Newsday applies personas to data to maximise engagement

By Ned Kaufman

Newsday Media Group

Long Island, New York, USA

Nowadays, to provide maximum value to our subscribers, we have to engage them personally. This is how we segment our subscriber base to guide targeted marketing and content development as closely as possible.

The first challenge to accomplishing this is to determine the dimensions on which to segment. Much of this decision depends on the nature of the actions on which we wish to base the results.

Understanding specific personality characteristics of readers helps define the best ways to engage with them.
Understanding specific personality characteristics of readers helps define the best ways to engage with them.

One approach is to group subscribers based on the stage of their relationship with us. This segmentation scheme involves engagement variables such as visits, pageviews, time on site, and scroll depth. This guides us in terms of what we’re trying to accomplish with our communication.

For example, for those “higher up in the funnel,” we will encourage more visits, build brand awareness, and try to increase our understanding of preferences and motivations. For those further toward the middle, we encourage registration and provide incentives for subscription. And for those at the end, we look toward retention rather than acquisition, and for opportunities for cross-sell and upsell monetisation.

So, if the engagement segmentation tells us what we should be accomplishing, our next step is how to accomplish it. This is where segmenting by variables such as demographics, interests, and lifestyle comes in.

By developing a picture of groups of subscribers as people, we gain insights into the type of content they’re likely to engage with, the channels through which they can best be reached, and the marketing appeals most likely to resonate with them.

This can be accomplished via custom cluster analyses, for example. Or by overlaying third-party lifestyle segments (InfoGroup “InfoPersonas”) on our subscriber file at a household level.

The InfoPersona clustering scheme consists of 42 clusters, organised into nine “superclusters” based on factors such as age, income, gender, marital status, presence of children, home ownership, education, travel, involvement with technology, political orientation, ethnicity, and leisure activities and other interests. We have also overlaid this information on a complete database of households in our region to segment our prospect universe as well.

The first set of insights from the clustering came from indexing our subscriber base versus the overall population to determine if any segments may be overrepresented or, perhaps more importantly, underrepresented. Analysing the lifetime value and churn propensity of the segments among our subscribers directed us toward those underrepresented segments that would be prime targets for acquisition. The overrepresented segments gave us a picture of our core customers and became targets for retention.

The other key part of this analysis was an investigation of the levels of interest of our subscribers in the various topics covered by Newsday. For the print edition, we conducted a survey asking respondents to rate their level of interest and desire for more/less content in each area. For the digital versions, we examined an engagement index made up of factors such as number of visits, pageviews, time on site, and scroll depth with respect to each section.

Taking the average interest/engagement scores for the entire subscriber base, we then tabulated the engagement scores against the cluster assignments to determine which topics are of significantly greater than average interest to particular segments. In this way, we arrive at the targeted approaches for tailoring content to maximise engagement across the board.

This application of personas will be applied in additional projects as well. We previously tabulated levels of interest in our sections against the amount of space we tend to devote to them. Areas where the serve level lags behind the interest are seen as areas for increasing coverage.

In addition, where overall demand and coverage are both low, if we find the subscribers who are interested tend to be of high value and engagement, we may consider developing niche, opt-in products to appeal to them. In this way, putting a “face” on groups of consumers who we want to accommodate informs the development and promotion of expanded content and new products.

About Ned Kaufman

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