Customer data encompasses a broad spectrum of information about the people and businesses your company serves. At the most basic level, customer data is an essential asset for understanding your customers and their goals—and, how your business fits into the equation.

In this post, we’ll take a deeper look at customer data and explore best practices for customer data management.

4 primary types of customer data

Names and job titles. Email addresses. Support ticket records. Online reviews. Transactions. Cross-device usage patterns.

The list goes on and on…

Simply put, customer data comes in many shapes and sizes—and, from many sources, too. Making sense of customer data can seem overwhelming, especially without the right perspective. As a result, some companies fail to overcome roadblocks to effective data use, thereby diminishing the impact of their most valuable business asset.

To create some semblance of structure and clarity, customer data is often categorized into groups. Here are four primary customer data groups. 

1. Basic data

Basic personal customer data forms your organization’s fundamental understanding of each relationship. Many—if not most—standard data fields in a CRM could be considered basic data. A contact’s name, email address, phone number, job title, and linked organizations are examples of basic customer data. Demographic data, such as gender and income, or firmographic data, such as annual revenue or industry, are also basic customer data.

When aggregated and analyzed across multiple contacts and/or organization records, basic data builds the basis for audience segmentation. Then, by using tags or reports in your CRM, you can begin to visualize how many customers share common attributes.

2. Interaction data

Sometimes referred to as “engagement” data, “interaction” data includes the many touchpoints that customers have with your brand. Interaction data is particularly useful for informing decisions that pertain to the buyer journey. Pageviews, ebook downloads, social shares, email inquiries, and demo requests are common examples. 

Interaction data is often anonymized and aggregated for high-level reporting purposes (with the ability to “drill down” for further insights). For example, marketing consultants spend considerable time studying interaction data in web analytics platforms to understand campaign effectiveness and return on advertising spend (ROAS). In addition, some marketing platforms provide user-level reporting to track where each customer came from.

3. Behavioral data

“Behavioral” data offers insight into the customer’s experience with your actual product or service. (Note: The difference between interaction and behavioral data can seem fairly nuanced depending on your business and industry.)

Technology companies are frequently cited as premier users of behavioral data, such as free trial sign ups, user account logins, feature utilization, user license additions, deactivations, and downgrades. 

That being said, almost every organization maintains some type of behavioral data (even if they do not realize it). If you’re a service-based company, you probably send detailed invoices that inform customers about why they’re being charged. Why not leverage this data to hone in on your most popular solutions? If you’re a manufacturer, you regularly receive purchase orders that are tracked in your ERP. In addition to helping you accurately fulfill your customer’s request, each purchase order represents an excellent opportunity to understand customer preference and identify future trends.

4. Attitudinal data

“Attitudinal” data helps you understand what customers think about your company and the solutions that you provide. Unlike the other three types of data, attitudinal data delivers a first-hand account of what customers actually think. Online reviews, support ticket comments, and satisfaction surveys are sources of attitudinal data.

Here’s the big problem with attitudinal data: Some customers are louder than others when it comes to expressing their opinions about your company. Does one scathing review from a dissatisfied person truly reflect the sentiment of your entire customer base? Probably not. That’s why consistent and proactive collection of attitudinal data from a statistically significant group of customers is key. 

Collecting and managing customer data

Once your team has established a firm grasp of these four primary types of customer data, they can begin discussing how best to collect it. Here are a few questions to think through as you formulate your data collection and management plan.

What are your customer data goals?

What are our data goals?

On its own, data offers minimal value to your organization. Start with the big picture. Do you want to harness data to improve customer experience or develop new products or features? Is accelerating revenue growth or profit maximization the primary motivator? Discuss and agree on your “why” before getting bogged down in the minutiae of data talk.

How do other companies in our industry leverage customer data?

You’re probably not the first company in your industry to seek a more data-driven culture. Research how similar organizations have leveraged customer data in a secure and scalable way. What are their data goals? Supplement your planning efforts with your findings.

What data is essential?

Accessing and integrating customer data requires effort and, likely, an upfront opportunity cost. As a result, you may not be able to have all of the data that you want on day one. What data is critical to the current and future health of your business? How does it align with your stated data goals? Sequence the most essential data first and build a backlog of secondary data to revisit in the future.

What is the cost of accessing and managing data?

In addition to intangible opportunity costs, you may also encounter tangible expenses, such as software and consulting fees. Does your current CRM offer the right mix of integrations to properly ingest and report on your essential data? Does your CRM vendor charge a premium for AI-driven features that make predictive analytics a reality? If you do not already have a CRM, what is the cost to evaluate and implement a system from the ground up? 

Do we have the right tech stack?

Sometimes less is more. Trying to integrate multiple systems is more work than just starting over with a unified platform that does everything you need. 

Case in point, I have one client who is thinking about switching CRMs. For years they’ve relied on separate CRM and marketing systems, creating constant confusion in the customer data management process. Insightly Marketing, which consolidates CRM and marketing under one platform, could be a viable solution for simplifying and elevating their customer data.

What are the risks?

Data protection regulations (like GDPR) along with industry-specific data security requirements are becoming commonplace amidst our data-centric economy. Understanding security risks and implementing safeguards to protect customer information are key steps for any company that wishes to use data.

How will we maintain clean data?

No one wants bad data. Without the right systems and processes, however, bad data will become an all-too-familiar reality. To keep data clean, implement proactive data deduplication measures, keep your staff well-trained, and look for opportunities to eliminate manual data entry.

What is our expected (and actual) ROI?

Anything worth doing should be done the right way. The use of customer data is no exception. If your primary goal is to reduce churn, put a hard number on it. For example, “We expect to reduce churn by 10% by effectively using customer data.” Once agreed to, set a process to measure progress toward the achievement of this goal. 

Maximizing data’s impact

It’s clear that customer data is more important than ever before. 

With the right mix of tools, systems, and processes, your organization will put itself in a position to effectively use customer data and, ultimately, achieve more goals and grow business.

How are you managing your customer data? What are the systems and processes you use to help you make the most of your customer insights?

You can get a free needs assessment from Insightly and discuss best solutions for your immediate and long-term customer data management goals. Request a demo—it’s free and no commitment is required. 

 

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