Chapter 1: The Hidden Goldmine in
Go-to-Market Data
The Importance of GTM Data
GTM data encompasses all the contact, account, and engagement information used to identify, target, and convert customers. This data is as critical as financial records for sales and marketing teams to the CFO. Yet in M&A, GTM data is rarely evaluated with the same rigor.
When treated properly, this data is a goldmine that can:
- Expand market reach by identifying untapped opportunities.
- Optimize sales and marketing strategies through segmentation and targeting.
- Improve operational efficiency by reducing redundancies and aligning data across systems.
Ignoring GTM data during due diligence means leaving potential synergies on the table—or worse, inheriting a liability that undermines growth.
Chapter 2: The Key Components of GTM Data Evaluation
1. Size Matters
Why it Matters: A robust dataset enables scalability and supports marketing and sales campaigns that can drive growth.
What to Look For: Does the acquisition target have a large database? Does it cover a wide range of accounts, contacts, and leads? While a small TAM is acceptable in niche industries, most successful organizations leverage extensive datasets to fuel their GTM efforts.
Key Question: Does the target have the quantity of data needed to support aggressive GTM campaigns?
2. Overlap Analysis
Why it Matters: Overlap analysis ensures the acquisition brings new, incremental data rather than duplicates of your existing database.
What to Look For: Run a detailed comparison between the target’s CRM and your own. Identify net-new accounts, contacts, and leads that can enhance your customer base.
Key Question: How much of the target’s data is unique and valuable versus redundant or irrelevant?
3. Data Validity
Why it Matters: Invalid or outdated data wastes time, damages brand reputation, and reduces operational efficiency.
What to Look For: Validate critical fields such as email addresses, phone numbers, job titles, company names, and physical addresses. Tools for email verification, phone number accuracy, and company association validation can help.
Key Question: Is the data clean, accurate, and ready for activation?
4. Funnel Metrics and Data Tracking
Why it Matters: A well-tracked funnel provides insights into customer behavior, sales performance, and channel effectiveness, which are vital for valuation and integration planning.
What to Look For: Does the target track metrics such as:
Funnel conversion rates (e.g., MQL to SQL to Closed Won) Win/loss reasons
Channel performance (e.g., outbound calls, inbound leads, social media)
Key Question: Can you gain actionable insights from the target’s GTM data, or will you need to invest heavily in fixing it?
Chapter 3: Operational Challenges in Data Integration
Data Format and Migration
Why it Matters: Data migration can be costly and time-consuming, especially when the acquired data isn’t formatted for seamless integration.
What to Look For: Check the format of key attributes like company names, addresses, job titles, industries, and hierarchies. Misaligned formatting can create complications during migration, leading to lost data or reduced usability.
Key Question: Is the target’s data compatible with your systems, or will integration require significant reformatting?
2. Data Source Analysis
Why it Matters: The source of the data impacts its quality, accuracy, and relevance
What to Look For: Assess whether the target sources its data from reliable vendors (e.g., ZoomInfo, Dun & Bradstreet) or through first-party activities like trade shows and LinkedIn outreach. Also, evaluate the mix of purchased vs. organic data.
Key Question: Are the data sources trustworthy, and do they align with your standards?
3. Data Contract Liabilities
Why it Matters: Inheriting unfavorable contracts with data vendors can lead to unplanned expenses and limit flexibility
What to Look For: Review contracts with data providers. Are there auto-renew clauses? Are there penalties for termination? Can the vendor relationships be renegotiated or terminated post-acquisition?
Key Question: Are you inheriting valuable vendor relationships or costly liabilities?
4. Dead Data
Why it Matters: Outdated or inactive data inflates database size without adding value, creating inefficiencies and costs.
What to Look For: Analyze activity and engagement history. How recently has the data been used? What percentage of the database is stale?
Key Question: Is the data an active, valuable asset or an outdated liability?
Chapter 4: Data as an Asset or Liability
Data isn’t inherently valuable—it’s only an asset when it’s accurate, actionable, and aligned with your GTM strategy. Without proper due diligence, you risk inheriting data that undermines your operations, damages your brand, and diminishes the ROI of the acquisition. Conversely, identifying high-quality data can uncover hidden opportunities to grow and scale.
Conclusion: Benchmarking Data Health in M&A
Evaluating the health of GTM data should be a standard part of M&A due diligence. By doing so, acquirers can:
Ensure data quality and readiness for integration.
Identify growth opportunities from net-new data.
Avoid inheriting costly data liabilities.
With the right tools, expertise, and processes, you can unlock the hidden value of GTM data and maximize the return on your acquisition investment.
How We Can Help
Our team specializes in GTM data due diligence, offering services that include:
- Data validation and cleansing
- Overlap and gap analysis
- Funnel metric audits
- Data migration planning
- Vendor contract review
