4 Types of Data to Track in Your CRM (& How to Structure It for Maximum Impact)

As a sales and marketing leader, you know your customer relationship management (CRM) system is the lifeblood of your revenue-generating engine. It‘s the centralized repository of every data point you have about your prospects and customers. And when populated with high-quality, well-structured data, it empowers your team to engage buyers more intelligently, close deals faster, and grow accounts strategically.

But according to research by SiriusDecisions, 60-70% of B2B data in the average organization is incomplete, out-of-date, or inaccurate. Bad data is a pervasive problem that‘s eating into company profits, to the tune of $3 trillion per year in the US alone.

The costs of bad CRM data are both acute and far-reaching:

Cost	Impact
Wasted marketing budget	Inaccurate targeting, high bounce rates, unsubscribes
Missed sales opportunities	Inability to reach prospects, longer sales cycles
Poor customer experience	Wrong information, irrelevant communications
Employee frustration	Lack of trust in the system, resorting to shadow CRMs
Inaccurate reporting	Skewed metrics, misguided decisions

To avoid these pitfalls and unleash the full power of your CRM, you need to focus on not just collecting data, but collecting the right data and ensuring it‘s complete, accurate, and usable. Here‘s a deep dive into the four types of data to track in your CRM and how to structure them for maximum impact.

1. Identity Data

Think of identity data as your digital rolodex – the basic contact information you need to literally get in touch with a lead or customer. At minimum, capture:

• First and last name
• Company name
• Job title or role
• Direct email and phone number
• Physical mailing address

Depending on your business, you may also want to log supplemental identity info like:

• Preferred name (ex: Christopher vs Chris)
• Alternative email or phone
• Company website
• Social media handles
• Photo
• Birthday

Identity data is the foundation that all other CRM data ties back to, so it needs to be as complete and accurate as possible. Some best practices:

• Make key fields like name, email, and phone required on your lead capture forms
• Use standardized picklists for fields like Title, State, and Country to keep data clean
• Enable form field validation for proper formatting of email, phone, etc.
• Append social media data upon import using a tool like FullContact
• Regularly dedupe records and update stale data using a data enrichment service

2. Firmographic & Demographic Data

If identity data answers the "who", firmographic and demographic data answers the "what". Firmographic data provides attributes about the person‘s company and role, such as:

• Company industry
• Company size (employees and/or revenue)
• Geographic markets served
• Type of business (B2B, B2C, nonprofit, etc)
• Technologies used

Demographic data includes personal attributes about the individual, like:

• Job function (sales, marketing, IT, HR, etc)
• Seniority level (manager, director, VP, C-suite)
• Years of experience
• Education level
• Age range
• Household income range

Layering this data onto your CRM records allows you to develop rich profiles of your ideal buyers and create hyper-targeted segments. You can infer a contact‘s likely pain points, goals, and buying behaviors based on trends and patterns seen across similar individuals.

Some ways to capture this intel:

• Progressive profiling that asks for different info at each conversion point
• Append data using form enrichment tools like Clearbit
• Regularly refresh data using third-party sources like ZoomInfo or D&B
• Extrapolate based on job titles using ideal customer profiles (ICPs)
• Train BDRs to ask probing discovery questions during calls

3. Behavioral & Transactional Data

Behavioral data is the digital equivalent of body language. It provides clues into a prospect‘s interests and intent based on actions they‘ve taken. Some examples:

• Pages viewed on your website
• Emails opened, clicked or replied to
• Content downloaded
• Webinars attended
• Videos watched
• Demos requested

Transactional data tracks the quantitative interactions someone has with your product or service:

• Purchases made (amount, frequency)
• Contracts signed
• Invoices paid
• Onboarding steps completed
• Features used
• Support tickets submitted

This type of data is incredibly valuable because it‘s:

1. Timely – Provides real-time insight into buyer readiness
2. Objective – Based on actual behavior vs stated interest
3. Relationship-building – Informs how to personalize outreach at scale

Best practices for behavioral and transactional data management:

• Invest in marketing automation to track digital behavior
• Integrate your CRM with back-office tools like ERP and billing
• Use custom objects to log product usage data
• Create reports & dashboards to visualize trends
• Build lead scoring models that combine fit and intent

4. Qualitative Data

If behavioral data is the "what", qualitative data is the "why" behind it. It documents the subjective, unstructured information that gives color to your interactions:

• Interests, pain points, goals
• Competitive landscape
• Buying process and criteria
• Objections and concerns
• Budgets and timelines
• Relationships and influence
• Post-sale feedback

Qualitative data typically lives in notes captured from sales conversations, but can also come from:

• Web form submissions
• Chatbot transcripts
• Customer surveys
• Net promoter scores
• References and case studies

While harder to organize than quantitative fields, this information provides crucial context that helps sales and customer success teams empathize with buyers and add value in the sales process.

Tips for tracking qualitative data in your CRM:

• Create custom text fields to capture key intel consistently
• Use tasks or notes to document ad-hoc conversations
• Associate notes to contact, company, and deal records
• Analyze notes with text mining tools to spot trends
• Share Voice of Customer insights across the org

Structuring Your Data for Actionability

Collecting the right data is one piece of the puzzle. Organizing it in a CRM so it‘s easily accessible and actionable is another challenge altogether. No matter what CRM you use, apply these architectural principles:

1. Standardize field values

Avoid freeform text fields in favor of picklists with predefined options. This keeps data clean for building segmented lists and reports.

In HubSpot, some key properties to standardize:

Object	Properties
Contact	Lifecycle Stage, Lead Status, Industry, Job Function
Company	Industry, Type, Revenue, Employee Count
Deal	Deal Stage, Deal Type, Lead Source

2. Create dependencies between fields

Set field dependencies so that field B only appears when Field A has a specific value. This keeps your team focused on the most relevant info.

For example, if Lead Source is "Referral", show a required Referrer field. Or if Industry is "Healthcare", show a Care Setting field.

3. Use naming conventions

Establish consistent naming conventions for your custom properties, especially if you have a large admin team. Some common ones:

• Prefix custom fields with your company name (ex: ABC Company Industry)
• Denote field type in name (ex: Contract Value – Currency)
• Camel case or underscores for multi-word names

4. Build custom objects for non-standard data

Most CRMs let you create custom objects to track and associate data specific to your organization. Use them to log info like:

• Products purchased
• Events attended
• Subscriptions
• Equipment
• Locations

In HubSpot, navigate to Settings > Objects > Create Custom Object and define the properties you want to track. Then use workflows or integrations to populate them.

5. Connect CRM and sales engagement data

The most innovative sales organizations are combining prospect engagement data from tools like email, phone, and social with CRM data for a unified view of pipeline and deals. Some examples:

• Number of emails exchanged with a contact
• Number of sales touchpoints per opp
• Calls made vs meetings booked
• Content shared with a prospect

Integrating sales engagement metrics with CRM data provides a leading indicator into deal health and momentum. It helps managers coach their teams and forecast more accurately.

Avoiding CRM Data Debt

Implementing CRM data best practices from day one is crucial. But equally important is the ongoing management needed to maintain data quality over time and prevent data debt.

Much like financial debt, data debt accumulates gradually as small data quality issues compound into bigger problems. And the longer bad data sits in your system, the harder it becomes to correct.

Consider these stats on how quickly data degrades:

Timeframe	Data Decay
Every year	25-30% of data becomes inaccurate
Every month	2% of records contain a spelling mistake
Every week	4% of records are flagged as "do not contact"

Sources: MarketingSherpa, Biznology

Without regular data maintenance, your once pristine CRM can turn into a morass of stale, incomplete, and inaccurate records that your reps don‘t trust.

To keep your data squeaky clean:

• Automate data capture with web forms and integrations
• Append and enrich data from third-party sources
• Run regular dedupe and cleanup jobs
• Create data quality dashboards to monitor completeness and accuracy
• Document data entry and management processes
• Make data health a performance metric for sales
• Appoint a CRM admin to own data governance

By proactively managing your CRM data, you can avoid the compounding costs of bad data and keep your system healthy, relevant, and trustworthy.

Transforming Data into Dollars

Your CRM data is only as valuable as what you do with it. Capturing high-quality data across the four key areas – identity, attributes, behaviors, and feedback – gives you a head start. But to truly gain a competitive advantage, you need to activate that data in your sales and marketing programs.

Think of your CRM as the "brain" of your revenue engine, and integrations as the "nervous system" that sends signals to the rest of your tech stack – marketing automation, sales engagement, digital advertising, analytics, and more.

When all your systems are seamlessly sharing data, some pretty magical things happen:

• Lead prioritization – Surface a sales-ready lead in your CRM to a rep the moment they visit your pricing page
• 1:1 personalization – Tailor an email‘s content and CTAs based on web pages they‘ve viewed
• Account-based advertising – Dynamically sync target accounts to ad platforms
• Next-best-action – Trigger a rep to call an account that just watched a product video
• Automated nurturing – Follow up with a "Sorry we missed you" email if a demo no-show occurs
• Predictive forecasting – Proactively alert reps and managers about deals at risk of stalling or churning

The more extensively you enrich and activate your CRM data, the more you can harness its full revenue-generating potential. According to HubSpot Research, data-driven companies are:

• 6x more likely to achieve competitive differentiation and increase profitability
• 19x more likely to generate above-average profits
• 58% more likely to beat revenue goals than non-data-driven companies

By mastering the art and science of CRM data management, you can improve sales productivity, marketing ROI and ultimately, topline growth. So don‘t let bad data sink your bottom line. Make data quality a strategic priority and watch your revenue and customer satisfaction soar.