Read All About It: Why Newspapers Need Marketing Analytics

After nearly 20 years, I decided to let my subscription to the Wall Street Journal lapse. A few months ago, I did likewise with my longtime subscription to the Chicago Tribune. I didn’t want to end my subscriptions, but as a customer, I felt my voice wasn’t being heard.

Some marketing research and predictive modeling might have enabled the Journal and the Tribune to keep me from defecting. From these efforts, both publications could have spotted my increasing frustration and dissatisfaction and intervened before I chose to vote with my feet.

Long story short, I let both subscriptions lapse for the same reason: chronic unreliable delivery, which was allowed to fester for many years despite numerous calls by me to their customer service numbers about missing and late deliveries.

Marketing Research

Both newspapers could have used marketing research to alert them to the likelihood that I would not renew my subscriptions. They each had lots of primary research readily available to them, without needing to do any surveys: my frequent calls to their customer service department, with the same complaint.

Imagine the wealth of insights both papers could have reaped from this data: they could determine the most common breaches of customer service; by looking at the number of times customers complained about the same issue, they could determine where problems were left unresolved; by breaking down the most frequent complaints by geography, they could determine whether additional delivery persons needed to be hired, or if more training was necessary; and most of all, both newspapers could have also found their most frequent complainers, and reached out to them to see what could be improved.

Both newspapers could have also conducted regular customer satisfaction surveys of their subscribers, asking about overall satisfaction and likelihood of renewing, followed by questions about subscribers’ perceptions about delivery service, quality of reporting, etc. The surveys could have helped the Journal and the Tribune grab the low-hanging fruit by identifying the key elements of service delivery that have the strongest impact on subscriber satisfaction and likelihood of renewal, and then coming up with a strategy to secure satisfaction with those elements.

Predictive Modeling

Another way both newspapers might have been able to intervene and retain my business would have been to predict my likelihood of lapse. This so-called attrition or “churn” modeling is common in industries whose customers are continuity-focused: newspapers and magazines, credit cards, membership associations, health clubs, banks, wireless communications, and broadband cable to name a few.

Attrition modeling (which, incidentally, will be discussed in the next two upcoming Forecast Friday posts) involves developing statistical models comparing attributes and characteristics of current customers with those of former, or churned, customers. The dependent variable being measured is whether a customer churned, so it would be a 1 if “yes” and a 0 if “no.”

Essentially, in building the model, the newspapers would look at several independent, or predictor, variables: customer demographics (e.g., age, income, gender, etc.), frequency of complaints, geography, to name a few. The model would then identify the variables that are the strongest predictors of whether a subscriber will not renew. The model will generate a score between 0 and 1, indicating each subscriber’s probability of not renewing. For example, a probability score of .72 indicates that there is a 72% chance a subscriber will let his/her subscription lapse, and that the newspaper may want to intervene.

In my case, both newspapers might have run such an attrition model to see if number of complaints in the last 12 months was a strong predictor of whether a subscriber would lapse. If that were the case, I would have a high probability of churn, and they could then call me; or, if they found that subscribers who churned were clustered in a particular area, they might be able to look for systemic breakdowns in customer service in that area. Either way, both papers could have found a way to salvage the subscriber relationship.


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