A Brief Guide to Customer Data Management

By Team Session AI on March 6, 2021

Everything you want to know about collecting and managing customer data

It’s no secret that digital marketing has taken over. If you’re not keeping up to date on the best practices of how to compete in the digital marketing age you’ll quickly be left behind in the digital dust. Customer data management has always been a part of business, even prior to the digital age.

Farmer Joe had a book with all of his customers’ names and orders. He put notes in his book about each customer, found out what they liked, and over time discovered what crops he needed to grow to better serve his customers and grow his profits.

Today Farmer Joe uses technology to do the same thing, but with more detail and efficiency. Every business today engages in customer data management on some level. Simply put, customer data management is the process of collecting, organizing, and using customer data to better serve your customers.

Customer data management is comprised of the tools businesses use to collect customer data, analyze it, the ethical considerations of acquiring the data, and the security involved with storing and accessing it.

CDM technology first started gaining traction in the 1990s with customer relationship management (CRM) systems. In the 2000s the technology evolved with the introduction of data management platforms (DMPs) with data warehouses managing cookie IDs. Starting in the mid-2010s, customer data platforms (CDPs) merged the CRM and DMP with features that included multichannel campaign management, tag management, and data integration in one platform.

The unifying theme throughout CDM’s technological evolution has been the need to gather data, manage the quality, and keep it secure and available to use.

Today, customer data management tech has evolved to the point where it can break down siloed departments and combine customer data with product data and other information. Organizations can now see previously hidden relationships and connections and create a truly 360-degree customer view.

This article will give you the latest information you need to know about the most important components of CDM:

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Collecting Customer Data:
types of data, sources of data, and how to collect it.
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Managing Customer Data:
best practices, strategy, security, and types of tools.

Memorable Consumer Engagement ad

Why Should You Invest in Customer Data Collection?

Customer data management

Customer data collection often gets bad coverage by the media. It’s framed as manipulation and a breach of privacy, but is it? Like most things, it comes down to intent. Most companies can only survive by solving their customers’ problems. Customer data collection is just a tool that helps companies get better insights into how to serve their customers and solve their problems.

When you invest in customer data collection you improve your understanding of your customer. The larger your business, the more difficult it becomes to serve customers on a personalized level. Data collection gives you a better view of each customer and gives you valuable data to better solve their problems.

Collecting customer data helps you identify where you can improve or expand. Looking at transaction data, for example, reveals what products your customers love most.

Customer data helps you more accurately predict the future. If you’re a clothing store, you might discover that your customers prefer pastel colors during spring and summer, and gravitate towards darker shades in the fall and winter months. Once you recognize this, you can introduce the right colors at the right time and better service your customers. You boost sales and can re-invest into your business and expand customer options.

The more you know about your customers the more you are able to personalize their experience. You can custom tailor messaging they receive that matches their interests and preferences. You can even personalize your customer’s experience when they visit your website by using cookies to determine where they are on their customer journey. Serving them what they expect and want at the right time can only be accomplished with customer data collection and management.

What Types of Data Should You Collect?

Customer data management

It’s easy to get seduced into collecting every type of data that moves. The problem is collecting it is only the first step. Collected data must be analyzed, stored, and used in a useful way. So collecting the wrong data can waste a lot of time and resources. Like with anything, you need to have a data strategy in place to maximize resources and return on investment.

Identity Data icon

Identity Data – Every company should be collecting customer identity data. Identity data is the basic information you need to build a profile. It includes the contact details needed to connect. After a buyer persona is created, the way you choose to communicate is typically matched to the specific stage the customer is in within their customer journey. Identity data will include collecting the following information:

Name: title, first name, and last name
Personal Details: date of birth, region, gender, etc.
Address: shipping address, billable address, etc.
Social Networks: Facebook, LinkedIn, Twitter, Instagram, etc.
Account: user IDs, payment preference, etc.

Collecting identity data is typically easy and straightforward. Most of the time you’re already collecting this type of data when your customers enter their payment details at check out or when signing up for a newsletter or lead magnet.

Descriptive Data icon

Descriptive Data – This type of data is considered a step up from identity data. The goal of descriptive data is to collect additional demographic information to flesh out customer personas. Doing this puts you one step closer to using predictive analytics to optimize timing for your marketing. Descriptive data includes:

Family: marital status, number of children, relationships, etc.
Lifestyle: homeownership status, car, pets, hobbies, interests, etc.
Education: high school, university, advanced education, etc.
Career: job description, income, professional background, etc.

It’s not always easy to collect quality descriptive data. Often companies rely on in-depth questionnaires for this type of data collection. Open-ended interview questions, in-depth surveys, focus group interviews, and advanced lead forms can all be used to capture descriptive data.

Quantitative Data icon

Quantitative Data – The next type of data you’ll collect will tell you how your customer is interacting with your business using operational or quantitative data. You collect the data throughout the customer journey. It measures discovery details, channel interactions, and conversion-specific steps that lead to purchases. Examples of quantitative data include:

Online/Offline Transactions: products purchased, amount of purchase, time of purchase, order/subscription values, order/renewal dates, cart abandonments, product returns, etc.
Inbound/Outbound Communication: date, time, channel, opens, clicks through rates, etc.
Online Activity: product views, registrations, website visits, etc.
Social Network: groups, interactions, interests, social handles, etc.
Customer Service: compliant details, customer query details, call center communication, etc.

The main purpose of quantitative data collection is to better understand your customer’s decision-making process with your company. Finding out what led them to discover your business and which channels drive the most conversions is extremely valuable.

There are a number of tools companies use to collect quantitative data including web analytics tools like Google Analytics, website cookies, tracking pixels in emails, and more.

Qualitative Data icon

Qualitative Data – The job of qualitative data is to discover the reasoning behind the choices your customers make. Qualitative data aims at answering the “why”, “how”, and “what.” Why people behave the way they do. How are opinions and attitudes formed? What are the differences between different social groups? Qualitative data includes:

Motivational: the reasons for purchase, customer needs, etc.
Attitudinal: perceived value, rating, feedback, repurchase likelihood, etc.
Opinion: likes/dislikes, preferences, etc.

Collecting qualitative data can be a challenge because of the time commitment required. However, the insights gained can be well worth the time and effort. Most often, qualitative data is collected using industry-related review websites, social listening with monitoring tools, and deep listening feedback form questions.

How Do You Decide to Collect Customer Data?

How Do You Decide to Collect Customer Data media

The most important thing to remember when collecting customer data is to make sure you’re only collecting data that’s actually useful for your company. Collecting unnecessary data will quickly lead to your customer data platform becoming overloaded. Before deciding to collect any type of data ask yourself three questions:

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Who needs this data?
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What does the data do for us?
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If we didn’t collect it, how could it affect our operations?

If you’re unable to answer these questions it doesn’t mean you shouldn’t collect the data necessary. But it does mean you need to learn more about that type of data and find out what it would mean to your business. That’s the only way to know if it’s worth pursuing.

What are the Methods for Collecting Customer Data?

What Methods for Collecting Customer Data media

Once you’ve made the decision to move forward and collect customer data, you’ll need to consider the different tools and methods for collecting. As you can imagine the tools and their sophistication have evolved substantially in the age of digital marketing. Many of the methods remain the same, but how they’re executed has changed with technological advancements.

The Interview icon
The Interview – The interview remains one of the most powerful methods of collecting customer data. Interviews are a great way to get in-depth information and accurate data. However, they can be time-consuming, and costly to conduct. There are three types of interviews marketers use to collect customer data:

Structured Interviews: Simply put, this is a verbally administered questionnaire. These types of interviews are usually surface level and completed within minutes.
Semi-structured interviews: in this method, the questions cover the scope of areas to be explored. It allows for more leeway for the researcher to explore the subject matter.
Unstructured Interviews: this is an in-depth interview that allows the researcher to collect a wide range of information. It combines structure with flexibility and more space to dig deeper into a specific question and answer.

Questionnaires icon
Questionnaires – The questionnaire is another time-tested and reliable way to collect customer data. Typically questionnaires are used to collect data from a group. A questionnaire isn’t a survey, rather it forms part of a survey. A survey is a process of data gathering that involves a variety of data collection methods, including a questionnaire.The three types of questions used on a questionnaire include fixed-alternative, scale, and open-ended. Questionnaires can be cost-effective because of their ability to be administered in large numbers. They can be effective in comparing and contrasting previous research to measure change. They offer actionable data, respondent identity is protected, and they are relatively inexpensive.

However, questionnaires don’t produce qualitative data.

Customer Data Management
Surveys – Surveys are a step up from the questionnaire as they can collect both quantitative and qualitative data. A survey consists of a list of questions respondents can answer in just one or two words. It often gives participants a list of responses to choose from. Surveys are cost-effective and there are a number of third-party developers that produce surveys you can easily incorporate onto your website.
Customer Data Management
Online Tracking – Your website and app are excellent tools for collecting customer data. Every time a prospect visits your website, they create dozens of trackable data points. When you access this data you can see how many people visited, how long they stayed when they clicked on, and a lot more. Placing pixels on your website allows you to read cookies to help track user behavior. Using this data you can build an audience in your data management platform that identifies your “clickers” and “converters.” These groups are the ones who are most likely to become your customers
Customer Data Management
Transactional Tracking – Whether you’re selling products in-store, online, or both, your transactional data can give you valuable insights into your customers and business. You can store your transactional records in a customer relationship management system. The data can come from your web store, a third party you contract with, or your point of sale system. This information can give you valuable insights about which products are most popular, how often people purchase products, and a lot more.
Customer Data Management
Subscriptions and Registrations – Offering customers something of value in exchange for providing information about themselves is one the best ways to gather valuable customer data. You can do this by requiring some basic information when customers sign up for your email list, rewards program, or lead magnet. When creating your forms used to collect information, it’s important to find the right balance in the amount of data you ask for. Asking for too much can discourage participation, while not asking for enough means your data isn’t as useful as it could be.

What is the difference between Primary and Secondary Data?

What Difference between Primary Secondary Data

Market research usually involves both primary and secondary research. Primary research is the research you conduct yourself or hire someone to do for you. It involves going directly to customers in your target market and asking questions to gather information. Examples of primary data include interviews, surveys, questionnaires, and focus groups. Collecting primary data costs more, but gives more conclusive results than secondary data.

Secondary data results from research that has already been compiled, gathered, organized, and published by others. It may include reports and studies by government agencies, trade associations, or other businesses in your industry. For smaller businesses with a limited budget, secondary data can be valuable because it’s obtained faster and is more affordable.

Three Customer Data Management Best Practices

Three Customer Data Management Best Practices

There is a lot of advice on best practices when it comes to customer data management. Nearly all of it is good. However, you could write a book on all the details, so we want to focus on the three most important data management principles.

Define Your Customer
Define Your Customer – Your customer is comprised of the individuals that make repeated purchases from your business. Defining a customer can get convoluted at the enterprise level. One department might define a customer as anyone who’s made a purchase in the last five years as an active customer, while another department may drop them from their list if they haven’t purchased in the last year. Determine which customer attributes to track and manage, and make sure all departments understand how to identify customers.
Unify Your Data
Unify Your Data – Use AI and natural language processing (NLP) across systems to automatically combine all types of collected data into an intelligent omnichannel customer view that’s searchable across all data, structured and unstructured. You want to avoid data silos and create a consistent 360-degree view of your customer.
Make Sure Data Actionable icon
Make Sure Your Data is Actionable – If you can’t trust your data, you can’t depend on it to deliver a good return on investment. Manage your data like the strategic asset it is. Storing your data in a secure data lake that allows you to get the most out of your analytics tools is critical. Transform, cleanse, enrich, and standardize your data.  Make sure it’s fit for use before sharing it. Take full advantage of new AI and machine learning capabilities while automating data management as much as possible.

CRMs, DMPs, CDPs: What’s the Difference?

Customer data management

The evolution of CRM to DMP to CDP is the story of customer data management.

Customer Relationship Management (CRM)

Customer relationship management

Platforms are great tools for engaging with existing customers, information for better service and aiding sales initiatives. CRMs come up short in real-time capabilities. The more you customize your CRM, the more complicated and unmanageable they become.

Data Management Platforms (DMP)

data management platform

Unlike CRMs, DMPs unify anonymous IDs by using purchased data sources. DMPs allow you to piece together second and third-party data from cookies and other behavioral data to divide users into segments. The segments personalize media and advertising. The downside to DMPs is they only store anonymous, third-party data with limited segmentation, making creating a unified customer view with multi-department sharing impossible.

Customer Data Platforms (CDP)

Customer data management

Easily integrates with existing data as well as offline and unstructured data, all in one system. CDPs centralize all of your customer data regardless of what channel or device your customer used. It organizes all the data you collect around the customer, rather than the channel or device it came from. A CDP is what makes a single customer view possible.

CDPs support real-time data streaming allowing for immediate action throughout the customer journey. They enable personalized recommendations. CDPs are built and designed for marketers. Because they can be easily integrated into your existing company environment, without creating custom integrations, they’re a very attractive addition to any business.

Define Your Customer Data Management Strategy

Customer data management

Now that you have a solid view of the customer data management landscape, you need to determine a strategy that fits your business. The best way to support a solid CDM strategy is by using a scalable data management platform that allows you to add new functionality or data as your needs change.

The best end-to-end CDM platforms let you manage and master all of your customer data across the enterprise. They come with data quality and enrichment, data integration, business process management (BPM), data governance, and data privacy capabilities in one package.

With the mass migration to the cloud you’ll also want to consider the different deployment models, whether it be cloud, on-premises, or a hybrid solution.

The best CDM strategies leverage AI and machine learning for streamlining and accelerating data management tasks.

Today’s most competitive enterprises use a CDM platform that allows them to easily add new sources of data from multiple sources such as email marketing solutions, POS systems, call centers, CRM, CDP, DMPs, data warehouses, and more. Platforms with pre-built integrations allow companies to take advantage of different technologies like mobile, tablets, AdTEch, chatbots, APIs, SDKs, Webhooks and more.

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