Customer Data Management: How to Perfect Your CDM
According to an IBM report, 83% of companies suffer from data inaccuracy. That means the majority of data-driven companies are relying on dirty data to make decisions.
By paying close attention to data quality and ensuring they use clean data, companies can make smarter decisions—and they’ll see the improvement in their bottom line.
The reason these companies have dirty data in the first place is that data collection can get confusing very quickly. Companies often have multiple departments collecting many different data points on individual customers, from demographics to individual data . That can lead to each department collecting the same data point as another department, collecting data in the wrong ways, or collecting more data points than they need.
The end result is too much useless data, which often leads to data security issues and confusion about what your company is doing with the data it’s collecting.
A good customer data management strategy can help you avoid confusing data like this. You’ll get a lot more functionally out of your data if you have set guidelines for customer data management. The first step to building your guidelines for customer data management is understanding what customer data management is and the principles behind it.
What is customer data management?
Customer data management is the process of acquiring, organizing, and using customer data to better understand customers and ultimately increase conversions and retention. Customer data management encompasses the tools businesses use to collect and analyze customer data, the ethical framework of acquiring customer data, and the security measures involved with storing and accessing this data.
When talking about customer data management, we’re usually referring to first-party data, meaning data collected by your company and used by your company. This can be anything from data about how website visitors browse your website to transaction data about what visitors have purchased.
Any software that stores customer data is involved in management, which is where it gets difficult and messy. You might have three different tools used by three different departments all collecting the same customer information in slightly different ways. Organizing all of that data in a way that makes it useful for your entire company is the ultimate goal of customer data management.
6 principles for improving your customer data management
When it comes to customer data management, there are six principles that you need to follow to make sure that your data works for you.
Principle 1: Have a data governance strategy
Data governance is the first principle of good customer data management because data governance will help you identify what data you will collect and how it will be collected. Data governance will also keep all employees on the same page about your plan for customer data management.
Every data governance strategy will have three parts:
Alignment: This step standardizes customer data collection across your company. Validation: During validation, you’ll confirm that all data is being collected properly. Enforcement: This ensures that any changes to data collection will go through the proper channels so that all collected data is useful and collected in the correct way.
The end result of your data governance strategy will be a tracking plan, or data dictionary, that clearly explains every piece of data that you’re collecting, who is using it, what it’s being used for, and who owns it.
Typeform is one company that benefited from implementing a data governance strategy. Prior to doing this, they didn’t even realize how messy their data was. When someone on the marketing or analytics team tried to put their data to use in analytics tools, they often found too many events monitoring the same things. That made it unclear which data was accurate and which data wasn’t.
Typeform also found that they had multiple events for different data points but with the same event name. That made it impossible to figure out why that data was being collected in the first place.
Once they implemented a data governance strategy, they were able to clear up all of this confusion. Typeform now has standardized data that could be put to good use.
Principle 2: Focus only on critical data
You need to make sure you’re only collecting data for your customer database that’s actually useful to your company. Collecting unnecessary data leads to your customer data platform (CDP) becoming overloaded. Unnecessary data can also lead to you collecting data that makes your customers uncomfortable.
Audit every piece of data you collect and ask yourself these questions:
Who needs this data?
What does it do? What’s the use case for this data?
If we didn't collect it, could we still operate in the same way?
If you don’t know the answers to those questions, that doesn’t mean toss that data point out. Ask around. Maybe there’s a reason for it.
For example, let’s say you’re collecting data about the company revenue of your website visitors. Seems like that could be a good data point, right? But, when you ask the four questions we mentioned above, you find out that the data doesn’t address any business needs, no one is using it, and not collecting it won’t change a thing. In that case, get rid of it.
Collecting unnecessary data can land your company in hot water. That recently happened to a publicly traded company. The company was collecting data about its customers, even when the customers had finished using the company’s service.
The FTC filed a complaint against the company, and as a result, they were faced with negative press and forced to reverse their decision.
Principle 3: Avoid data silos
Data silos happen when data is being collected by different departments in the same company, and they’re not sharing that data with each other. This usually isn’t intentional. It comes from a lack of a data governance or data orchestration strategy (and the fact that there are thousands of data analytics tools and data sources). Customer support, product, and dev teams all working with different tools, resources, and datasets is a recipe for confusion.
Say you’re trying to understand how people feel about your product, but your team is completely siloed by department.
The tool your social media team uses to respond to customers doesn’t share data with the customer service team or the product success team. Both customer service and product success would love to know what feedback they’re getting on social media, but it doesn’t happen because of data silos.
One of the data points your website analytics team monitors is cart abandonment. That’s a number the development team would like to know, so they can take steps to reduce cart abandonment if necessary. Unfortunately, because of another data silo, the development team doesn’t have that information.
These types of problems can happen across all departments. Finance might accidentally be holding back useful data from the sales team. The sales team might use a customer relationship platform (CRM) that has data that the marketing team needs. You can see how data silos can become a huge problem. Data works best when it's shared across departments because that can promote collaboration and problem-solving across the company.
Data collaboration allows marketers to get a complete view of the customer journey and the various touchpoints in it. With a Customer Data Platform (CDP) you can use this data to create a single customer view that consolidates your data into unified customer profiles. It allows the product management team to develop products that better align with customer expectations. It allows you to create personalized marketing campaigns targeted to specific stages of the customer journey. It can even help the analytics team get a more accurate view of customer acquisition costs and lifetime value.
Data shared across departments also leads to a better customer experience. You may have experienced a data silo when talking to a customer service representative at a company. If the customer service rep is asking you questions about things they should already know, there’s a good chance that the company isn’t sharing data across departments. When that’s the case, it gets worse if you’re transferred to another department and have to repeat the process all over again.
Principle 4: Data security is essential
Data security has a simple definition — “the protection of data from unauthorized access, use, change, disclosure, and destruction,” but it’s a very complex topic.
It’s one of the most important parts of customer data management. No matter what type of data you’re collecting from your individual customers, they want to know that their information is safe. Not only will a data breach give your company a lot of negative press, but it can also be very costly to your company. In the United States, the average data breach costs companies $7,910,000.
If you’re using a customer data platform to manage your customers’ data, you might not have much say in that platform’s data security standards. That’s why it’s crucial to make sure the platform you’re using operates with an ISO 27001-based security program. That security program means that the customer data platform is constantly reviewing, refining, and improving its security practices.
Principle 5: Have a Data accuracy process
The accuracy of your data can be affected when you collect it, but it can also be affected months or years down the road because data can change over time — this is known as data decay.
Data inaccuracy at the point of collection can happen when a company doesn’t have a defined data governance strategy. For example, even a simple data point such as dates can cause data inaccuracy. Are you collecting dates in the MM/DD/YYYY format or are you using DD/MM/YYYY?
Data inaccuracy can also happen if data collection events aren’t set up properly. To solve this problem, use automatic data validation. This automation will test your tracking code to make sure it’s working properly.
Over time, data can become inaccurate through data decay. This happens when there are changes in email addresses, phone numbers, physical locations, and more. For example, that email address you collected from the Chief Information Officer at Company X might be wrong now if that person left the company.
Clearing up data decay can be as simple as dumping data from prospects and customers who haven’t engaged with your company in a certain number of months or years.
Principle 6: Comply with data regulations
As data privacy becomes more important to the public, you’re going to see more governments enacting laws similar to the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA).
These laws have already changed the way companies collect and store their customers’ data. It’s now crucial to get consent to collect data about your website visitors. This is why many company websites now have banners asking for your permission to use your data.
Another important piece of both the GDPR and the CCPA is that they require companies that collect data about their users to give those users access to their own data. Users need to be able to not only see what data you’ve collected from them (such as demographic or behavioral data) but also request that you delete that data.
The process of deleting customer data can become difficult when you’re using multiple tools to collect data on your users. A single user’s data could be stored on 10 different tools. A good customer data platform will make GDPR & CCPA compliance much easier by allowing you to delete user data from all of your tools at once.
Even if your company doesn’t have a physical presence in Europe, it can still be subject to GDPR if you’re collecting data on website visitors from the European Union. You have two options when an EU visitor accesses your website:
Completely block people from the EU from accessing your website
Use consent management on your website
There’s a chance that the United States will create a law similar to the GDPR, so it’s a good idea to get ahead of this now so that you’re not scrambling to update your website when it happens.
Customer data management doesn’t need to be difficult
To recap, the six principles you need to follow are:
Have a data governance strategy
Focus only on critical data
Avoid data silos
Data security is essential
Have a data accuracy process
Comply with data regulations
Following these six principles of customer data management will go a long way to simplifying your data collection and making your data more useful.
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