As the velocity, volume, and variety of data increases, many businesses struggle with unreliable data that doesn’t offer valuable insights, leading to significant losses. In fact, one key study found that bad data costs companies up to 25% of their potential revenue.

Data-as-a-Service (DaaS) can make a clear difference. DaaS solutions deliver enriched, real-time, AI-ready data that illuminates a full view of customers and prospects, far beyond what first-party, notoriously dirty customer relationship management (CRM) systems can provide.

By leveraging multi-vendor enrichment, real-time orchestration, and AI-powered insights, DaaS ensures that data quality becomes an advantage — not a liability.

What is Data as a Service (DaaS)?

Data-as-a-Service (DaaS) is a cloud-based system that provides on-demand access to critical business data anytime, anywhere, across a wide range of platforms and applications.

Unlike traditional data management systems, DaaS eliminates the need for complex on-site infrastructure, offering scalable, flexible, and cost-efficient solutions that deliver AI-ready data directly into GTM workflows.

Users can access DaaS via APIs, major cloud data platforms, or even flat files, giving businesses the flexibility needed to customize and deploy GTM data how, when and where their teams need it.

Key components of a comprehensive DaaS offering include:

With reliable DaaS platforms, businesses can combine first-party data with third-party insights, building a single source of truth that powers predictive modeling and hyper-personalized go-to-market strategies.

Leveraging DaaS to augment first-party data eliminates costly blind spots and missed opportunities that are common for companies relying solely on customer relationship management (CRM) data, which is typically messy, incomplete, and outdated.

How DaaS Helps Companies Leverage GTM Intelligence

The emerging category of Go-to-Market Intelligence represents the next evolution of B2B go-to-market data. Rather than relatively static lists and profiles of companies and contacts, Go-to-Market Intelligence provides GTM teams a dynamic, constantly updated source of comprehensive data, high-value buying signals, and AI-derived insights.

GTM Intelligence is primed for AI-powered systems, which require data that is not only accurate, but also real-time and engagement-ready. Because of the speed and scale of AI-based decision-making and analysis, stagnant, outdated, or incomplete data can send sales and marketing motions off course much faster than human systems can keep up, making it difficult and costly to refocus.

When delivered via DaaS systems, GTM Intelligence can be combined with first-party CRM data to help GTM create highly advanced applications that drive increased value all across the GTM operation — sales, marketing, operations, and beyond.

“With go-to-market intelligence, we’ve achieved a significant boost in marketing campaign performance – the kind of results you only get by leveraging real-time insights to understand and connect with your audience.”

Tommie O’Brien, Chief Sales Officer, Semrush

Use Cases for GTM Intelligence Delivered via DaaS:

1. AI-Powered Data Cleansing:

Removes duplicates and corrects inaccuracies in real time.
Automates data normalization for semantic consistency across all GTM systems.
AI-powered automation cuts pipeline downtime by up to 40%

2. Multi-Vendor Enrichment:

Combines thousands of data points from multiple trusted vendors to ensure completeness.
Enables granular segmentation by supplementing ZoomInfo’s proprietary data with niche datasets.

3. Real-Time Data Orchestration:

Automatically routes and integrates data across CRM, marketing automation, and sales engagement tools.
Supports dynamic segmentation and intent-based outreach, ensuring AI-powered personalization at scale.

What Types of Data are Typically Offered Through Data-as-a-Service Platforms?

A comprehensive DaaS solution includes two interconnected layers:

A data access layer: Delivers the data points from which teams can draw insights
A data management layer: Provides the maintenance and enhancement services needed to make data work across a company.

Data Access Layer

The data access layer draws on several types of data, including:

Firmographics: Fundamental attributes used to define a business, similar to demographics for individuals. These may include the company name, website, revenue, employee size, location, and industry.

Parent-child hierarchy: The relationship between companies, sites, and structures. Examples include site locations, global parents, domestic parents, subsidiaries, franchise identifiers, and brands within a company.

Technographic data: The applications and software infrastructure used by a business, such as AWS, HubSpot, Salesforce, and ZoomInfo.

Intent data: Behavioral information about a company, such as content consumption, that provides insights into interests and potential buying signals.

Scoops: Actionable leads that are sourced through surveys and ZoomInfo’s in-house research team. Scoops identify projects and leadership moves to share with users for timely outreach.

Location: Detailed address information, including satellite offices, temporary locations, and more.

Contacts: Professional contact data, including work email, direct dial phone number, and office address.

Advanced insights: Additional information about a business that provides a more detailed picture of a company, such as its level of marketing sophistication.

Data Management Layer

The data management layer ensures the right data ends up in the right place. It requires a series of complex operations, including:

Cleanse: A systematic way to automate database health, including processes like record deduplication, data normalization, standardization, and customer segmentation.

Multi-vendor enrichment: A system with flexible, rules-based logic that enriches a database with multiple data providers and ensures that data is standardized and segmented to unique business requirements.

Route: Automatically route any type of data into a CRM based on any designated field or related object field. Creates simple or sophisticated routing workflows to quickly and accurately assign leads for fast follow-up.

APIs and webhooks: A comprehensive suite of search, enrich, and subscription APIs that seamlessly integrate and update B2B data and intelligence directly in any system and workflow, in real time, at scale.

A DaaS solution also includes data services for teams that have custom requests, advanced analysis, and larger-scale data delivery needs.

Data cube: An entire database of continually refreshed firmographics and technographics, delivered as a flat file or via services such as Snowflake, Google BigQuery, and AWS. ZoomInfo Data Cubes are built to support your master data strategy or run advanced analysis and modeling.

Custom enrichment services: Offline matching resolves any blanks left by real-time matching. Uses the same core technology as real-time matching, but it happens periodically in mass batches rather than instantly.

Modeling & scoring services: Lookalike regression and custom models are used to identify net-new, cross-sell, or upsell opportunities for product lines, divisions, and go-to-market teams.

Understand your ideal customer profile (ICP) better by scoring any object based on any attribute. Leverage multidimensional scoring along with scoring based on behavior, intent, and fit.

Data can get pretty granular depending on your goals. Only the best DaaS platforms are equipped to provide data like advanced insights or intent data.

Capital One was able to use ZoomInfo’s data services to modernize its GTM strategy, ditching spreadsheets and manual processes and creating a more productive self-service data workflow for all its sales reps.

“My job is to bring the information to our sales teams as easily as possible. Now, instead of 100 different sales teams coming to me with requests, we put the data in one place. We give them a report, and they can get it themselves — it becomes more of that self-service model.”

Andy Ruffles, director of sales operations and strategy at Capital One Commercial Banking.

How DaaS Solves Common GTM Challenges

While DaaS solutions provide critical advantages for modern businesses, successfully implementing DaaS requires overcoming several key challenges. The most successful DaaS strategies ensure AI-readiness, real-time data accuracy, and system-wide orchestration to support go-to-market GTM operations.

Additional data challenges include:

1. Unreliable and Inconsistent Data

One of the most significant challenges with DaaS implementation is data hygiene. GTM, operations, and master data management teams frequently struggle with:

Fragmented datasets from disparate sources.
Incomplete records that prevent accurate segmentation.
Outdated data that disrupts AI-powered workflows.

These issues directly impact strategic planning, tactical execution, and revenue outcomes. Without AI-ready data, even the most advanced predictive analytics fall short.

That’s why a comprehensive Go-to-Market Intelligence provider is vastly superior to single-source or low-cost B2B data providers:

AI-powered data cleansing automatically corrects inaccuracies in real time.
Multi-vendor enrichment ensures complete, consistent datasets by aggregating information from trusted sources.
Real-time orchestration keeps data continuously updated, reducing reliance on manual interventions.

2. Data Security: Safeguarding Revenue-Critical Data

As data becomes the lifeblood of revenue operations, ensuring its security is essential. The challenge lies in protecting sensitive data from:

Breaches and leaks.
Unauthorized access.
Compliance failures related to global data privacy regulations.

How Go-to-Market Intelligence Improves Data Security

Enterprise-grade encryption and secure access controls.
Regular security audits and compliance certifications.
Privacy-first frameworks that align with regulatory requirements, including GDPR and CCPA.

Result: Revenue teams can access real-time, engagement-ready data without compromising security or compliance standards.

3. Data Governance: Sustaining Data Integrity Across the Business

Data governance remains a complex challenge in DaaS adoption. Ensuring data availability, usability, and integrity requires:

Clear policies on data access and sharing.
Reliable data stewardship to oversee compliance.
High-quality data pipelines for uninterrupted GTM execution.

How Go-to-Market Intelligence Automates Data Governance

Unified data frameworks ensure consistent data standards across all departments.
Automated data validation within GTMI platforms eliminates manual errors.
Comprehensive data governance strategies enable scalability without sacrificing data integrity.

4. Data Silos: Breaking Down Barriers for Unified GTM Execution

Data silos—isolated datasets confined to specific departments—are a major obstacle in scaling GTM operations. Siloed data leads to:

Lack of transparency between sales, marketing, and RevOps.
Operational inefficiencies due to redundant processes.
Missed opportunities from incomplete customer views.

How Go-to-Market Intelligence Breaks Down Data Silos:

Real-time data orchestration unifies data across all GTM systems.
Prebuilt connectors and low-code integration solutions eliminate integration complexity.
Dynamic segmentation and cross-departmental access ensure sales, marketing, and operations teams operate from a single source of truth.

Key Benefits of Data-as-a-Service (DaaS)

Data-as-a-Service (DaaS) from a GTM Intelligence (GTMI) provider goes beyond simple data delivery. It transforms how businesses access, analyze, and activate data to accelerate revenue growth and streamline go-to-market (GTM) strategies.

1. Speed: Real-Time Insights for Rapid GTM Execution

GTM Intelligence-powered DaaS delivers real-time, AI-ready data, enabling businesses to react immediately to market changes and buyer intent signals. This real-time orchestration ensures:

Faster lead prioritization based on dynamic intent data.
Reduced sales cycle times, allowing teams to seize opportunities as they arise.

Businesses using GTMI solutions such as ZoomInfo experience 31% more pipeline generation and 15% faster deal cycles due to enhanced data responsiveness.

2. Hyper-Personalized Sales Messaging

Granular customer insights provided by DaaS empower sales teams to craft highly personalized sales messaging that resonates on an individual level. Through:

AI-powered segmentation based on firmographics, technographics, and behavioral data.
Dynamic personalization driven by real-time buyer intent signals.

Sales teams see higher engagement rates and increased conversion opportunities by aligning outreach with buyer needs at every stage of the journey.

3. Accelerated Revenue Growth

DaaS integrated with GTMI identifies hidden revenue opportunities by surfacing:

Undiscovered market trends through predictive analytics.
Cross-sell and upsell opportunities via lookalike modeling and behavioral scoring.

AI-powered orchestration ensures that sales and marketing teams can activate these insights at scale, driving sustained revenue growth.

4. Deeper Understanding of Your Ideal Customer Profile (ICP)

Multi-vendor enrichment provides a holistic, data-backed view of the ideal customer. By combining:

Internal CRM insights with external third-party data.
Advanced intent signals that reveal buyer readiness and preferences.

Businesses can refine their ICP and adjust GTM strategies based on real-time insights, ensuring precise targeting and higher win rates.

5. Cost-Effective Operations

GTM Intelligence platforms streamline operations by:

Eliminating the need for disparate data tools through a centralized solution.
Reducing infrastructure costs associated with storage and manual data management.

By automating data cleansing, enrichment, and activation, businesses save operational costs while increasing pipeline velocity and sales efficiency.

6. Data-Driven Decision Making

Accurate and timely data from DaaS forms the foundation for strategic decision-making. With:

Real-time dashboards offering AI-powered insights.
Predictive modeling that guides GTM investments.

Leadership can make faster, more informed decisions, boosting forecasting accuracy and aligning GTM strategies with business objectives.

7. Enabling AI, Machine Learning, and Predictive Modeling

AI-powered GTMI platforms thrive on high-quality, AI-ready data supplied by DaaS. This data is essential for:

Training machine learning models that deliver precise sales predictions.
Powering generative AI applications, where clean, structured data prevents AI models from producing inaccurate outputs (“hallucinations”).

McKinsey research shows that companies integrating AI across GTM processes see up to a 20% boost in sales productivity due to improved data-driven decision-making.

8. High-Quality Data When and Where You Need It

DaaS ensures that businesses receive clean, well-structured data—when and where it matters most. By leveraging:

Real-time enrichment pipelines that automatically update CRM systems.
APIs and webhooks that enable seamless data flow across GTM tools.

Revenue teams can access engagement-ready data in a single click, eliminating the time-consuming task of manual data preparation and cleaning.

How is DaaS Used? 3 Example Use Cases

Companies use DaaS in a variety of ways to drive go-to-market success:

1. Using DaaS to source accurate data on small businesses

For businesses that rely on physical address information — like shipping or freight carriers — having accurate location data is mission-critical, yet quite challenging at scale. The task is even more difficult if your customer profile includes small businesses.

With DaaS, teams can leverage third-party data alongside their own internal customer records to accurately cover even the most difficult addresses, like warehouses, small business storefronts, branch offices, and satellite buildings.

2. Using DaaS to profile the ideal customer for a niche market

If a product serves a niche market, prioritizing new customer segments can be challenging. Sometimes a company’s best accounts are not easily defined by traditional firmographics, like employee size or annual revenue.

Teams can leverage DaaS to pair nuanced company and contact attributes (such as decision-making authority, industry classification, and online behavior) with internal customer data (like time-to-close, deal size, and app download history) to uncover new industry segments with strong candidates for their solution.

3. Using DaaS to understand granular details about your target accounts

Every revenue team wants to know more about its target audience in order to segment and prioritize accounts. Segmenting target account lists by industry is a common practice, but sometimes a default industry classification, such as “technology” or “manufacturing,” can be too broad.

With DaaS, companies can select a handful of ideal accounts and plot their relevant terms or keywords onto a company semantics graph. This reveals related companies in new or adjacent industry segments that are potentially well-suited for what’s being offered.

Transform Data Complexity into Predictable Revenue

Data-as-a-Service from ZoomInfo, the leader in GTM Intelligence, unlocks the true potential of modern go-to-market strategies. In an era where data drives every sales and marketing decision, simply having access to data isn’t enough. Success depends on how you enrich, orchestrate, and activate that data to fuel scalable growth and predictable revenue.

With the right DaaS solution, businesses can:

Access real-time, AI-ready data that enables faster, smarter decisions.
Leverage multi-vendor enrichment to ensure complete, accurate customer profiles.
Automate data orchestration for seamless, end-to-end GTM execution.
Empower revenue teams with engagement-ready insights at every stage of the buyer’s journey.

ZoomInfo’s GTM Intelligence Platform transforms fragmented data into a single source of truth, delivering the actionable insights that accelerate sales cycles, increase conversion rates, and unlock hidden revenue opportunities.

Talk to a data specialist today and discover how ZoomInfo’s GTM Intelligence solutions turn data complexity into competitive advantage — because data alone isn’t enough. It’s how you activate it that drives success.