How to apply data-driven insights that will grow reader revenue
The key cycle for audience and revenue growth is “analyze, experiment and iterate.” Your investment in business intelligence and marketing tools will pay off as you understand reader needs and behaviors, and make decisions and create processes that are data-driven, testable, and support organizational learning and staffing decisions.
Many of these tactics are possible even with a small staff. While technology can facilitate the work, the primary requirement is access to the data and the ability to generate insights that drive action in support of business goals.
And, we are only interested in data to the extent that it tells us how the business is performing and provides guidance on what steps to take next. So, it is important to remember that not all data is equal.
- Basic audience metrics are raw data. (For example: page views, unique visitors)
- Key performance indicators (KPI) are metrics or a combination of metrics directly relevant to strategic business success. (For example: subscription conversion rate, average revenue per user)
- Insights are deeply analyzed KPI that inform business decisions and actions. (Weekend visitors are more loyal than average; newsletter subscribers are more like to become paid subscribers.)
Your specific strategies will determine the KPI and the combination of metrics you rely on for insights and decisions. But for any subscription business a few basic metrics are important:
Conversion rate: How many of the readers who are presented with an offer to subscribe actually complete the purchase. This will be tracked in aggregate, but also for each marketing campaign, acquisition channel (email, advertisement, paywall) and audience segment.
Churn rate: Gaining 100 new subscribers in a month is not a success if another 200 cancel. The volume and cause of lost subscribers is something newspaper circulation departments typically understand, but it is still deeply complex for digital. The churn rate should be measured both in aggregate and in as many segments (for example, subscription start date, original marketing campaign, subscription price) as is practical to identify factors driving cancellations.
Average Revenue Per User: In its simplest form this is calculated on a monthly or annual basis (total revenue divided by unique visitors). For more focused measurements, you could divide total revenue by just the number of paying customers, or divide just subscription revenue by the number of paying customers. Combined with churn rates and overall length-of-subscription averages, you can also calculate Customer Lifetime Value (CLV or CTLV). But none of these numbers have meaning in isolation — they must be tracked over time and in comparison to other business costs.
Cost Per Acquisition: CPA is the key number to contrast against ARPU or CTLV. A customer with an annual value of $100 who required marketing expenses of $50 to acquire will take six months to be “profitable” for the business. Understanding this equation is necessary to measure the success of both your subscription business and your marketing efforts:
Profit = ( (subscription revenue per user * length of subscription) – cost to acquire and retain)
Calculating these KPIs is simple, once you have the raw data available. Getting this data is at the heart of the organizational transformation to reader revenue.
We should only be interested in data to the extent that it tells us how the business is performing and provides guidance on what steps to take next.”
Think of a marketing campaign promoting a subscription offer as a very long chain of evidence. Each step of the process must be monitored and protected to maintain the integrity of the data. Even one break in the chain results in a loss of data and a breakdown in any effort to improve business performance.
Three typical gaps in that chain of data include:
- The cost per acquisition for individual campaigns and subscribers. Utilizing “average CPA” will not allow you to monitor and improving your marketing efforts.
- Average revenue per user, especially if the subscriber also receives the printed newspaper.
- Campaign attribution that allows churn rates and lifetime value to be assigned to specific email messages or advertising creatives.
As those questions are answered, you can begin to pursue increasingly sophisticated data analysis and marketing tactics. That could involve:
Creating a “propensity to subscribe” score: As noted in the previous section, making a broad guess at a visitor’s likelihood to subscribe is not difficult. A local reader coming directly to your site for the fourth time this week is a potential customer, while an international visitor following a Facebook link is probably not.
Measuring email effectiveness: Email campaigns have a cost, both in real money and in straining the patience of the recipients. You can seek to reduce the volume of emails sent and the cost per subscriber acquisition, increase open rates and click-through rates for subscription campaigns by targeting readers who are most likely to become subscribers and personalizing messages and offers to those targeted audiences.
Improving reader engagement: Increasing loyalty metrics onsite, including pages viewed and return visits; and increasing the frequency and value to readers of contacts in other channels. Some publishers have improved loyalty and engagement metrics using the following tactics:
- Personalizing recommended stories and filtering out already-read stories.
- Providing cross-platform notifications for topics readers have indicated an active interest in.
- On mobile apps, reducing the number of push alerts sent by letting readers opt-in to specific topics.
- Sending email notifications of breaking news updates to readers who have visited an earlier version of the story.
- Highlighting email newsletters of interest to individual readers, and excluding newsletters which they already receive.
- Customizing email newsletters.
Focusing on subscription conversion: Increasing the number of paid subscribers and reducing the cost per acquisition. You could do this by:
- Continuously A/B testing the subscription funnel to remove any usability barriers and to experiment with messaging and pricing offers.
- Using dynamic metering, with each reader receiving a customized number of pages in front of the paywall based on their calculated “propensity to subscribe” score.
- Delivering targeted offers onsite, via email and as retargeted ads on other websites.
- Tracking subscription starts.