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by Matt Manning

During this pandemic, the value of accurate data has never been more obvious. Without reliable information derived from the mountains of data being generated by fast-moving events the actions necessary to slow the outbreak are impossible to make. From the data-gathering process to the intelligent analysis of that data by experts and through to action based on that analysis—all stages of the process are now very familiar to almost everyone on the planet.

The management of this data supply chain process is, of course, old news for people in the online information business and many of our firms are now scrambling to help businesses navigate the perils and opportunities opened up by the crisis. Among the information feeds now in development are:

  • Robust primary source data on the spread of the pandemic via public and (especially) ‘alternative’ sources
  • Value-added feeds of government contract and grant data
  • Fluctuating price and production data for marketers, distributors, and retailers
  • Personnel data for those leading the global pandemic response
  • Predictive analytics on the long-term economic effects of the lock-down

All of these efforts help to define the ‘ground truth’ of our current situation and there is a case to be made that this kind of data work is ‘essential’ to the intelligent response to the virus affecting all of our lives. Smart decisions require accurate source data, sound data analysis methodology, and timely action.

Of course, because we are familiar with fundamentals of gathering and analyzing primary source data it’s easy for us in the information business to second-guess government responses. Simple things like comparing daily mortality rates to the baselines of the recent past to see the true impact of the virus are blindingly obvious to us, but apparently confound many of the amateur data analysts leading the response to the outbreak. Similarly, the explosive nature of an exponential growth curve is hard for many people to understand just in terms of the basic mathematics of it all.

One thing that everybody can understand, however, is that the value of truly understanding ‘ground truth’ has never been so apparent to so many people. Years from now when this disaster is just a painful memory for us all, we will perhaps look back on this year as the tipping point when the critically important nature of our real-time intelligence industry came of age.


posted by Shyamali Ghosh on April 14, 2020

by Matt Manning

The business model for selling subscriptions online has been based, from the beginning, on the idea of an automatic renewal of a subscription as a core part of the subscription agreement. This is what was called the “til forbid” model in the business-to-business circulation management world of the 1980s, and that meant that the subscriber’s corporate credit card would be dinged on a periodic (usually annual) basis until the publisher was forbidden to do so. Prior to this, publishers would cancel and then re-start subscriptions, losing revenue in the process.

Ever since this model has been deployed, the trick for the circulation marketing team has always been in how to communicate that an automatic debit charge is coming (usually as quietly as possible) and how to handle the fallout from irate subscribers unprepared for the subscription renewal, which typically also involves a price increase.

There is some finesse to handling these interactions and successful publishers, along with the online services who followed them, were the ones who left the customers feeling a pang of subtle coercion but not enough annoyance to go out of their way to cancel their subscription.

These days, credit card issuers are actively addressing the issue of ‘zombie’ subscriptions by adding functionality to their online services that allow a consumer more transparency into their recurring transactions. I think there are lessons here for business-to-business publishers to use this tried-and-true model for their own renewals.

Some potential approaches to fine-tuning the automatic renewal process could include:

  • Performing an analysis of the subscriber’s usage patterns well in advance of the renewal date to highlight light users, who could then be offered training on getting the most out of their subscriptions. This also gives the customer retention team a heads-up.
  • Linking to a clear statement detailing how subscriber data will be used and specifying details on subscription renewal terms, potentially offering a “renewal at birth” option.
  • Adding a “deadman’s switch” to terminate a recurring subscription after a predetermined amount of time, perhaps five years.

This model focuses on customer ROI, gives invaluable customer satisfaction metrics, and offers the opportunity to stress the professionalism of the information provider. If carefully executed, this model should deliver results that are more than strong enough to justify the related expense of their implementation.


posted by Shyamali Ghosh on November 21, 2019