What Big Data Can Bring to Your Retail Marketing Strategy

You probably feel like integrating Big Data into your business is a good idea. But it’s not so straightforward at first — you’re likely to see some initial reduction in productivity as your team gets used to their new tools.

Once the dust settles, though, you will start seeing all the ways that Big Data can elevate your business.

To give you a glimpse into the future of ecommerce, here are just a few of the ways Big Data can enhance your retail marketing strategy:

Churn Prediction

Churning refers to users leaving your platform and not coming back. It can apply to mobile apps, email newsletters or an ecommerce store. With Big Data, you are able to analyze trends among your users and make accurate predictions as to when a particular user is at risk of churning.

Most applications of Big Data serve to improve things that your human marketers are already doing, but churn prediction is a field that’s unique to machines. The markers that the machine considers when determining that a user will churn can seem inconsequential to us, but the algorithm sees correlation where we can’t. Once several markers have been detected, and it’s confident a user will churn, it’s time for you to take steps to keep them.

Big Data helps here, too: It can help you determine the best course of action to retain users who are at risk. It can build a user profile and, based on what has historically worked for similar users, it can choose the optimal action to take to keep that individual on your site.

Mass Personalization

One of the most useful aspects of Big Data for any business is its potential to provide personalization at-scale. That means you can tailor your marketing to each specific user, while running a large-scale, international campaign.

The first factor in determining how much you are able to personalize your marketing is the amount of information you have on a user.

If you install a plug-in, such as Disconnect and then go about your browsing as usual, you will see that many sites are carefully watching where you visited before you arrived at their door — and where you went afterwards. By using algorithms, sites are able to learn a great deal about you from just that limited information.

For example, many sites or pages skew toward one gender, political belief or socioeconomic rung. So, even if you’re not buying targeted ads, you still have an opportunity to personalize your marketing using this readily available behavioral data.

The second factor that determines how personal you can get is your marketing team and your content ecosystem. Unless you have an AI generating content for you, your marketing team will have to create different versions of your ads or newsletters to serve each type of user.

There’s no limit to how personal you can get here, so get those customer avatars polished up and combine programmatic ad buying with some solid ad templates.

Conversion Rate Optimization (CRO)

Conversion rate optimization is a discipline premised on testing, and data has always been at the heart of it. But data and Big Data are two different beasts.

Big Data can provide insights about the best way to drive a sale for a specific customer based on the very limited information you have on their journey to this point. This can take the form of better recommendations, flash sales, or optimized wording of your product descriptions.

While some CRO applications of Big Data are unique, plenty of them are simply improvements over the old “small data” methods.

Content Timing

The importance of timing content delivery isn’t lost on the major political parties. They know that there is an optimal time to send you content that will get you out of the house to vote; by using Big Data analysis, they can quite accurately discern who you will vote for.

In ecommerce, you can take advantage of the same phenomenon to optimize your email marketing. Your audience is global, so there will never be one perfect moment to publish your content to everyone. Staggering times for different time zones is an easy first step, but with Big Data, we can do better than that.

We can learn what times are the most effective for each type of user and deliver the content at the exact moment that it’s most likely to lead to a conversion.

Consistency Across Platforms

Your customer doesn’t live their online life on just one platform. If you want your marketing to be effective, it has to span multiple platforms, too.

But this can complicate things when it comes to tracking a customer’s journey. How are you supposed to know where a user is in the sales funnel when they’re jumping around between different sites?

Tracking users between sites is a common practice these days and by using Big Data, you can enhance your re-marketing by intelligently targeting users on an individual level.

Maybe a user sees your content promoted by an influencer on Instagram, then some lead ads when they’re next on Google, and before you know it — they’re on your site and ready to convert. Big Data helps retail brands close the multichannel gaps.

Unless you have a dedicated team of data analysts, you’re going to want to start your foray into Big Data with some well-defined, specific goals in mind.

One thing’s for sure: The future of online retail is tied to Big Data, and the sooner you jump on board, the better off you will be down the road.

Editor’s note: The opinions expressed in this article are the author’s and do not necessarily reflect the views of Convenience Store News.