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Using your Magento data to better understand your customers

Over the next few weeks, we’ll be sharing a series of posts to help Magento retailers get the most out of their ecommerce data.

We’ll start by looking at how your Magento data can provide essential insight into your customer base that will enable you to deliver more personalised customer experiences.

If you’re using Magento to power your online store, chances are you’re sitting on a treasure trove of data about your customers – information such as products purchased, average order value, and the items on their basket or on their wishlist.

With the right technology behind it, this data can illuminate who your customers are so you can interact with them in a more personalised and relevant way. Here are a three ways you can understand customers more effectively using your Magento data:

Assign customer personas

We’ve written quite a bit about developing customer personas based off your data (this post is a good starting point). But personas are useful for more than just guiding your content or product development strategy.

With the right data to draw on, you can sort existing customers into the most relevant categories and actively target your outbound comms based on persona. Take, for example, a fashion retailer with two key personas – one consisting of fashion-forward women in their early 20s, mostly single, and the other of women with young children who want to keep their whole family on-trend.

By segmenting their customers into two groups based on these personas, the retailer can develop tailored marketing messages for each segment. The retailer might use different copy, images and offers for each group, like so:

Emails targeted by persona

This data can also be used to see how many customers you have in each persona – are they split as you’d expect? Do most of your customers fall into your ideal or target persona? Answering questions like these can help guide your marketing strategy, and show you where to focus your efforts.

Pinpoint lifecycle stage

Lifecycle stage is fairly easy to pinpoint, as it’s mainly based off of their last purchase. You’ll need to know how often your customers usually shop with you – do they come back for another purchase every two weeks? Every month? Every six months?

You’ll probably have an idea of this purchase cycle already; if not, looking at a sample of your purchase data from Magento (and your ePOS if you have a physical store) should help. Most customer lifecycle models have at least these four stages: new, active, about-to-lapse and lapsed (or dormant).

“New” customers are easy to define, as are “active” – they’ll be purchasing at or around the expected frequency. When their purchase rate starts to decline (at whatever rate makes sense for your purchase cycle) they’ll move into the “about-to-lapse” phase, and eventually into “lapsed”.

Additional data will make your lifecycle stages even more accurate – for example, if a customer hasn’t purchased for a while but they’re still engaging with your marketing comms, logging into their account on your website or adding items to their wishlist, they’re probably not about-to-lapse.

Once you’ve defined the parameters for each lifecycle stage, you can place customers within them using data from your Magento store. For example, if your Magento data shows they haven’t made a purchase for 3 or 4 months and haven’t added anything to their wishlist in a while, they’re probably about to lapse and need to be re-engaged.

Knowing where your customers are in the lifecycle can highlight areas that need attention and support decisions in terms of your marketing strategy. It also gives you the opportunity to re-engage at-risk customers before they lapse, maintain positive relationships with active customers, and welcome new customers into the fold.

To make this feasible, you’ll need software to automate things and move customers from one lifecycle stage to the next as soon as their purchasing behaviour indicates a change.

If you’re interested in lifecycle marketing and what to send at each stage, we’ve written about it in-depth here and here.

Identify your best customers

Not all of your customers are worth the same to your business. Some will be more valuable, more loyal, more influential on social media – and therefore, worth a little extra effort to impress.

Your Magento data can help you figure out who these customers are, so you can reach out to them with tailored messaging and ensure they stay satisfied and engaged.

Your most valuable customers are easy to identify – average spend is the best indicator to use. Of course, there’s more to value than just how much they spend. A customer may not be the highest spender, but if they’re a strong advocate for your brand and buy often, they can still be worth a lot to your business.

Loyal customers can be harder to identify. Membership in a brand’s loyalty programme doesn’t mean much on its own. If a customer is actively engaging in a loyalty programme – earning and redeeming points – this is a stronger indicator of loyalty. Recency and frequency of purchase are also good indicators of brand loyalty.

On its own, your Magento data can provide some marker of loyalty based on the recency and frequency of purchase. Combine it with data from your loyalty programme software, and you’ll have a crystal clear picture of which customers are truly the most loyal to your brand.

Drawing out insight at scale

In theory, you could analyse and sort your data manually and pull out at least basic insights in each of these areas. But in reality, your team is busy and you need this information in real-time to make it truly worthwhile.

That’s where the right technology comes in. You’ll need a platform that can pull in your Magento data, analyse it, and output actionable customer insight and insight-driven marketing segments.

Our Horizon platform is built to do exactly that. With the Horizon extension for Magento, you can pull your ecommerce data into the Horizon platform in real-time, and combine it with any other customer data you hold.

Horizon automatically assigns each customer to the relevant persona and lifecycle stage, and allows you to segment based on any combination of these. And our unique ELVIS insight uses powerful algorithms to rate each customer’s engagement, loyalty, value, influence and sentiment towards your brand.

Get in touch to find out more →

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