Right, let’s talk email. For years, we’ve been blasting out messages based on demographics – age, location, job title. Sound familiar? It worked… sort of. But it always felt like firing a shotgun and hoping to hit something. That’s where AI comes in, and honestly, it’s been a game-changer for me. Forget those static, clunky demographics, we’re diving deep into behavioural data. Buckle up, it’s a ride!
My initial foray into AI-powered segmentation was, admittedly, a bit daunting. All that data swirling around – where do you even begin? Well, the first step is identifying your data sources. Think beyond just your CRM. Consider purchase history, obviously. What are your customers buying, and how often? But also, what are they browsing on your website? Which products are they lingering on, even if they don’t add them to the basket?
Then there’s social media. What are your customers talking about? What are they liking and sharing? Tools exist that can analyse sentiment and extract keywords, giving you valuable insights into their interests and needs. Don’t forget things like email engagement itself! Who’s opening what, and clicking on which links? This shows you where your current email strategy is successful and where it needs work. Bring this data into a central location, a data warehouse, a CRM or even a cloud based document.
Now comes the fun part: feeding all this information into an AI algorithm. Think of it like teaching a clever dog a new trick. You show it examples, and it learns the patterns. I use machine learning algorithms – clustering algorithms are your friend here – to automatically group customers into segments based on their behaviour. The beauty of AI is that these segments are dynamic. As customer behaviour changes, the segments shift, ensuring your targeting remains laser-focused. This means that instead of static segments based on age, you’re getting segments based on ‘frequent buyers of camping equipment’ or ‘users interested in sustainable living’, for example.
Let me give you a practical example. Initially, I had a segment called ‘Young Professionals’ (demographic, yawn!). But using AI, I discovered that within that segment, there were two distinct behavioural groups: ‘Event Goers’ (frequent attendees of workshops and conferences) and ‘Career Climbers’ (avid readers of industry articles and downloading leadership guides). By creating dedicated campaigns for each, tailored to their specific interests and needs, engagement went through the roof. ‘Event Goers’ received invitations to upcoming networking events, while ‘Career Climbers’ got access to exclusive leadership content. This is the power of understanding the nuanced behaviours within a supposedly homogenous group.
Of course, this level of personalisation requires more than just fancy algorithms. It demands a change in mindset. You need to be constantly testing and refining your approach. A/B testing subject lines, send times, and content is crucial. This iterative process helps you continuously improve your understanding of your audience and optimise your email campaigns. Remember, data is only as good as the insights you glean from it. Make sure you dedicate time to analysing the results of your campaigns and identifying opportunities for improvement.
Also, think about triggered emails. Someone abandons a shopping cart? Send them a personalised reminder with a tempting offer. Someone views a specific product multiple times? Send them more information or a customer testimonial. This kind of timely, relevant messaging can significantly boost conversions. And don’t be afraid to experiment with different email formats. Videos, interactive content, even short surveys – anything that grabs attention and encourages engagement.
The real reward isn’t just about improved open rates or click-through rates. It’s about building stronger, more meaningful relationships with your customers. When you show them that you understand their needs and preferences, they are far more likely to become loyal advocates for your brand. And ultimately, that’s what it’s all about: creating value for your customers and building a thriving business. The process requires analysis of data from multiple sources to feed an AI engine that will use behavioural patterns to classify clients. From there creating a personalised experience that builds rapport and encourages engagement is key. Keeping this process dynamic as user habits change is paramount.
