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Leveraging the Multiplier Effect of Renewals to Increase Profits

by on May 14, 2012 in Retention, Subscriptions, Yield Optimization

In subscription-based services, revenue comes two sources: customer acquisition and renewal acquisition. Once renewals become more than 50 percent of the revenue, sales and marketing costs associated with the renewal process begin to become a larger factor in managing profitability. The interesting dynamic is that while the acquisition phase occurs once during the lifetime of a customer, renewal acquisition is an annual event. The multiplier effect of reducing renewal acquisition costs can increase customer lifetime profits substantially. The best way to measure sales and marketing contribution to profits is to measure the ratio between gross-margins generated and the associated sales and marketing costs. So for calculating the customer acquisition cost (CAC) ratio, it would simply be the revenue from new [...]

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Measure Loyalty to Increase Trial Conversions

by on January 13, 2012 in Behavioral Analytics, Subscriptions, Yield Optimization

While trials are a common mechanism for generating paying subscribers, trial conversion rates for most publishers are in the low single digits. The majority of users starting a trial do not have the budget or authority to convert into paying subscribers. Often times, the trial user is exploring or investigating, and most trial users become fence sitters whom without sales help don’t convert. Because the sales force doesn’t have the capacity to contact every trial user, focusing efforts on the right fence sitters becomes the key to increasing conversion rate and revenues. Research shows that focus on the most engaged trial users is the same as focusing on the right fence sitters and increases conversion rates by 100% or more. In [...]

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Prospecting Up-sells with Behavioral Analytics

by on December 16, 2011 in Subscriptions

In paid content, one of the challenges for corporate sales is finding demand for content that can be monetized – finding a good lead. Our research shows one of the best sources for leads is within existing individual subscribers where several individuals are sharing the access to the paid content. The charts below show a typical example of how to identify an individual subscriber that is a lead for an up-sell to a corporate or group agreement. The first chart shows the daily use profile for two different individual subscribers by graphing the total number of reports accessed over a 90-day period. Each daily use profile is color coded based on the unique devices used to access the reports. The [...]

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Value Rating Part 2: Targeting in Paid Content

by on August 17, 2011 in Subscriptions, Value Rating, Yield Optimization

In paid content, how can a sales manager differentiate the up-sell vs. the retention risk between two customers with same number of page views and visits? Value Rating is the answer, or the percentage of page views that are units of value (full description of Value Rating in Part 1 of series). Using Value Rating as a metric, Scout Analytics has found that categorizing engagement on page views alone, will incorrectly classify the revenue opportunity of 15 percent of customers. The consequence of using page views as a primary metric is that sales managers will use wrong negotiation tactic with customers 15 percent of the time. Chart 1 to the right will help illustrate the limitations of page views only. The [...]

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Analyzing Disparities in the Unit Cost of Engagement

by on November 17, 2010 in Digital Revenue Optimization, Subscriptions

"Demand Map"

Posted by: Matt Shanahan This is the second in a series on the importance and use of unit cost of engagement. In paid content, a pricing disparity is defined as a subscriber paying too much or too little for the content compared to their peer subscribers.  Pricing disparities are often hidden because fees are charged based on the contract period or quantity of users neither of which account for actual consumption (i.e., engagement).  Because subscriber value is directly correlated with engagement, the unit cost of engagement can be used to uncover pricing disparities and opportunities for digital revenue optimization.    One of the easiest ways to visualize pricing disparities is to plot each subscriber according to their subscription fee and their measure of engagement during the term [...]

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Importance of Analyzing Unit Cost of Engagement in Paid Content

by on November 16, 2010 in Digital Revenue Optimization, Subscriptions

"Unit Cost of Engagement"

Posted by: Matt Shanahan Last week, Scout Analytics announced research concluding that aligning engagement and revenue provides a 20-30 percent uplift potential for paid-content publishers.  After fielding a few questions on the research, I thought it might be worthwhile to explain some of the methodology here in the blog.  This blog entry will address the following questions: What is engagement? What is unit cost of engagement and how do you calculate it? Why is calculating unit cost important? First, what is engagement?  In paid content, engagement is consuming content (e.g., reading an article, downloading a report).  Engagement can be measured at an individual level (e.g., number of articles read by a single user) or at an organizational level (e.g., number [...]

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Attention Economics: The Publisher ARPU Equation™

by on September 8, 2010 in Advertising, ARPU, Subscriptions

Posted by: Matt Shanahan Outside of sponsorships and donations, a publisher has to drive revenue from an audience member’s engagement.  Whether it’s games, software, information, or media, a digital publisher has a limited audience and limited revenue potential.  Some audience sizes are in the hundreds of millions, but the vast majority of audiences are in the hundreds or tens of thousands.  The 1,400+ regional news publications in the US are a good example, and so are the more than 1,000+ SaaS firms.  The limited size of an audience and the need to be profitable requires a publisher to answer the question: “What is the maximum amount of revenue that can be made from a unique audience member?” That is why Scout Analytics [...]

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