The most successful digital marketers in e-commerce today are the ones who place online shopping experiences at the core of their businesses. According to Econsultancy, 54% of customers would consider ending their relationship with a retailer that doesn’t provide tailor-made, relevant content and offers, yet only 5% of marketers say they provide adequately personalized, 1:1 interactions.
When it comes to improving the visitor experience, a brick-and-mortar store has a clear advantage over an online one. The floor associate can physically talk to his customers. He can learn a visitor’s brand affinities, price threshold, and intent for shopping today. He recognizes VIP customers and treats them that way. Essentially, he builds up a mental profile for each visitor who walks into the store and recommends products or provides assistance based on this information. The floor associate doesn’t badger a visitor the second she opens the door and yell at her to give him her email address.
Now consider the online store experience. The online customer, whether a VIP or first-time anonymous visitor, actually provides all of the same rich information online that a floor associate tries to gather and leverage in the store. Yet many digital marketers dump all this data on the floor like a box of broken hangers. Instead, they should use it to provide 1:1 experiences with each shopper just like the in-store floor associate does.
The Right Data
Much like the in-store floor associate’s mental profile for each of the customers he speaks with, you as an e-commerce marketer can create a unified customer profile for every anonymous, named, and logged-in individual that visits your website. It can look something like this:
This customer profile can be used to drive rules-based targeting and algorithmic recommendations for a personalized experience on your e-commerce site, and it is created simply by collecting data as visitors engage with your site. Let’s explore the data you need to provide a one-to-one experience, starting with the key metrics on the top left.
This section tells you the lifetime value, number of orders, average order value, and geolocation of a shopper. This data can flow into basic segmentation, like defining a VIP customer. You can also leverage the shopper’s location to invite her to events in the local area or plan out your next brick-and-mortar location.
The affinity wheel in the upper right serves as a high-level overview into the customer’s intent, helping you dig into her favorite categories, brands, colors and content (or whatever is important to your business). We can see that this visitor prefers black to any other color, and shops for dresses and skirts most often. The data can be used to provide highly relevant product recommendations to this visitor, based on her unique preferences — much like the floor associate can do by asking a customer about her favorite brands and colors.
Online, you can capture deeper information than a floor associate can in-store. For example, the profile features an engagement and purchasing timeline to help marketers understand buying trends, time between purchases, etc. It allows you to drill down to see the products that the visitor engaged with on the bottom right.
The bottom left of the profile retains all of the segments to which that visitor belongs, as well as any attribute data known about the customer like shoe size or birthday.
The customer profile can even be beefed up with offline transactional data from in-store profiles too. For instance, if the customer buys a beach towel and a bathing suit in a store, you could send a dynamic email to her that says, “complete the look” and recommend a straw fedora hat or flip flops.
While you do not need to dive into all of the preferences of all of your shoppers, you do need all of this data to deliver the maximally relevant experience for every visitor in real time. Since every visitor has a different profile, you can serve up a truly personalized experience.
When shoppers interact with a website or mobile app, marketers need a platform to capture this data and determine their preferred products, brands, styles, categories, price affinities, and more. These are determined by both explicit actions – views, purchases, adds-to-cart – and implicit behavior such as active time on a page or screen, mouse movement, scrolling, etc.
With this data, you have every tool in your belt to create personalized experiences in real time. You can leverage the knowledge that typically only a floor associate at a brick-and-mortar store may have gathered in the past, take it to scale, and provide the best and most engaging shopping experiences for everyone who visits your website.
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