes to measuring engagement, it’s hard to argue with the approach of measuring everything.  The incremental cost of collecting three or three-dozen quantitative measures is negligible. Why not have duration and frequency of visit, click-through rate, bookmark data, RSS subscriptions, downloads and blog comments metrics available at your fingertips?

My view gets a bit more controversial when we start talking about how to derive meaning from all the engagement data points that are collected. The general model today is to sift through the data points and, based on instinct and/or experience, determine what knob to dial up or down.  An organization might create a feature that helps improves content resyndication, roll out a program that increases downloads, or create a promotion that increases repeat visits.  All are fine ideas, but they are mostly guesses, and the approach is often shotgun.

I find it fascinating that all of these objective analytics are translated into activity through a mainly subjective lens.  Call me a stickler, but it seems we need an approach these analytics in a way that’s, well, a bit more analytical.

What’s missing is a quantitative platform for comparison—a normalized metric for figuring out which engagement metrics matter. That’s where subscriber loyalty comes in.  Once you have a quantitative way of understanding the subscriber loyalty, the engagement metrics come alive. Demand Rating™ is our metric for subscriber loyalty. It enables organizations to rank subscribers and group them into comparables sets to investigate differences. 

For example, you can group subscribers with high loyalty scores and then compare their engagement metrics to those with low loyalty scores. The delta between these groups will offer insight into engagement metrics that drive loyalty. Or, you might compare loyalty across segments —maybe geographical, organizational, or firmographic—to understand which engagement metrics are important to that particular segment.

As you can see, engagement metrics are loyalty metrics, but they can be highly correlated to each other.  Further, loyalty metrics quell a lot of controversy about engagement metrics because it’s the key for quantifying contribution of each engagement metric.

Demand Rating, Metrics, Subscriptions Demand Rating, Metrics

Posted by: Matt Shanahan

John Lovett has an interesting post Building a Culture of Measurement.  The title and content caught my eye because it was embodied a big force behind the development of Demand Rating™.  As John stated in his post, “Culture consists of values, beliefs, legends, taboos and rituals that all companies develop over time.”  Below are some of our values and beliefs behind Demand Rating. 

Scout Analytics set out to measure one of the most critical variables in sales, marketing, and product management: visitor loyalty.  Our culture is marked by pursuit of an astonishingly simple measurement that has dramatic impact on results.   The Demand Rating measurement was originally sparked from a book called How to Measure Anything and the following excerpts have directly shaped our culture:

Measurement is a set of observations that reduce uncertainty where the result is expressed as a quantity.

If it matters at all, it is detectable/observable
If it is detectable, it can be detected as an amount (or range of possible amounts)
If it can be detected as range of possible amounts, it can be measured

In business cases, only a few key variables merit deliberate measurement efforts. 
The rest of the variables have an “information value” at or near zero. 
In other words, most measurements do not reduce uncertainty.

Guessing which visitors represent the best revenue opportunities is still widely based on intuition and experience.  It doesn’t have to be that way.  Learn more about Demand Rating in this blog.

Customer Demand, Demand Rating Behavioral Analytics, Demand Rating

Posted by: Mark Upson

So when and where should you do the deep dive?  Demand Rating™ and Demand Ranking™ offer insights to determine when and where analysis is warranted.

Evaluating the range on Demand Ratings, the difference between the high and low, provides a uniformity measure of subscriber loyalty.  In general, the tighter the range, the more uniform the subscriber loyalty is, and the more uniform the loyalty the less time should be spent comparing subscribers to each other. 

Outliers, however, can throw a wrench into the works by creating a big range and potentially raising unnecessary analysis.  Demand Rankings increase the accuracy of a range by filtering which Demand Ratings should be included.  Within a subscriber segment, the Demand Rating with a rank of 1.0 should be the high, and the Demand Rating with a rank of -1.0 should be the low.  Using these two ratings to create a calibrated range eliminates the outliers that are not representative of the subscriber base in general.  The calibrated range can be assessed on uniformity and the need for further analysis.  

So what do you do with the outliers?  As you can imagine, outliers prove to be an important source of clues to loyalty drivers.  Much like the previously mentioned cluster analysis for high ranking and low ranking subscribers, outliers can be compared to the segment in general to identify additional loyalty drivers.

Demand Ranking extends the power of Demand Ratings.  Whereas Demand Rating gives you a measure of subscriber loyalty, Demand Ranking lets you understand the drivers behind subscriber loyalty. 

Closing out the series on Demand Rating and Rankings it is important to underscore the importance of firmographics.  Firmographics provide the basis for tracking behavior needed in ratings and for segmentation needed by rankings.  In the next blog series, Pete will examine the challenges and strategies to accurate firmographics.

Demand Ranking, Demand Rating, Firmographics, Subscriptions Demand Ranking, Demand Rating, Firmographics, Subscriptions

Posted by: Matt Shanahan

In the same way that Demand Rating™ helps maximize up-selling opportunities, it can also play a critical role in prospect to customer conversion efforts and opportunities. 

Take for example, the freemium model where a low end version of the product or service is offered for free with hopes of converting that prospect to a subscriber of a higher end product, or the free-trial model where prospects can try the product for a specific period of time before buying.  How does the organization prioritize its conversion efforts?  How does it know to which prospect the product is delivering the most value? 

By now you know the answer.  Demand Rating gives a comparable number to work from.  Conversion efforts should be targeted first towards those that are getting the most value out of their free version—those with a high demand rating.  Those with a low demand rating are probably not worth the sales effort, and those in the middle might be helpful for understanding product refinement.

Next, Mark will look at Demand Ranking – the ability cluster and compare groups of customers.

Behavioral Analytics, Demand Rating, Subscriptions, Up-sell Behavioral Analytics, Demand Rating, Subscriptions, Up-sell

Posted by: Matt Shanahan

Up-selling is another important play in the subscription revenue optimization game.  When should you run that play?  Again, Demand Rating™ provides new insight, offering quantitative indicators for when sales should pursue an up-sell opportunity. 

Recently, we spoke to a publisher that offers a subscription service to both corporations and individuals.  Corporate subscriptions are driven by a corporate sales team that sells a premier service offering, while individual subscriptions are distributed through membership in a key professional association.  The publisher had a hunch that if individual subscriptions being used inside a corporation could be identified, then they could up-sell a corporate subscription.  Unfortunately, the publisher had no way to quantify the potential opportunity or take advantage of it.  Enter Demand Rating.

The publisher will identify individual subscriptions used from within target corporations by grabbing the domain name associated with access.  Since each individual has a demand rating and the demand ratings of all individuals from that corporation can be aggregated, the aggregate rating serves as an indicator of overall demand within the corporation.   The new rating of target corporations arms the sales team with critical information.  First, prospects can be qualified and ranked by the aggregated individual demand, helping the sales team to know where the low hanging fruit might be.  Second, the quantitative data can be used as a part of the sales process, offering proof of need to the decision makers. 

Converting individual licenses to corporate licenses can be highly lucrative and very strategic.  The organization is also considering a seeding partnership with the association to further take advantage of the opportunity.

Behavioral Analytics, Demand Rating, Subscriptions, Up-sell Demand Rating, Subscriptions, Up-sell

Posted by: Matt Shanahan

Subscriber loyalty is not just about revenue retention.  In fact, revenue expansion is where a loyalty metric really starts to hit its stride—cross-selling, up-selling, and even new subscriber acquisition.  Because Demand Rating is measure of subscriber loyalty, it can be used to identify new revenue opportunities with existing subscribers through targeted cross-selling efforts.

Denials, the statistic that tracks attempted access of unlicensed content or services, is a great indicator of subscriber demand, but denials alone don’t indicate whether a cross-sell opportunity exists. Demand Ratings give that insight.  High Demand Ratings equal subscriber loyalty, so subscribers with high Demand Ratings are already ‘feeling the love’ with your offerings. They perceive good value in your service, making them likely to be open to complimentary and expanded offerings; they instantly become your highest priority cross-sell target.  In short, high Demand Ratings provide the answer on who the best prospects are for cross-selling and denials provide the answer on what to cross-sell.

Take the situation where there is a high Demand Rating, but no denials.  Can you tell whether a cross-sell opportunity exists?  Demand Ratings again provide an answer.  What to offer these ripe subscribers becomes easier as well by looking at the product mix for peer companies with high Demand Ratings. The current product mix for a subscriber can be compared to product mix of peers within their segment, providing high probability recommendations for cross-selling. 

By reducing subscriber loyalty  into one comparable number, subscription businesses can suddenly use quantifiable evidence to target their cross-selling efforts.  Demand Rating gives critical insight into what should be offered and to whom.  Looking at Demand Ratings and product mix across peer groups offers a model for scaling success.

Behavioral Analytics, Cross-sell, Demand Rating, Subscriptions Cross-sell, Demand Rating, Subscriptions

Posted by: Matt Shanahan

Another critical use of Demand Rating™ is to better understand and reduce churn—a threat to any subscription business model.  A no-churn mentality drives profits and creates a platform for growth.  Unfortunately, most organizations don’t have the necessary optics to determine which subscribers have waning loyalty and are at risk of defection. While web analytics tools might deliver standard low usage reports, they can be misleading.  Demand Rating enriches web analytics with contract and firmographic data—supplying a normalized metric for comparison—and giving new insight into preventing churn before it happens.  Here’s how Demand Rating helps:

Which subscribers are at risk?  While low usage is never good, often it’s difficult to know what’s low. Take a global financial information services company. Usage by their venture capital subscribers is radically different from their corporate subscribers, and is like night-and-day from the traders they have in their subscriber base. The definition of low is different in each usage scenario, so a metric that allows an apples-to-apples comparison is essential. Demand Rating is a normalized metric that is relevant and comparable as the market is sliced, diced and segmented. Suddenly, what is normal is for a segment or even a particular subscriber become obvious and addressable.   

When is a subscriber at risk? Too often, organizations don’t have the ability to recognize a subcriber issue until a license is not renewed.  Because Demand Rating enables comparisons over time, it can identify subscriber issues when they occur.  A sudden drop in the Demand Rating could be because of a reduction in force or the entrance of a competitor.  Identifying this issue when it occurs allows a sales team to refine the license mix and boost the Demand Rating.

Why is a subscriber at risk?  While some subscriber issues are outside the control of a service provider, many are not.  Demand Rating helps compare subscribers to each other and identify the difference between low demand subscribers and their high demand peers using the same content. It helps identify characteristics of high risk subscribers. Knowing these differences enables the organization to target specific retention programs toward them so that they might gain more value from the service. 

By constantly measuring the dynamics of subscriber loyalty, Demand Rating is an important new element for identifying at-risk subscribers early, intervening through effective retention programs and holding on to subscribers.  After all, it’s all about maximizing the lifetime value of the subscriber.

Behavioral Analytics, Churn, Demand Rating, Subscriptions Behavioral Analytics, Churn, Demand Rating, Subscriptions