Behavioural data: what it is, why you should be collecting it and how it will help your business

Knowing what customers want is the foundation for successful marketing and one of the best ways to determine this by is collecting behavioural data, writes Guy Hanson, VP Customer Engagement Validity Inc.

Behavioural data provides measurements of how your customers and prospects interact with your products and services. The actions measured span the full buyer journey and an important part is the way users interact with digital content. Email, mobile and web interactions are all rich sources of behavioural data, and metrics like open rates, click rates, page dwell time, bounce rates, and purchase activity all provide strong behavioural signals. Additional sources increasingly being used include customer interactions with chatbots, wearable technology, and smart devices (TVs and speakers).

So, why is behavioural data so valuable?

In short – because actions speak louder than words. While asking customers for data about needs, interests and preferences should form part of any brand/customer relationship, this approach has limitations. Customer profiles built from self-provided data run the risk of being incomplete and can decay over time if not regularly updated. By comparison, behavioural data is generated by real-life interactions and more accurately gauges the intent of prospects and customers that generate it.

Responsible marketers can use this data to create messaging and offers that are more targeted, relevant, and personalised –  driving customer engagement and ultimately helping grow revenue and customer lifetime value. There are also operational benefits for SMBs. Using behavioural data in this way means smaller, more effective campaigns that cost less to produce.

How can it be used?

Behavioural data provides the raw material for a broad range of new marketing tools that are under-pinned by Artificial Intelligence (AI). Many marketers are perhaps unaware that AI already touches multiple aspects of their marketing – it’s been driving email spam filtering and fraud prevention solutions for a while now, but 2020 encouraged an explosion of new uses, and senders now use AI for send-time optimisation, engagement prediction, best offer selection, better personalisation, and next-best channel identification – all the things that make marketing messages stand out as truly best-in-class.

How should small businesses collect behavioural data?

Most marketing platforms have at least some marketing automation capability and SMBs can harness this to do some of their heavy lifting for them. For example, abandoned carts send out a strong behavioural signal of a partially-formed intention to purchase. This is why cart abandonment emails tick so many boxes – factors like time, context, and mindset are all relevance dimensions, and serving customers with real-time messages that reaffirm those part-formed intentions to purchase is nudge theory at its best! What’s more, research by Bluecore shows cart abandonment emails generate a phenomenal A$3 average revenue per email because of their relevancy, compared with just A$0.25 for one-time-send emails.

A challenge for the effective use of behavioural data is that it comes from many different sources and is held in many different silos, making it hard to create a single view of ‘behavioural truth’. Increasingly, marketers are dealing with this through the adoption of CDPs (customer data platforms). CDPs enable businesses to get all their customer data under one roof and are built to handle multiple data points from many sources. They collect both online and offline customer data and can include anonymous visitors as well as specific customer identifiers. While CDPs were initially the preserve of only the biggest marketing budgets, they are now far more cost accessible, and SMBs should consider them as an essential part of their marketing toolkits.

Are there any watchouts?

Collecting and applying behavioural data is a common and strategic marketing practice, however, increased focus on consumer privacy does create a higher duty of care on marketers. The litmus test for the use of any behavioural data should be, “Would the customer know/expect their data to be used in this way?”

The recent introduction of new privacy-based regulations in many countries creates a legal requirement to provide clear notification of the use of technology such as tracking pixels and cookies. And subscribers must be notified where personal data may be shared with another party for processing purposes, to ensure that explicit consent has been obtained. Major tech companies are also proactively prioritising consumer privacy, such as Apple introducing its new Mail Privacy Protection (MPP).

While consumer expectations, tech changes, and new laws have raised the bar for what’s best practice, businesses can easily achieve this by being transparent about what data they use and how they use it, making sure their customers see clear value, and providing choice to keep the data up to date.

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