How to Solve Your Ecommerce Customer Retention Problems with Data Analytics

Did you know the cost of acquiring new customers is five times more than retaining current ones?

That’s why so many ecommerce businesses are investing more in customer retention than they are with acquisition. After all, even a 5% increase in loyal customers can increase business profits by 25%-125%.

There might be several tactics you’re already using to try and boost customer loyalty, but there may be key element you’re currently missing: data analytics.

Challenges faced in keeping customers loyal

It’s one thing to have a customer loyalty program or great customer service already operating to keep customers engaged and loyal. These are essential and important in contributing to your overall customer retention strategy.

But if you’re not currently using data analytics then you might not be making the most of these tactics or maximizing cost.

But if you’re not currently using data analytics – or, better put, not using data analytics to drive more sales and increase overall profits – then you might not be making the most of these tactics or maximizing cost.

For example, you might be churning out thousands of dollars on advertising via different platforms. Say you’re putting out content as Facebook ads, Google paid ads, and Instagram ads.

You’re making sales, but you’re not sure which of these channels is responsible for the best or even most conversions. What can you do then?

Let’s take a look at how Spark, a company selling a marketing system that helps online businesses, is tackling this problem.

You’ll notice in the screenshot above Spark’s top five sources of conversions, each with a specific path and conversion goal (far right column).

On each source, Spark can trace the exact steps a visitor takes to which sources contribute most to a specific conversion goal that they set.

For Volusion customers, you can link your Google Analytics right to your Volusion-hosted online store to get some actionable insights about your sales based on where your visitors come from. This way, you see how everything works end-to-end between your site, store, and social media channels.

To make the most out of this integration, be sure to set up conversion goals and assign monetary value in Google Analytics so you can see just how much each channel or source is helping you meet these goals.

For a more detailed look at conversion goal setup for Google Analytics, check out this handy blog post.

Ways to use data analytics to improve customer retention

Improving customer retention doesn’t have to remain a mystery. If you’re serious about overcoming these challenges that are keeping you from retaining those loyal customers, read on.

Here are 4 actionable ways to use your ecommerce data analytics to keep customers loyal to your business.

Segment your customers based on buying behaviors

Most businesses segment their customers based on interests or buying behaviors, especially if they offer products or services that cater to different and specific needs.

For example, Volusion can segment customers based on the service they’re currently subscribed to – be it the site builder, shopping cart software, or marketing tools.

From these segments alone, the company can create relevant content, such as email newsletters or promotions or exclusive tips, tailored specifically to what these customers are trying to achieve.

So customers in the site building segment might receive exclusive tips on how to create the best conversion-focused landing page. Or customers in the shopping cart software segment can get a free cheat sheet on how to take great product photography.

This can increase customer retention by convincing customers that your business can keep helping them grow – without annoying them with irrelevant offers or emails.

Send targeted product recommendations

In your ecommerce business, you’ll want people to repurchase from you, be it the same product (if your product or its parts need constant replacing) or other related products in your store.

An online clothing store, for example, might get from historical sales data that a woman likes a particular look for her tops and dresses, then recommends similar products from the newest collection she might like.

More often than not, one purchase decision isn’t enough to tell you a lot about a customer already.

A word of caution: more often than not, one purchase decision isn’t enough to tell you a lot about a customer already.

Think about it – a man might buy a woman’s perfume from an online shop to gift to his wife. Based on this one purchase alone, it wouldn’t be wise to keep sending this man more targeted product recommendations for other women’s perfume.

Instead, get as much data as you can about your customers from different touchpoints with your brand to remain relevant. This way, a targeted product recommendation can convince customers that you know their needs well, and they’ll keep their business with you.

Use AI to personalize search results

AI learning has made it easier and faster to provide personalized search results to leads and customers – you no longer have to spend hours and hours mining at different insights using traditional analytics.

AirBnB and Spotify are some of the best examples of companies that make the most of this kind of AI. For example, we see AirBnB creates instant search results for returning users based on their history of wishlisted homes or previous search history to showcase the best results for users.

These personalized results are influenced by the price points, specific amenities, and desired locations these users searched for in the past.

Similarly, Spotify uses the same AI learning to be able to provide personalized playlists to users. They recommend new music and songs based on users’ frequently-listened genres, favorited tracks, songs they include in their playlists, and even other playlists they follow.

On the other hand, you can also get inspired by their “Tastebreakers” campaign, where they used customer data to create tailored playlists with music that a specific user doesn’t normally explore but still might enjoy. This keeps their customers engaged, seeing that their Spotify suggestions evolve as much as their own music taste.

Retarget by sending follow ups to existing customers

Retargeting campaigns can be a key strategy for maximizing your customer lifetime value or reengaging cold customers.

Some customers might abandon their carts because something comes up – retarget them by sending a follow-up email or ad that reminds them of the purchase they tried to make.

If loyal customers haven’t purchased anything in a while, give them a special promotional offer to keep them hooked.

If loyal customers haven’t purchased anything in a while, give them a special promotional offer to keep them hooked. Say, a personal care retailer might offer a special discount on all makeup products to a customer with a shopping history of lipsticks and eyeliners.

Key Takeaways

Data analytics can be the one thing you’re missing to make the most of customer retention. Gleaning the right insights about your customers can keep them engaged, either by feeling that your company really understands their needs. Keep checking back on your analytics to create better campaigns and making the most of your budget and efforts.

Have any questions about data analytics? Ask them in the comments!