DATA ANALYSIS
Is The Wrong Data Holding You Back?
The need to handle and analyze user data is essential for the viability of media and digital publishing companies.
President and CEO of FIPP, James Hewes, says that “Data is now at the heart of news publishers’ business models. Without digital data, news companies can’t understand their audiences.”
While it’s clear publishers are eager to get their hands on as much customer data as possible, not all metrics provide the same value, and some can even hold you back from exceeding revenue goals- wasting time and money if you pay too much attention to them!
Digital publishers who succeed are those who set the right priorities and track suitable data to make informed decisions— allowing them to strengthen relationships with their readers which lead to robust revenue streams.
With this in mind, it becomes crucial to discern what the ‘right data’ actually is. Read on to discover the different types of data, the pitfalls to be aware of, and how to ensure your teams are tracking metrics that move the needle for revenue.
Useful Metrics to Track in Publishing
By far the best metrics to track are those involving performance data. Performance data offers insights that help digital publishers plot strategic direction and determine what to change and how.
Performance metrics make it easier to track significant objectives without analyzing vast amounts of data. They do this by highlighting positive or negative variations from behavior norms. Once you understand the baseline for a particular user behavior, you no longer need to analyze vast amounts of this data. Instead, you can simply watch for deviations from the average that might indicate a strategy change is required.
Here are some examples of useful performance data to track in digital publishing:
Monthly Engagement: The amount of times a user engages with your content each month is an important metric because it can help you see trends in their behavior. If engagement decreases, it’s a sign the content isn’t resonating with a user’s preferences, and something needs to be done to entice them back.
Performance metrics make it easier to track significant objectives without analyzing vast amounts of data. They do this by highlighting positive or negative variations from behavior norms. Once you understand the baseline for a particular user behavior, you no longer need to analyze vast amounts of this data. Instead, you can simply watch for deviations from the average that might indicate a strategy change is required.
Retention and Churn Rate: Tracking retention and churn rate helps publishers understand how well they’re serving customers. Fluctuations in either can inform publishers if particular changes have been well received by their audience or not. If a publisher discovers the rate of churn is increasing after a particular change to a subscription package, they can clearly see it’s a wrong move.
As well as tracking deviations from the norm, it can also be useful to look at patterns leading up to user churn. If the data suggest there’s a gradual decline in engagement and a drop-off in overall subscriber retention after 3 months, publishers can test different strategies within the subscriber journey to mitigate against churn indicators in the future. E.g. creating a re-engagement campaign at this point in the journey.
For more help with tracking and understanding subscriber churn, see our article “How To Cut-Down Subscriber Churn”.
Customer Lifetime Value (CLV): Examining purchase history, average subscription length, and one-time transactions during a specific time frame can help publishers gauge an idea of how much value customers are receiving from their service.
The more value customers perceive, the more likely CLV will increase. Low CLV figures suggest a publisher might need to consider new packages or pricing options to better align perceived value with service.
Metrics to Avoid
Now we’ve discussed some of the key metrics digital publishers can track to help improve revenue, let’s delve into some of the types of metrics to ignore which can actually slow a business down and waste valuable time:
Vanity Metrics: These are low-value data points that focus mainly on brand image, but do little to actually move a company towards its tangible objectives. E.g. The total number of page views per user per month. Total page views are typically a vanity metric because they lack the context required for the numbers to be meaningful. Solely looking at total page views would fail to account for all the other different contextual factors that may impact this metric, like where a user is referred from (direct to the site, via social media, or through an ad campaign running at the time). Many marketers get caught up tracking these metrics without actually knowing what to infer and how to use the data.
It’s not that a vanity metric itself is always useless, but if a publisher fails to use it in the appropriate context for a specific goal, the numbers lack the substance required to make any worthwhile decision.
Deep Data: Deep data is often at the opposite end of the spectrum to vanity metrics and comes with its own challenges. Usually, deep data involves large-scale, high-quality data collection for very specific objectives. Unfortunately, with these large volumes of data comes a lot of analysis. Some types of data on intelligent paywalls, for example, require so much context that the actual numbers are difficult to make actionable. You need a full-time product manager or data scientist to analyze and identify opportunities for actionable insights.
In instances where it is crucial to examine large data sets, it may be worth first identifying whether the added maintenance and expertise is essential for your business.
To tackle large-scale deep data, many leading digital publishers rely on subscription experience platforms to help with data capture. This data is enriched using CRM or CDP integrations, allowing publishers to determine clear actionable steps without having to manually delve into a vast array of sources.
“A lot of publishers have their reader data in 10-15 different buckets and struggle to create a single view of their customer from all that data. Publishers are trying to find ways to bring all this data together digitally and use the right technology to do it.” James Hewes, FIPP
Getting More From Data
While it’s beneficial to understand the types of metrics that can make a real impact on business objectives, arming yourself with the right data is only one aspect of effective utilization. To truly take advantage of the unique advantages first party data has to offer, publishers also need to consider the following:
Analyze Data Quickly: If a customer complaint comes during a trial period, it can take mere days to take action before that customer is lost forever. With this in mind, data must be accessible in real-time. When you are analyzing lots of data from different sources, and requiring various expertise, high latency is often an issue. Subscription experience tools ensure all datasets are complete and surface meaningful data insights for technical and non-technical teams alike, enabling them to answer questions and gain the ability to react and take action.
Empower Collaboration: If a subscriber has an issue that is offline and yet there are efforts onsite encouraging a purchase, it can result in a disjointed experience for the user. There should be alignment and clear communication across functions. Therefore, a strong subscriber journey involves several departments – customer service, marketing and sales – which require access to the same data via a shared interface.
Understand Technical Trade-Offs: Diving too deep into extensive data comes at a price. Determine if the analysis is an absolute must, and if there are tools that can provide an alternative to help automate the process.
Being able to access the right data, and having the infrastructure in place to analyze and action it quickly means publishers will be primed to strengthen relationships with their readers and grow their revenue streams.
For more help utilizing your data, download our e-guide ‘how successful digital publishers achieve significant results by leveraging their data.’
Keep Customers For Life
4 Types of Data Publishers Should Be Making the Most Of
Not all types of data hold the same value, and publishers who can set the right priorities and goals with the right types of data will be in a better position to strengthen both relationships with their readers and their revenue streams.
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