In addition to independence from social media algorithms and first-party data collection, personalisation is one area that makes e-mail newsletters such an attractive medium for publishers.

But what types of personalisation are there? And why is it so important?

Types of personalisation

Personalisation is a means of curating your content to your subscribers to build more durable relationships. This can take many forms.

Most obviously, using merge tags allows you to address subscribers by their name, letting them feel like more than one of a countless mass. Research has shown that everyone has a subconscious bias toward their own name — even the letters used in them.

There is also personalisation by segmentation. Dynamic text blocks, for instance, can be used to tailor specific calls to action (CTAs) within a newsletter edition to certain audience groups. An advertisement upselling subscribers with 20% off a higher-tier subscription plan isn’t much use to subscribers who aren’t particularly engaged or who are already on that plan.

Finally, there’s per-subscriber personalisation. That means accounting for the interests of each subscriber individually. This is something tech companies are exceedingly good at: Think of Netflix or Spotify and how the selections presented to you get better over time (usually).

News publishers can also achieve great results with per-subscriber personalisation. The Financial Times saw an 86% increase in engagement with their newsletters when they implemented an active personalisation strategy of simply allowing subscribers to set their preferences themselves.

Why per-subscriber personalisation is so effective

Let’s demonstrate this with a real-life example.

A news organisation wanted to understand which topics its newsletter audience was most interested in to boost click rates. In one campaign over a month, it sent newsletters to subscribers that included 35 different topics.

It might be assumed we could calculate the four or five topics people were most engaged with and simply include more of those kinds of stories. The chart below indicates what this looks like.

We can see there are, indeed, a few topics producing noticeably more engagement than others, but it’s also clear the extent to which aggregate data hides variance. Indeed, the indistinguishable block that takes up two-thirds of the graph represents the interests of an enormous number of subscribers.

We could further analyse this data to look at complementary combinations of topics (i.e. cluster together readers who are all interested in topic X and Y). Doing this, we can produce more complex segments that represent groups within a subscriber base. However, there would still be significant variation within a segment.

For instance, the illustration below represents the profiles of three real subscribers from the newsletter described above. Each bubble represents a topic, and bigger bubbles correspond with higher interest.

The interests of person A broadly correspond to the high-performing topics in the graph above; that is, they are primarily interested in religion and technology (the green bubbles). But person B and person C, while mildly interested in these topics, are far more interested in others; in case of person B, travel, and in the case of person C, careers.

So, while all three sometimes engage with stories on religion and technology, focusing on those topics would not be the best way to maximise engagement for two-thirds of the group. Of course, for a newsletter focused on a more niche topic, it’s important to use finer topic classifications and to gain an even deeper understanding of the content.

This is why per-subscriber personalisation is so important.

Our research indicates that personalising the content of a newsletter to each subscriber — representing their interests as individuals rather than segments of an aggregate — can lead to an average increase in engagement of more than 50%.

Two takeaways

Each level of personalisation outlined above has the power to foster deeper ties with audiences. But each publisher’s resources will vary.

So, what can they do to move the needle?

1. If you can’t personalise, segment.

If you don’t have the technology to personalise your newsletters to the interests of individual subscribers, then segmentation is a brilliant halfway option.

The scope and depth of segmentation will depend on the resources available to each publisher, its goals, and the data at hand. Analysis that is too coarse will miss the nuance that makes any form of personalisation so effective. Too fine, however, and publishers run the risk of making the process unscalable.

Segmenting by engagement and high-level interests are excellent starting points. Once this segmentation is done, making use of them is the next priority. Most e-mail solutions will have the capability to create automated “journeys” of varying levels of sophistication that can make offering plan upgrades to engaged subscribers, say, relatively simple and effective.

2. Don’t lose editorial control.

For those with the technology to personalise content to individual subscribers, one of the concerns we sometimes hear from publishers is the trade-off between personalisation and editorial control.

In reality, the tension between the two will vary case to case — from newsletter to newsletter or even different sections within a single newsletter. Nevertheless, it is a balance that can be successfully struck.

A successful relationship between a publisher and its audience is never simply transactional. Trading an e-mail address for content, even if that content has been tailored to you, is a fairly mercenary proposition. Combining data-driven suggestions with editorial judgement helps preserve the essence of a newsletter, avoids information bubbles, and aids discovery support. Not everything needs to be personalised.

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