Pricing for content is a challenging business decision. What content to sell, how much to sell it for, and when to request customers buy the content are all elements of the pricing strategy. In addition, publishers need to be aware of content pricing decisions on their available advertising inventory.
In the digital business environment, the sheer volume of data and the level of complexity can be overwhelming. Here at Mather, we have developed econometric models of price elasticity and propensity to subscribe as well as economic models of revenue to determine our client’s optimal meter setting. Often, the optimal meter level is different by section of the site, by day of the week, by time of day, and by season of the year.
Our models balance the generation of audience revenue while maintaining advertising revenue. We analyze CPMs and sell through rates by advertiser line of business, site section and time blocks. Our extensive analysis reviews page views, user behavior, and available inventory. This dynamic metering program can show the probability of conversion when the meter is set at a certain level and price.
Using econometrics, we determine the relationship between price points and conversion rates to estimate price elasticity. We measure how meter settings affect conversion rates to estimate ‘meter elasticity’, or how engagement with the content affects probability of purchasing a subscription. Using these models, our clients see forecasts of the success rate and revenue using different scenarios for the meter setting and price points.
Our Publishing clients can also view their optimal meter setting related to specific sections of their paper. The net revenue and meter settings are analyzed for sections such as business, health, entertainment, news, classified, financial and sports. Additionally, we can analyze the digital only price or a print/digital bundle price and show the elasticity and optimal meter optimizations for each.