Misunderstanding the Dynamic Paywall

The definition of a Dynamic Paywall assumes that the Paywall shows an offer when certain conditions are met. Regardless of whether these conditions are based on content category, device type or location - the most important factor paywall actions depend on is the dynamic of a particular user’s engagement during their interaction with a publisher’s site.

The first part of rule-based segmentation is generally easy and offered by almost all paywall providers. The second element is extremely difficult as it requires Data Architecture which provides the capacity for real-time user engagement scoring.

Many solutions are able to run such scoring only by weekly or daily batch processing which seriously impacts their effectiveness as user-performed actions such as purchasing a subscription are very much in-the-moment decisions.

“Emotional (or impulsive) purchase” is an old trading concept used by many vendors. It is driven by the fact that purchase is done when the need to posses is met with growing emotions/impulse at a specific moment where the probability to purchase is the highest.

After such a moment the probability to purchase decreases significantly - and publishing is not different than any other business.

Take this scenario for example: a user comes to the site with an increasing frequency and consumes more content per session. One day, the user gets really interested in a story or series of stories and they wants to read it now. This user’s emotions are heightened at that moment. If we are not able to detect this flare-up, we will lose the opportunity to sell a subscription at that particular moment.

Simple rule-based metric modeling (e.g. IF a user is coming from Facebook THEN show paywall) or batch processing would not work.

Let’s use an example here. Say a publisher chose a metered model with a limit of 5 articles per week.

We have two new users: user A who came one day and used up their limit of all 5 articles in one session and user B who comes every day, 5 days a week and reads one article each day.

User A did not have a chance to build the habit nor loyalty to your publication but was caught with a paywall. User A will not wait another week just to come back with refreshed paywall hits, thus User A never comes back.

User B comes every week but 5 days a week. Their engagement pattern is very clear here and is growing with every visit during the month (due to a growing frequency of visits and a smaller time between each of these visits - otherwise known as recency). Then, one day user B may find a set of articles which drew their interest during one session and reads 3 or 4 articles during that session.

If you are not scoring your users dynamically in real-time but in batch processing, you will not show them a paywall at that specific moment, when their emotions are at their peak. You will show the paywall next day (when your batched user scoring process brings the results). Unfortunately, the emotions/impulse is gone and probability to purchase will be much lower than the day before and the reader will ignore the paywall and return back to his routine of consuming one article daily, 5 days a week. In the case of batch processing of data, we’ve actually created a negative habit for that user rather than push them to subscribe.

If the Paywall offer is displayed “IN THE MOMENT”, it will meet criteria of already existing engagement (the need) and emotional/impulsive need to possess this locked content, thus capturing the user when their probability to purchase is at its highest.

Then after the purchase, if subscription on-boarding is well executed, user engagement should grow very quickly. Most importantly, users that purchased the subscription with a stronger awareness built with engagement stay longer as subscribers vs. users that were caught by paywall randomly. We observe that in many cases of individual user behaviour.

It’s also confirmed with user engagement levels on user journeys required to execute certain actions.

When constructed properly, Dynamic Paywalls deliver consistently better results over any other methods and do not create negative habits where users dismiss communications from publishers as “just another pop-up or paywall” but rather are seen as valuable invitations to invest in what interests them, at the time that they’re ready to invest in this subscription.

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