World Association of Newspapers and News Publishers

Smart Data – Report 2: Building valuable relationships

Smart Data – Report 2: Building valuable relationships


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This is the second in a series of three Smart Data reports that WAN-IFRA will publish this year. The reports are the result of a cooperation with Xavier van Leeuwe, Director Marketing and Data, and Matthijs van de Peppel, Manager Data Intelligence & CRM Team, both of NRC Media in the Netherlands; and Matt Lindsay, president of Mather Economics in the USA.

The reports are based on the authors' recently published book, "How to Succeed in the Relationship Economy: Make Data Work for You, Empathise with Customers, Grow Valuable Relationships."

The first report, titled "How to make data work for your news organisation," was published in April. The third report in the series, tentatively titled “Sustain relationships by improving customer experience,” will be published in early autumn.

Report 2 explains how you can use data to attract the right customers – ones who are willing to commit to a longer-term relationship – and how you can keep those relationships going by understanding the influence of pricing.

Relationship must be mutually beneficial

After building the data teams and using the right data (see Report 1), it becomes important to put those data to use so your organisation or business can grow. Only when a relationship is beneficial for both your customers and the company will the organisation prevail.

The last chapters of this report discuss analytical modelling techniques that have been "packaged" with a specific business application in mind to create an analytical tool. Rather than describe the technical modelling approaches employed, they discuss the context in which they are applied within a business.

These customer analytics can predict aggregate behaviour, such as subscribers' likelihood of stopping their service, and there are several modelling approaches that are well suited to this purpose, such as discrete choice models, survival models, and machine learning techniques. The common ingredient in all of these models is data on past customer activity.

Here are some takeaways from this report:
• Targeted pricing can increase revenue substantially while minimizing customer losses.
• Don’t let the gut define prices (it never beats data).
• If it’s about pricing, analyse real behaviour.
• Forget group averages; understand individual performance.
• Learn what emotionally drives and what burdens salespeople.
• Build intelligent thresholds to acquire customers who want to invest in the long term.
• Customer Lifetime Value is best for quantifying customer relationship management.
• Move from “one size fits all” to personalized churn prediction, pricing and acquisition offers.
• Bottom-up forecasting is more accurate than “last year plus X percent.”
• Holistic analysis includes all revenue streams such as advertising and audience revenue.
• Marginal costs are more important than average costs.

Xavier van Leeuwe and Matthijs van de Peppel, NRC, The Netherlands; and Matt Lindsay, Mather Economics, USA


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2017-05-31 10:06

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