How using the right customer data yields better personalization

How using the right customer data yields better personalization Headshot

By Mike Austin, CEO & Co-founder

Converting a one-time buyer into a repeat customer is the single most effective way for many businesses to grow, and one of the best ways to do this is by offering a personalized customer experience.  With the virtually limitless shopping options consumers have in the palms of their hands, retailers can differentiate themselves from competitors by tailoring their marketing to the individual customer. Targeted email and web marketing are highly effective retention tools provided the underlying data is available.

The further you want to get, the deeper you need to delve into the data. Many marketers are aware of the data which is available, but can’t take advantage of it as they don’t have the tools to connect up their silos of data. The good news is that there are ways to easily connect up your data pools, even if you don’t have a big budget for a data integration project.

So let’s look at which types of data you can use to personalize your marketing and where to find it.

Types of data used for personalization

Contextual data

Contextual information, such as the device and browser used or the shopper’s location, weather and the date and time of opening an email or visiting a website, all offer opportunities to determine which content is presented to the shopper on each channel.

Demographic data

For most customers you should be able to access demographic information such as gender, city, country and potentially age, which you can use for segmented campaigns. However, you need to challenge the assumption that everyone who shares similar demographics also shops in the same way for the same products. The problem with focussing on demographics is that although they can partially speak the truth, the information you have in your CRM or marketing database might be incorrect or outdated. You will also be missing out on additional promotional opportunities, such as parents buying for their kids or gift shoppers, if you target your database based on demographic information

Behavioral data

Behavioral and transactional data will give you a more accurate picture of a customer’s preferences and habits. Insights can be gleaned by looking at behavioral information, such as browse data, abandoned cart data, content consumed, search keywords or visitor frequency, as well as transactional data, such as purchase history.

There are three avenues retailers can mine for insightful customer data in order to effectively personalize their marketing communications: website, mobile app and email.  

Website

Being able to collect a shopper’s web behavior across devices, even if they haven’t identified themselves by clicking on an email link or logging into their customer account in this session is the holy grail. Cookies will allow you to identify the shopper on whichever device they currently are and tie their browsing and purchasing behavior back to their history.

Recognising people and tracking their behavior online is just the beginning, though. This information will let you build a picture of what a shopper is interested in and how those interests are evolving.

App

The customer data gleaned from desktop and mobile internet browsing can be further enriched with the browsing behavior from your app. This information is vital to retailers’ marketing strategies, where they have an app. However, all too often in-app data is held by tech and development teams. If it is available and can be correlated, it can only help to achieve a comprehensive picture of the individual shopper.

Email

Lastly, retail marketers need to tap into email data as consumers’ email addresses have become their digital I.D. Don’t think just using a person’s name in your email marketing is personalisation, though. Most consumers expect this as a given.

It is the insights into each customer’s behavior that will allow you to personalize the entire message, not just the salutation. Look at the products they click on, the types of emails (sale announcements, weekly newsletter, cart recovery emails etc.) and the type of content the shopper interacts with as well as time of day the subscriber opens your emails.

Using the right data

When deciding which data to use to personalize the experience, you need to keep three critical factors in mind. The first is to use fresh data. No relevant insights can be gleaned from stale, inaccurate data. The second is to use data from all customer touchpoints. This is essential as this data allows you to see the entire customer journey end-to-end. The third factor is to ensure it is fit-for-purpose. For example, website behavioral data shouldn't only include a list of URLs, it should be broken down to products visited and other business-meaningful attributes.  

Marketing performance increases significantly once as much available customer data as possible is used. Targeted offers to the existing customer base with email marketing and other direct marketing approaches is a highly effective way to increase sales and open new business opportunities. For example, if the data indicates that a group of customers have high brand affinity to a particular sportswear brand, then that is likely that this group will be very receptive for direct marketing related to a new product from that brand.

Smart retailers will use all insights gathered from the website, mobile and email to personalize the shopping experience seamlessly across all devices, based on the shopper’s stage in the customer lifecycle, purchase funnel or individual preferences. By making the shopping experience simpler and more convenient, you are increasing the odds that a first purchase will turn into repeat business.  

This article was originally published on Multichannel Merchant

How using the right customer data yields better personalization Headshot

By Mike Austin

CEO & Co-founder

Mike Austin is co-founder and CEO at Fresh Relevance. Recognizing the challenge of data aggregation in the ecommerce space, Mike launched Fresh Relevance in 2013 with co-founders Eddy Swindell and Pete Austin to solve this need and optimize the customer journey.