Retail: Big Data and Personalized Shopping Experiences


If you’re a retailer, chances are you’ve got loads of data from your customers, but the question on the minds of many is how to take advantage of it all? The digital age is also the age of personalized experiences, but there are plenty of marketers who have yet to take advantage of these opportunities – whether that be because they’re not collecting the right data, or don’t have the means to implement it.

Yet there’s no question that personalization is helpful in raising revenue and decreasing customer drop-off. For example, British Gas found a 39 percent growth in click rates, a 58 percent drop in unsubscribe rates and a 52 percent jump in open rates once it implemented personalized content inside each of their user emails. So the question isn’t “should I be implementing personalization?” It’s “How can I be implementing personalization?”

First, you need to establish which data you need to collect in order to effectively craft your messaging. HubSpot breaks down the type of data available to marketers into three groups:

Behavioral data: The products or services customers purchase, and what products they view. For B2C companies, this can also mean looking at the contents of abandoned carts, and for B2B companies, this can mean considering which pieces of content a prospect viewed before becoming a customer.

Brand interaction: What pages are prospects viewing on your website, and how are they engaging with your email messages? How did they reach your site in the first place? Do they follow you on social media?

Demographic data: From age, gender and geographic location to marital status, children in the household, income and homeowner status, demographic data tells businesses a lot about the people behind the purchases.

Sometimes you won’t have enough first-party data to work with, but if you’re a large enough entity you probably also have the buying power to purchase third-party data. The more data retailers have access to, the better informed decisions they can make.

So how do you manage, keep track of and utilize all that data?

To make your Big Data actionable, a universal API framework can be used to connect your data warehouse with an ecommerce engine, CMS or marketing cloud solution, allowing developers to create the personalized experiences that are absolutely necessary in this day in age. This can be a daunting task, but working with a data warehousing specialist ensures you get your environment up and running smoothly.

Then you can start personalizing. At the most basic level you can populate customer emails with their name, but this doesn’t reflect the true power of Big Data. You can send out email blasts or populate an app with personalized offers and coupons that take into account factors such as customer shopping history, demographic and abandoned online shopping carts. These offers are much more likely to be acted upon since they are tailored to the individual via predictive analytics.

Predictive analytics doesn’t just assume consumers will purchase the same items over and over, but instead takes into account Affinity Analysis, seasonal trends and the shopping habits of customers with similar profiles to determine the likelihood of a customer purchasing different items. For this to happen, data algorithms need to be developed and dashboards implemented by a savvy BI partner to help make the analysis of data faster and more user-friendly.

Meanwhile, many retailers are pushing the boundaries of what is possible with big data. Some retailers are getting really creative by combining personalization with in-store location intelligence. Kohl’s piloted a project that allowed customers to opt into a project that detected where they were in the store using a phone’s GPS and then show them coupons and offers related to the section they are browsing. If the offer is unique to that customer and linked to previous data related to how long a customer tends to linger in a specific section, Kohl’s is much more likely to make that sale.

If all of this talk on Big Data and Personalization is overwhelming, be sure to check out FitForCommerce’s Annual Report 2016, with plenty of insights retailers need in order to be successful in the information age.

Thank you for reading our series on retail and big data! We hope you’ve found it helpful. If you missed one of the other parts, be sure to go back to the beginning to read it all.

Image credit: GoodWorkLabs

More Blogs on Retail:

More Blogs on Retail:

1. The Value of Dashboards for Store Reporting
2. Market Basket Analysis and Planograms 
3. Privacy and Consumer Data
4. Personalizing the Shopping Experience

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