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InContext / An inside look at the business of digital content

Digital publishers must avoid being dazzled by vanity data

October 14, 2021 | By Chris Scott, CPTO – Zephr@ZephrGlobal

Professionals in all industries have become obsessed by data over the last decade. It is true that having a firm understanding of your data sets is key to growing a successful business. However, data for its own sake is never the answer.

The whole point of collecting data is to achieve something, such as optimizing subscription experiences to improve your conversion rate. Doing so leads to better value alignment, longer lasting customers and, ultimately, higher revenue.

But data that isn’t understood and actionable is a waste of an organization’s time. And the concept that data is gold dust has led many publishers to chase vanity metrics.

How to approach data

We advocate for a new outlook on the types of data that digital publishers have at their disposal. Working backwards from the outcome, rather than forwards from the granular metric, data can be prioritized into three buckets:

Performance data

The most important data is performance data. These are the metrics that tell you whether things are, generally speaking, getting better or worse. In turn, this is the data that you should call on when deciding to explore a new initiative.

If you don’t have performance data, then filling this gap should be an urgent business objective. Doing so allows you to report on the overall health of your business. For example, if your organization’s churn rate has gone up, you know you need to fix it. Similarly, if acquisition rates have tanked, you know the conversion journeys aren’t working. These insights are the very least you should be getting from your datasets.

Actionable data

The next metrics to turn your attention to are actionable insights. This data points you towards improvements you can act on immediately. These are high priority as they are the clearest and least risky levers you can pull to affect your performance stats.

For example, if no readers are reaching the end of a paywall meter, you know you’ve set the limit too high. The data is the average number of pages a visitor consumes against a meter; the action is to reduce the meter size.

Everything else

There is a plethora of datasets available. However, if the metrics don’t give you an overview of your performance, or provide you with an actionable route to improvement, they shouldn’t be prioritized.

You could call this bucket of data “vanity metrics,” or data that have diminishing returns. By this we mean data that might appear interesting in theory, but in practice needs so much contextual explanation that it becomes more time consuming than it is valuable.

Let me give you an example. Imagine a publisher that uses a metered paywall, allowing five free views per week. This publisher tracks their average number of free pages before subscribing, which is 30. What are the actions that the data points can trigger?

On its own, it’s just not enough data. The metric doesn’t distinguish between visitors who viewed all five free pages, six weeks in a row, from those who dabbled with the odd article here and there over the course of a year. To derive an action would require a lot more analysis, probably with data scientists. A different metric, average meter consumption, would be far quicker and cheaper to action. This data could immediately point to a misconfiguration in the meter.

How to approach data tools

There are a myriad of tools out there to enable news and media companies to collect, clean, manage and store their data.

Data solution red flags

There are two extreme ends of the same spectrum that digital publishers should avoid at all costs.

One of these is a black box. Solutions in this camp do not expose any data or allow you to export it to other systems. In other words, these tools may do the job, but exactly how they get to the output is unclear. Digital publishers need access to their data to take action on it. Ideally, the data is embedded at the point where decisions are made.

The other red flag is a company that offers a specific solution but is proposing to solve every pain point you have. We often see solutions that provide a rich dashboard that looks great. However, it may rarely be in practice because the data is either non-actionable or not holistic.

Does the perfect tool exist?

You would be hard stretched to find a holistic, actionable solution that covers all ground. In an ideal world you could build a data warehouse that combines business intelligence and actionable functionality, although this could be expensive.

In reality, best-of-breed solutions should expose performance data for their own domain. And – crucially – they should integrate actionable data into their UI at the point of action. The important thing is that this will guide users toward an informed decision.

Modern businesses need to experiment, iterate and A/B test in real time, without calling upon a team of engineers to implement changes. All readers that interact with your content should be tracked in a comprehensive and meaningful way, by a platform that then allows commercial decision makers to test and learn from different conversion strategies.

In short, a full-scale subscription experience platform should not only show you what your data looks like, but also how you can use it to improve the customer experience. Publishers that match deep industry knowledge with powerful technology solutions will take market share from those still relying on “one-size-fits-all” customer journeys.

Data provides the key to profitability, when done correctly

You need to have quick and effective reactions to underperforming aspects of your business. This means having holistic and actionable data locally situated to make changes effectively.

Those who approach the data conundrum with a creative, long-term mindset, and avoid being dazzled by vanity data and impractical tools have the best chance of success.

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