Tangible AI - Collecting customers: How media companies can boost email signups with AI

In this article, I look at smart new ways to boost your newsletter subscriptions, powered by predictive analytics, sentiment analysis and other AI tools.

Email fails

Traditionally when it comes to email collection, media companies tend to use unobtrusive plug-ins quietly placed throughout their content. This seems logical, as it avoids interrupting the user experience and irritating the reader.?

The trouble is this: many users miss the call-to-action entirely as it is buried among the digital clutter. These conventional email subscription methods have become even less effective in recent years, as readers suffer digital fatigue and their inboxes reach saturation point.

On the opposite end of the spectrum, some publishers have tried showing obtrusive popups that usually never work.

Let’s look at three ways an AI-enabled approach can generate stronger loyalty, create a higher impact and reduce the strain on your resources.?

1. Perfect timing with predictive analytics

When are your casual, infrequent readers most likely to subscribe? Your success in collecting their email address and other details is often a matter of one thing—timing.?

Predictive analytics is already used by nytimes.com to request information from users at the peak of their interest.?

How to implement ??

The technology which powers this is machine Learning (ML), with predictive tools like scikit-learn enabling media companies to develop ML models that understand user preferences, deliver tailored content, and elevate the user experience.

Adopting this predictive approach doesn’t have to be arduous and time-consuming, some out-of-the-box and no-code solutions do the work for you.

2. Creating the right value exchange using classifiers

Publishers can significantly enhance their value exchange with audiences by integrating AI classifiers into their newsletter strategies. Classifiers are machine learning algorithms that can categorize individuals based on various attributes such as interests, demographics, and online behavior.

For example, by analyzing user data, AI can identify patterns and preferences, enabling publishers to send targeted offers to those who have shown interest in specific topics or products. This not only enhances user experience but also improves engagement and conversion rates.

How to implement ??

There are 2 ways to build something like this. If you have skilled Machine Learning and data teams, you can build something using platforms that support classifiers, such as Microsoft Purview or DataBricks. Another option that will give you less customizations but chepare and faster experimentation would be to use out-of-the-box solutions such as Bridged Media or Intuit Mailchimp that allow you to create proof-of-concepts.

3. Powering personalisation with generative AI

Personalisation is at the heart of successful AI-powered email collection. Media companies can dynamically generate personalised calls-to-action by employing generative AI models. Take Scandinavian digital media group Schibsted – the family of brands not only uses AI to spark creativity in newsrooms but also enhances its newsletter subscriptions with generative algorithms that create personalized emails.

Furthermore, AI-driven personalization can be automated and scaled, enabling publishers to manage large audiences effectively while maintaining a high degree of personalization.

How to implement ??

In order to implement personalizing using Gen AI, you need to first identify what is the personalization in the email. Do you want to send recommended products, offers or just bring them back to new content that they might be interested in. Once you identify what goes in the email, you can use different approaches to building a RAG system using platforms like Miso.ai or open source libraries such as Surprise. But if your team is not usre how to experiemnt with these platforms or open source libraries, it would make more financial sense to try any out of the box solution.

Bonus tip: measuring success

But how can you evidence the impact of these AI tools for your media company? According to our AI and engagement experts at Bridged Media, understanding your email collection success requires tracking key performance indicators (or KPIs) beyond the conventional metrics. To start, think of your email subscription KPIs in two distinct areas – before collection and after collection.

Pre-collection, you should be analysing indicators like email penetration (which is the percentage of your total email subscribers out of all users) and conversion rate, the percentage of users subscribing to email when shown your call-to-action.

After collection, consider evaluating metrics like email open rate (simply the percentage of users who opened your email campaign) and click-through rate, the percentage of users who clicked on a link from the email campaign.

Setting targets for your KPIs is vital, and is best achieved by understanding your baseline metrics then aiming for incremental improvements. For example, a tangible, achievable goal might be increasing your email open rates by 15% in the next quarter or boosting lead quality by 20% over the next six months.

About Me

I am an experienced entrepreneur who has worked in Media and Tech consulting for many years. Apart from being a full-time parent, I am also leading a project that aims to make AI more accessible to restore the balance of power between tech providers and digital publishers in the Media ecosystem. I helped sports publisher BOAS double its newsletter signups and Greenways Publishing increase its sign-up rate six-fold. Bridged’s out-of-the-box tools eliminate the need for extensive data processing or dedicated AI resources, making AI adoption accessible and efficient.