What Really Drives the Cost of B2B Marketing Data (and Why Prices Vary So Much)

B2B marketing data — often referred to as sales intelligence, account intelligence, or go-to-market data — underpins how teams identify, prioritize, and engage target accounts.

If you’ve evaluated B2B marketing data providers, you’ve likely seen pricing that ranges from a few thousand dollars per year to well into six figures — all for products that appear, on the surface, to “do the same thing.”

They don’t.

B2B marketing data pricing varies so widely because vendors are not pricing the same inputs, the same outputs, or even the same underlying product. Understanding what actually drives cost (and value) is the difference between overpaying for unnecessary coverage and an underinvestment in data that ultimately constrains growth.

This article breaks down the core variables that influence pricing, so you can evaluate providers based on what you’re buying and the value it creates — not sticker shock.

Why Pricing in B2B Marketing Data Is So Hard to Compare

Unlike commodities, there is no standard unit of measurement for B2B marketing data.

Vendors may price or license by:

• Number of users (seats)
• Number of reports or downloads (consumption-based)
• Unlimited or market-level access (enterprise)

On top of that, most platforms bundle:

• Data
• Software
• Analytics
• Support
• Integrations

…into a single annual contract.

That makes direct price comparisons misleading. A $10,000 solution and a $75,000 solution might look similar on the surface while delivering very different data, functionality, and value underneath. To compare knowledgeably, you need to understand the variables behind the price.

The Core Variables That Drive Cost

1. Market Coverage

One of the biggest pricing drivers is the size and scope of the market covered. Broadly, providers fall into two segments: horizontal providers and vertical providers. Horizontal providers are generalists, offering relatively similar data structures across many markets. Vertical providers are specialists, offering datasets that are unique to the vertical they cover. The table below compares several dimensions on the two provider segments.

Why this affects cost:

• Broad coverage benefits from scale and standardization so you can “know more entities”
• Narrow coverage concentrates cost per entity so you can “know more about each entity”

Buyer consideration:
If you sell into a narrow or niche market, paying for broad coverage often means paying for a large percentage of data you will never use. Vertical coverage can appear more expensive on a per-account basis but cheaper relative to the data’s relevance and downstream impact.

2. Depth of Data Per Account:

Not all “company records” are created equal.

Basic records usually include:

• Company name
• Industry code
• Employee count
• Revenue range
• Basic contacts

Deeper records may include:

• Financial statements
• Technology stack
• Organizational structure
• Performance metrics
• Top opportunities
• Strategic initiatives
• Vendor relationships
• Segmentations
• Purchasing intent signals

Why this affects cost:

• Deeper data requires more source inputs
• Greater normalization across entities
• Ongoing validation
• More frequent review cycles

Buyer consideration:
Shallow data is cheaper but pushes more research onto your team. Deeper data costs more but reduces downstream labor, manual validation, and ultimately guesswork. Depth and quality of data is a major factor in value assessment. There is a meaningful difference between just knowing a company’s size versus understanding how it operates, what technology it uses, and where its needs reside. It can be the difference in engaging as a vendor or engaging as an advisor.

3. Update Frequency & Data Freshness

Data does not decay evenly across industries.

In many B2B sectors — especially regulated or technology-driven ones — meaningful changes occur frequently:

• Leadership changes
• Vendor/product changes
• Mergers and acquisitions
• Financial performance shifts
• Product launches
• Strategic pivots

Pricing impact:

• Annual refresh = lowest cost
• Quarterly refresh = moderate cost
• Monthly refresh = higher cost
• Continuous monitoring = highest cost

Buyer consideration:
Lower-priced data often trades ongoing freshness for lower upfront cost. Higher-priced data reflects continuous monitoring and validation with the platform. The key consideration for the buyer is the pace of change in its target market(s).

4. How the Data Is Collected & Delivered

Data collection methods have a direct relationship to cost, scalability, and coverage.

Common approaches include:

• Automated web or digital data extraction
• Third-party data aggregation
• Self-reported or survey-based inputs
• Proprietary research and validation

How this affects cost:

• Automated collection enables continuous expansion of coverage and more frequent updates, but requires significant investment in data engineering, infrastructure, and quality assurance systems
• Human research and review might improve confidence in complex or ambiguous attributes but do not scale efficiently as a primary collection method
• Self-reported data can add detail but often suffers from uneven participation, inconsistent definitions, and delayed updates

The data delivery model also influences costs or pricing and often affects other pricing variables. The two extremes in delivery models are Platform-Based Delivery and File-Based Delivery. The table below broadly compares the two models.

Buyer consideration:
The way data is collected shapes its long-term value. Collection methods that depend on participation, external partners, or manual effort limit coverage expansion and update frequency. More scalable systems are better suited to keeping pace with changing markets and expanding data depth. Buyers should focus on how a provider’s methodology supports continued relevance – as well as current accuracy. Buyers should pointedly ask providers exactly how they procure their data and should be particularly wary when the provider is unwilling to detail their methodology.

Platform-based delivery is the norm for higher-end SaaS data providers focused on account-based marketing. File-based delivery is more appropriate for non-recurring projects. When delivered in this form, the buyer should question how the provider sourced the data to ensure their ownership and usage rights of the data.

Pricing Models You’ll See in the Market

B2B Marketing Providers typically offer three variation of pricing models based on individual seats, consumption or enterprise access.

Seat-Based Pricing

You pay based on the number of users.

Pros:

• Predictable
• Easy to budget
• Fit with well-defined roles & tasks

Cons:

• Penalizes collaboration
• Weak alignment to data value

Best for: Large sales teams with repetitive, defined tasks & consistent usage patterns.

Credit or Consumption-Based Pricing

You pay based on:

• Exports
• Contacts
• Searches
• Actions

Pros:

• Aligns cost to usage
• Lower entry price

Cons:

• Difficult to forecast
• Discourages internal adoption and experimentation

Best for: Teams with clearly defined, limited use cases.

Account-Based or Enterprise Pricing

You pay for unlimited access to a defined set of companies or institutions.

Pros:

• Cost aligns to TAM
• Encourages broad internal usage
• Incents application to multiple use cases

Cons:

• Less flexible outside the covered market

Best for: Account-based selling and an evolving vertical go-to-market strategy.

Buyer consideration:
Pricing models reflect assumptions about how data will be used. Models optimized for controlled usage can hinder your go-to-market (“GTM”) model evolution as your needs change. Buyers should choose structures that support adaptation, not just initial efficiency.

Hidden cost to consider:
Time spent filtering irrelevant accounts, validating accuracy, and supplementing missing industry context.

When Each Model Makes Financial Sense

Vertical data makes sense when:

• You sell into one complex industry
• Account insight matters more than lead count
• Precision improves win rates

Horizontal data makes sense when:

• You sell into many industries
• You prioritize lead volume across those verticals
• Industry nuance matters less

The Questions Buyers Should Ask to Understand True Cost (and Value)

Instead of asking, “How much does it cost?”, ask:

1. What proportion of this data aligns with our ICP (applicability)?
2. How often is it updated — and by what mechanisms (i.e. data sourcing)?
3. What research or validation work will our team still need to do?
4. What usage limits could increase costs mid-year?
5. How much of the data is unique versus widely available elsewhere?
6. What data categories are covered/offered (data depth)?
7. Are we buying raw data, or interpreted insights (analytics)?
8. What GTM use cases are applicable to the data analytics (ex. ABM)?

These questions reveal cost structure and relative value, not just price.

Final Takeaway

Price alone tells you very little about B2B marketing data.

Cost is driven by:

• Market focus
• Data depth
• Freshness
• Collection methodology
• Pricing model

The “right” price is the one that aligns with how you sell, who you sell to, and how much insight your team actually needs.

Understanding these variables allows you to evaluate providers rationally — and avoid paying for either excess coverage or insufficient intelligence. With this approach, your firm can avoid wasting money and just as importantly – wasting precious time in accelerating your go-to-market.

About the Author

Steve Cotton is CEO and founder of FI Navigator. His expertise spans financial institution analytics, advisory services, and B2Bank go-to-market (GTM) strategy, providing fintech vendors, advisors, and financial institutions data-driven insights to navigate the complexity of the U.S. banking market.