We live in a data-driven age.
Businesses of all sizes—regardless of industry, product, or service—are facing an increasingly complex situation when it comes to managing all of their data. Customer data can be especially difficult to manage; yet, it’s the most important type of data that a business owns.
So, what should a modern organization do to effectively manage all of their customer data? Implementing a CRM is an essential step. That being said, simply signing up for a new piece of software (or switching CRMs) is no guarantee for success.
To reduce risk of failure and maximize the impact of customer data, forward-thinking companies take a strategic approach by proactively organizing and centralizing their customer data. In this post, we’ll discuss why customer data is so important, how a CRM can help, and best practices for structuring your CRM so that it provides clarity (and not confusion).
Why a structured approach to data is worth the effort
Before we dive into specifics about organizing your CRM, let’s briefly reflect on why doing so is worth the effort. After all, you’re a busy person. Your team is busy. Spending time on non-revenue producing activities, such as data organization, can feel like a major distraction.
On the other hand, failing to effectively manage customer data can have devastating consequences on your business. When data is spread across inboxes, spreadsheets, shared documents, and other data silos, your teams cannot perform at peak efficiency. They spend more time chasing down customer contact information than actually engaging the customers they aim to serve.
Organizing customer data in a central, shared database overcomes the inefficiencies of data silos by providing:
- Quick and easy access to relevant customer information
- A single source of truth for internal collaboration
- Transparent reporting for enhanced accountability
- Less confusion, fewer overlapping systems, and a lot less craziness
And, you have to keep in mind the growing concerns about data privacy and security—especially in light of recent regulations, such as GDPR. In today’s business environment, proactive data management has rapidly become an essential element of compliance and risk management.
How a CRM helps
One of the most challenging aspects of managing customer data is knowing the right way to structure it.
Sure, you could keep everything in a spreadsheet on a shared network drive. That’s certainly one approach to managing customer data (and, surprisingly, one that many companies still rely on). However, do-it-yourself solutions, like spreadsheets, have a number of obvious drawbacks—not the least of which includes a lack of structure.
To illustrate this point, let’s imagine that you’ve been tasked with building a spreadsheet to house all of your accounts, contacts, and leads. Where would you even begin? Should leads and contacts be maintained on separate tabs? Which column headers (data fields) would you create? What would be the best way to draw connections between organizations and their related contacts? Where will sales reps add their updates and notes? Organizing customer data in a spreadsheet is not as easy as it may seem. Too much flexibility, it turns out, creates nothing but confusion.
Compare this approach to that of using a CRM, like Insightly. Unlike a spreadsheet, most CRMs come with prebuilt data structures that help you bypass basic questions about data organization. As an example, Insightly’s standard record management structure looks like this:
Prospective customers are entered as lead records. Leads are converted to opportunities, organizations, and contacts. Once opportunities are won, they’re converted into projects. Each lead, opportunity, contact, and project has a set of standard fields that help to ensure consistency of data collection.
As a relationship advances, the entire customer journey remains perfectly intact. Nothing gets lost along the way, and there’s no time wasted building pivot tables for reports. Everything feeds into a customer data management system that’s already been tested by tens of thousands of customers who have gone before you. (Of course, you can always customize your CRM to your exact needs, if necessary.)
In short, a CRM provides an out-of-the-box solution for collecting and managing data in alignment with your customer journey. After all, not every customer buys on day one.
Best practices for keeping customer data clean and organized
A CRM gives you the structure—but you still need the right habits, CRM best practices and processes to keep your data reliable over time. These practices will help.
Stay focused on adoption
Some companies fail to successfully implement their CRM. Failure has many causes, but lack of user adoption is certainly at the top of the list.
Adoption is not a one-time project.
Smart companies establish ongoing accountability measures and training programs aimed at maximizing system utilization—and, as a result, ensuring that users are collecting customer data as expected.
Integrate and consolidate systems where possible
Relying exclusively on manual data entry is not a fail-proof strategy. People forget and make oversights. Supplementing manual data collection with automated CRM integrations increases the flow of customer data and lessens the administrative burden on end users.
Better yet, look for ways to reduce the need for third-party integrations and simplify your tech stack. For example, with a unified CRM for sales and marketing, users no longer need to build data integrations to third-party email marketing automation systems.
Build a practical data governance framework
“Data governance” sounds like something that requires a steering committee and a six-figure consultant. The reality is, it doesn’t.
At its core, governance just means answering basic questions your team needs to agree on:
- What’s a lead versus a contact?
- When should a lead get passed to sales?
- Who updates account information after a call?
Without documented answers, you end up with inconsistent data entry—one rep logs “ABC Corp” while another logs “ABC Corporation, Inc.”
Start simple with a shared doc covering definitions for your core record types and naming conventions. Assign someone to run a quarterly spot-check for duplicate and incomplete records. That’s it.
A lightweight framework people actually follow beats an elaborate one that gets ignored.
Establish regular data cleansing cadences
Customer data decays faster than most teams realize.
In fact, B2B contact data decays at roughly 2.1% per month—and that compounds to over 22% annually.
Factor in job changes and company restructuring, and you’re looking at a significant chunk of your database going stale every year. Waiting for problems to pile up just makes the cleanup harder.
Build cleansing into your rhythm instead—monthly or quarterly works for most mid-market teams.
Focus on high-impact issues first:
- Duplicate records
- Incomplete fields on active opportunities
- Contacts with bounced emails
- Accounts with no recent activity
Most CRMs let you create saved searches or dashboards that surface these problems automatically. Run them on a schedule, assign cleanup to specific people, and keep sessions short.
Thirty minutes of focused data maintenance each month prevents the “garbage in, garbage out” spiral that makes CRM data useless.
Limit user permissions
Members of your sales development rep (SDR) team probably do not need access to sensitive customer billing information. Likewise, a graphic design contractor who occasionally helps with email marketing campaigns may not need access to customer names or emails. Be selective about who can access and edit your data.
Be strategic about customizations
True, it would be nice to know each customer’s date of birth so that account executives can extend their birthday greetings. But is this data field actually necessary to the success of your business? Does it move the needle enough to impact your bottom line? Scrutinize every customization idea in light of its impact on business.
Customizations, when used strategically, can be helpful. When used flippantly, customizations can create clutter, distractions, and muddy your data.
Dispose of data when appropriate
Collecting and organizing customer data should not be confused with data hoarding. Not every record should be retained indefinitely. Developing an effective disposition strategy can keep data tidy and align with ongoing data security and compliance initiatives.
Organize your customer data with Insightly
Data management processes and systems may not help you increase sales or decrease the cost of goods sold on day one.
But when done the right way, prudent use and collection of data can have a lasting impact on the long-term health of your company—especially as you scale your operations to serve even more customers.
That’s where Insightly comes in.
Insightly gives small to mid-sized teams the structure they need without the complexity they don’t. Unlike enterprise CRMs that require consultants to configure or spreadsheets that fall apart at scale, Insightly meets you where you are.
With Insightly, you can:
- Build custom fields and page layouts without developer tickets or IT backlogs
- Integrate with 2000+ tools through AppConnect to eliminate manual data entry across systems
- Start with prebuilt data structures that map to real sales workflows—leads, opportunities, contacts, and projects—out of the box
Ready to organize your customer data? Request a demo with an Insightly rep to receive a free business and data needs assessment.
Common questions about organizing customer data
Here are answers to common questions about managing and organizing customer information in a CRM.
How do you collect customer data in a CRM?
Data enters your CRM through multiple channels: manual entry by sales and support reps, web forms that capture leads directly, integrations that sync data from other tools, and imports from spreadsheets or legacy systems.
The key is reducing friction on manual data entry (fewer required fields means higher adoption) while automating collection wherever possible. Most mid-market teams use a combination—reps log calls and meeting notes manually, while lead capture forms and tool integrations handle high-volume, repetitive data collection automatically.
What is customer data management (CDM)?
Customer data management is the practice of collecting, storing, organizing, and maintaining customer information so it stays accurate and useful over time.
It covers the full lifecycle—how data gets into your systems, how it’s structured and categorized, how it’s kept clean, and how it’s protected.
CDM vs CRM: What’s the difference?
CDM is a practice—the processes and policies for handling customer data across your organization. CRM (customer relationship management) is a tool—software that helps you manage interactions with customers and prospects through features like lead and opportunity tracking.
Your CRM is where much of your CDM happens, but CDM also includes data governance policies, cleansing processes, and how data flows between systems. Think of it this way: CDM is the discipline, and CRM is one of the tools you use to practice it.
CRM vs CDP: Which one do you need?
A CRM manages direct interactions with customers—tracking deals, logging calls, managing contacts and accounts, and supporting sales and service workflows.
A customer data platform (CDP) consolidates data from many sources into unified customer profiles, primarily for marketing segmentation and personalization across channels.
Most mid-market B2B companies need a CRM as their foundation—it’s where your sales and service teams actually work. CDPs are more common in B2C or enterprise environments with complex, multi-channel customer journeys and heavy behavioral data requirements.
If you’re choosing between them, start with CRM. You can add a CDP later if your marketing needs demand unified profiles across dozens of touchpoints.
