How to Leverage Customer Data Unification for Cross-Channel Campaigns

Picture this: You’re a marketer who wants to email your most loyal customers about upcoming promotions. At the same time, you want to reach out to previous customers on social media you haven’t seen in a while to invite them back into your store. And you’d like to mail coupons to make good on service issues that may have recently plagued your company. 

When you plan these campaigns, you pull up your email lists, recent purchase histories, and customer service call logs. You expect this will be easy, but the fragmented nature of each list type means you don’t know which customers need which message. You have plenty of data, but it’s scattered all over the place.

With data unification, you can bring together all of your customer data into a unified view to gain insight and streamline those decisions. 

This type of data-driven marketing is an essential skill for any business. For businesses without organized customer information, it might be just out of grasp. Fragmented customer data can cause several issues with customer segmentation, cross-channel attribution, and the customer experience. Let’s unpack how data unification can overcome these challenges and how you can implement it for your business. 

What is Data Unification?

Data unification is the process of consolidating and combining data from several sources, formats, and systems to create a single dataset. A unified dataset provides a coherent, consistent, and comprehensive source of information. This makes analyzing data, getting insights, and making informed decisions easier.

What is the difference between data unification and data integration?

When it comes to data unification vs data integration, you might see the terms used interchangeably. But they’re not identical. These two concepts have subtle differences, especially regarding the scope and objectives.

Data integration

Data integration focuses on merging data from several sources into a central storage system like a data warehouse or lake. The idea is that this data is easily accessible. Most of the time, the process involves extracting, transforming, and loading (ETL) processes to convert the data into a common format and structure so it’s compatible with the target storage system.

Data unification

Data unification goes beyond merging the data and emphasizes a consistent, standardized, and unified view of it across the entire organization. Unification’s primary goal is to eliminate inconsistencies and duplicates in data. When you pursue data unification, you want to ensure all users can access clean, accurate, and reliable information.

Data unification uses ETL processes but also involves data cleaning, validation, normalization, and enrichment to improve data’s overall quality and usability. If you want the most accurate data possible, focus on unification over integration.

Why is Data Unification Important for Cross-Channel Campaigns?

Having the correct data for your customers and audience is essential for success. Not having the right information could be a recipe for a real headache, and it starts with fractured data from several sources. 

A customer’s information rarely remains constant. Addresses and phone numbers change. They might use two handles on social media platforms that don’t even match their legal name. Or they may make a large purchase but refuse to sign up for an account and check out as a guest.

At any point, you may have four or five ways to contact this customer, and none of them match up. Fragmented customer data hinders your ability to create an effective cross-channel marketing campaign that touches them at the various points they interact with you.

This is where your efforts to unify data come into play. You use available tools, such as a CRM or data management platform (DMP), to match the “Kelly Neal” in your customer service team’s database to @kneal1985 on Twitter, and so on. When you unify the data, you won’t overlook them when segmenting audiences and avoid sending duplicate marketing emails or text messages.

Benefits of Customer Data Unification

Customer data unification offers plenty of benefits, from giving you a better picture of how customers interact with your brand to the ability to personalize your marketing efforts. Brands that unify their data and use it to empower personalization and customer service efforts have more engaged, happier customers. 

Let’s dive into how these benefits impact your brand’s marketing strategy and overall customer journey.

Improved customer insights

Data unification takes the guesswork out of understanding your customers. When you have accurate data that you’ve grouped and organized, you can better interpret your customers’ habits, preferences, purchases, and more. This allows you better control over the messaging you send them through audience segmentation. It’ll also help you determine which of your channels is most effective.

More personalized marketing campaigns

Why is personalizing marketing campaigns to your consumers’ interests important? For starters, it lets you reach customers in the way that’s most useful to them. Customers are more likely to convert when you target them with marketing that addresses their needs, whether through the proper channels or with the correct verbiage and imagery.

For example, with accurate, unified data, you can direct an email marketing campaign to a current customer who recently purchased a new laptop computer and remind them about accessories and technical support options or offer a delayed customer service survey.

Fewer than 50% of DTC brands say they are able to use key marketing strategies like segmentation and cross-channel campaigns due to a lack of technology and quality data. Customer data unification enables these more advanced marketing strategies for your brand. 

Increased customer engagement

When you personalize marketing and consolidate interactions across channels, you stand a better chance of connecting with your customers. The right segmentation ensures the right messages get to the right customers, and the ability to tailor that content to their specific interests means they’re more likely to respond — hopefully with their dollars and not with complaints.

Improved customer satisfaction

Taking steps to unify customer data can also help cut down on complaints. With fragmented data, you risk calling your customers by the wrong name over the phone or via email. Or you might have incorrect details about their consumer behaviors, which can lead to sending irrelevant marketing to them. For example, a customer may complete a purchase but continue to see cart abandonment ads due to disjointed data. 

With data unification, you can be confident that targeted messages you send the customer are relevant to their needs and past purchase history. It also helps you quickly resolve service issues they may have by looking that information up in your systems.

Increased sales

A customer’s journey from discovery to purchase can sometimes be long and winding. While your teams may be collecting valuable customer data along that journey, too many businesses are unable to leverage data points due to siloed teams and platforms. 

Unified data enables your teams to get a more complete picture of your customers and their journeys. By better understanding your customers and where they are in the sales cycle, you can ensure your marketing is reaching the right people at the right time — and improve your sales.

How to Unify Customer Data

So you want to begin the process of data unification. How you unify your customer data is just as important as why. If you don’t take the time and energy to follow best practices, you might not see much benefit from consolidating information.

The following tips can help reduce the stress of normalizing and unifying your customer data so that you can rely on it to create better, more cohesive cross-channel marketing campaigns that actually reach your customers.

Identify your data sources

You can’t clean or optimize your data unless you know exactly where it’s coming from. Identify your internal and external data collection resources. Typical data sources include:

• Customer service portals

• Email lists

• CRM software

• Physical mailing lists

• Basic spreadsheets

The reason you’re identifying these data sources is to ensure you’re aware of inconsistencies in formatting. For example, your email list may not use customers’ last names, but your primary CRM software does. Or one platform uses m/d/yy formatting while another uses mm/dd/yyyy. These inconsistencies can cause issues as you merge data into one platform. That’s why you should clean data as part of the unification process.

Clean and normalize your data

Cleaning your data isn’t complicated. You just go through a dataset and remove any inaccuracies or inconsistencies. Cleaning data involves checking for redundancies or errors and removing them. This way, the datasets are ready to go when you combine them.

There are a number of tools available to assist you with the task — from validation tools like Experian Data Quality to data cleaning and matching tools like WinPure and OpenRefine.

Cleaning data is also an excellent time to nail down (and document) conventions for names, dates, and other required fields.

Integrate your data into a single platform

The best way to ensure consistent data is to migrate it to a single platform. When you have a single destination for customer data, you won’t have to second-guess whether the information is correct. And you won’t have to cross-reference datasets to glean actionable insights.

The prospect of migrating that data sounds daunting, but it really isn’t. Automation makes migrating and validating user data easier than ever, freeing up your time to focus on what counts. Automation also removes the potential for human error, whether that’s missing a form field or spelling something wrong because of errant keystrokes.

When migrating your data, make sure you’re choosing the best platform for the job. Depending on the data you’re moving, you could use various platforms like CRM software or data management platforms (DMPs).

Create a customer profile for each individual

After you migrate the data, create customer profiles for every individual. Use all the data you have at your disposal such as customer-provided data (like their email address or first name) and digital exhaust (location, browsing history, or preferred device). 

Not only does this help inform how and when you market to these people, but it also allows you to use that first-party data to create robust buyer personas. If you know the exact kinds of people who frequent your business, you can learn who best fits your intended audience.

How to Use Customer Data for Cross-Channel Campaigns

When you have customer data that offers insights into when and how these people interact with you, you can create marketing campaigns that reach them no matter where or when they’re spending time online. But to do that, you have to leverage your unified data analytics appropriately.

Segment your customers based on their interests and behavior

Segmenting your audience isn’t a new marketing tactic, but it’s much easier when you have appropriate data. When you invest in proper tracking, you can see what your users are doing on your website, in email messages, and in-store. Using data to see which items customers shop for allows you to put your customers in the right buckets.

If you have a customer who rarely opens email campaigns related to women’s clothing but consistently looks at men’s options, you can probably assume they’re more interested in that part of your business.

Create targeted marketing messages for each segment

Once you know what your customers are shopping for and how they interact with you, you can create targeted marketing messages for them. If a customer shops with you at least once a week, you can tailor messaging and promotions around new product launches. If you have customers who haven’t purchased within the past six months, you can send marketing to them that invites them back in.

It’s important to ensure those tailored messages are authentic because customers can tell when they aren’t. According to the consulting firm McKinsey & Company, 71 percent of customers expect you to deliver personalized interactions. What’s worse, more than three-fourths of consumers get frustrated when it doesn’t happen.

Deliver your messages through the channels that your customers prefer

The beauty of cross-channel marketing is that it allows you to reach your customers across multiple mediums. Still, it’s important that you deliver your messages through the channels your customers enjoy. 

Depending on your brand presence, your efforts may be better suited to emails, SMS messages, social media ads, or display ads. The best way to analyze this data is to use cross-channel attribution tools to see which messages have the most impact. For example, you may find that your target audience is more receptive to sale announcements via SMS message than social ads.  

Data unification allows you to understand better where your customers are coming from. Chances are that if most of your customers are clicking on social ads but ignoring your emails, there’s an issue to uncover. Maybe your email subject lines aren’t compelling. Perhaps your text message campaigns are more annoying than educational.

When you have unified data available, these preferences become clearer and easier to act upon.

Track the Results of Your Campaigns

Cross-channel marketing gives you abundant resources to reach your customers, but you must pay attention to the data to ensure that those messages land when and where they need to. If you’re not using a solution to track and monitor those campaigns’ results carefully, your marketing may not be as effective as it can be. 

The best way to analyze your cross-channel marketing is to use the right platform. AdRoll removes the guesswork from your marketing reporting efforts with our cross-channel performance dashboard. Track and optimize your performance from one place to remove ambiguity and make the most of your unified customer data. Get started today.

Last updated on August 8th, 2023.