What Is Data as a Service (DaaS)? A Guide for Revenue Teams

Bad data costs companies up to 25% of their potential revenue. As data volume and complexity increase, revenue teams need clean, real-time intelligence to drive decisions.

Data-as-a-Service (DaaS) delivers enriched, AI-ready data that provides complete customer and prospect views. Multi-vendor enrichment, real-time orchestration, and AI-powered insights turn data quality from a liability into a competitive advantage.

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 across platforms and applications. It eliminates on-site infrastructure needs and delivers AI-ready data directly into GTM workflows through scalable, subscription-based access.

Businesses access DaaS through multiple delivery methods:

• APIs: Real-time data retrieval integrated directly into workflows

• Cloud data platforms: Direct connections to Snowflake, Google BigQuery, and AWS

• Flat files: Batch delivery for custom data warehouse needs

Key Components of a DaaS Solution

A comprehensive DaaS offering includes six essential components:

• Cloud delivery: Data hosted and delivered via cloud infrastructure, eliminating on-premise storage

• On-demand access: Real-time data availability when teams need it

• Subscription model: Flexible pricing that scales with usage

• Data sourcing: Aggregation from multiple verified sources for comprehensive coverage

• Data cleansing: Automated processes that remove duplicates and correct inaccuracies

• Integration capabilities: APIs, webhooks, and connectors for direct CRM and marketing automation flow

DaaS platforms combine first-party data with third-party insights to build a single source of truth for predictive modeling and go-to-market strategies. This eliminates blind spots from relying solely on CRM data, which is typically messy, incomplete, and outdated.

How Does Data as a Service Work?

A comprehensive DaaS solution includes two interconnected layers:

1. A data access layer: Delivers the data points from which teams can draw insights

2. 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 seven types of data:

1. Firmographics: Company name, website, revenue, employee size, location, and industry

2. Parent-child hierarchy: Relationships between companies, sites, global parents, domestic parents, subsidiaries, and franchise identifiers

3. Technographic data: Applications and software infrastructure like AWS, HubSpot, Salesforce, and ZoomInfo

4. Scoops: Actionable leads from surveys and research identifying projects and leadership moves for timely outreach

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

6. Contacts: Work email, direct dial phone numbers, and office addresses

7. Advanced insights: Detailed company information like marketing sophistication levels

Data Management Layer

The data management layer ensures the right data ends up in the right place through four core operations:

• Cleanse: Automates database health through record deduplication, data normalization, standardization, and customer segmentation

• Multi-vendor enrichment: Enriches databases with multiple data providers using flexible, rules-based logic that standardizes and segments to business requirements

• Route: Automatically routes data into CRMs based on designated fields, creating routing workflows that assign leads for fast follow-up

• APIs and webhooks: Integrates and updates B2B data directly in any system and workflow in real time at scale

DaaS solutions include specialized data services for custom requests, advanced analysis, and large-scale delivery needs:

• Data cubes: Continually refreshed firmographics and technographics delivered via Snowflake, Google BigQuery, or AWS. ZoomInfo Data Cubes support master data strategy and advanced modeling

• Custom enrichment services: Offline matching that resolves blanks left by real-time matching through periodic mass batches

• Modeling and scoring services: Lookalike regression and custom models that identify cross-sell, upsell, and net-new opportunities. Score any object based on any attribute, including behavior, intent, and ICP 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.

DaaS Delivery Methods

DaaS platforms deliver data through four channels to fit different workflow requirements:

• APIs and webhooks: Real-time integration into CRM and GTM tools with on-demand retrieval and automatic updates

• Flat files: Batch delivery for custom data warehouse needs or legacy systems requiring periodic bulk updates

• Cloud data platforms: Direct integration with Snowflake, Google BigQuery, and AWS for advanced analytics and machine learning

• Native integrations: Pre-built connectors for Salesforce, HubSpot, Outreach, and Salesloft

Benefits of Data as a Service for Revenue Teams

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.

Cost Efficiency and Scalability

GTM Intelligence platforms streamline operations by:

• Eliminating disparate data tools through centralized solutions

• Reducing infrastructure costs for storage and manual data management

• Operating on subscription-based pricing that scales with business needs

Automating data cleansing, enrichment, and activation saves operational costs while increasing pipeline velocity and sales efficiency.

DaaS provides the foundation for strategic decision-making through real-time dashboards with AI-powered insights and predictive modeling. Leadership makes faster, more informed decisions that boost forecasting accuracy and align GTM strategies with business objectives.

"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

Improved Data Quality and Accuracy

Multi-vendor enrichment provides a holistic view of ideal customers by combining internal CRM insights with external third-party data and intent signals that reveal buyer readiness. This enables ICP refinement and precise targeting based on real-time insights.

A comprehensive Go-to-Market Intelligence provider delivers three core advantages over single-source data providers:

• AI-powered cleansing: Automatically corrects inaccuracies in real time

• Multi-vendor enrichment: Ensures complete, consistent datasets by aggregating from trusted sources

• Real-time orchestration: Keeps data continuously updated without manual intervention

Faster Time-to-Insight

GTM Intelligence-powered DaaS delivers real-time, AI-ready data, enabling immediate response to market changes and buyer intent signals. Real-time orchestration accelerates lead prioritization based on dynamic intent and reduces sales cycle times.

DaaS ensures clean, well-structured data reaches teams when and where it matters through:

• Real-time enrichment pipelines: Automatically update CRM systems

• APIs and webhooks: Enable data flow across GTM tools

• One-click access: Deliver engagement-ready data without manual preparation

DaaS delivers additional strategic advantages for revenue teams:

• Personalized messaging: Granular customer insights enable personalized sales messaging that aligns with buyer needs at every journey stage, increasing engagement and conversion

• Hidden revenue opportunities: Predictive analytics surface undiscovered market trends while lookalike modeling identifies cross-sell and upsell opportunities that scale through AI-powered orchestration

• AI model optimization: High-quality, AI-ready data trains machine learning models for precise predictions and powers generative AI applications without inaccurate outputs

DaaS Use Cases for Go-to-Market Teams

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

Sourcing Accurate Account and Contact Data

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.

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

Building and Refining ICPs

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.

Multi-vendor enrichment combines thousands of data points from multiple trusted vendors to ensure completeness and enables granular segmentation by supplementing ZoomInfo's proprietary data with niche datasets.

Enriching Records for Targeted Outreach

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.

Real-time data orchestration automatically routes and integrates data across CRM, marketing automation, and sales engagement tools, and supports dynamic segmentation and intent-based outreach, ensuring AI-powered personalization at scale.

"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

DaaS vs. Data as a Product: What Revenue Teams Should Know

DaaS delivers continuous, subscription-based data streams while Data as a Product (DaaP) provides one-time or periodic dataset purchases. The key difference: DaaS provides real-time updates, while DaaP delivers static datasets.

DaaS connects once and delivers ongoing updates as data changes, making it ideal for sales prospecting, marketing automation, and revenue operations that require real-time intelligence. DaaP organizations purchase specific datasets for analysis, modeling, or research projects where the data remains static until repurchase.

For revenue teams running continuous outbound motions, DaaS eliminates the manual work of repeatedly purchasing and uploading data. For data science teams building predictive models on historical patterns, DaaP may provide the specific datasets needed without ongoing subscription costs.

Common DaaS Challenges and How to Overcome Them

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.

Data Security and Compliance

Ensuring data security requires protecting against breaches, unauthorized access, and compliance failures related to global privacy regulations.

Go-to-Market Intelligence platforms address these challenges through:

• Enterprise-grade encryption: Secure access controls that prevent unauthorized data access

• Continuous auditing: Regular security audits and compliance certifications

• Privacy-first frameworks: Built-in alignment with GDPR, CCPA, and other regulatory requirements

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

Data Quality and Governance

DaaS implementation faces three primary challenges:

• Data hygiene: Fragmented datasets, incomplete records, and outdated data that disrupt AI-powered workflows and predictive analytics

• Data governance: Complex requirements for data availability, usability, integrity, and stewardship to maintain compliance

• Data silos: Isolated datasets that create transparency gaps, operational inefficiencies, and incomplete customer views

Go-to-Market Intelligence platforms automate solutions through:

• Unified frameworks: Consistent data standards across all departments

• Automated validation: GTMI platforms eliminate manual errors

• Real-time orchestration: Data unified across all GTM systems with prebuilt connectors

• Single source of truth: Dynamic segmentation enables cross-departmental access for sales, marketing, and operations

What to Look for in a DaaS Provider

Choosing the right DaaS provider determines whether your data becomes a revenue driver or a cost center. Evaluate potential providers on these criteria:

Data Quality and Freshness

Data accuracy and currency separate premium providers from budget alternatives. Evaluate providers on four criteria:

• Verification methods: Multi-source verification delivers higher accuracy than single-source data

• Refresh frequency: Real-time updates outperform quarterly refreshes for fast-moving GTM teams

• Coverage depth: Comprehensive firmographics, technographics, and intent signals versus basic contact data

• Accuracy guarantees: Specific deliverability rates and accuracy metrics with SLA commitments

Continuous data refresh eliminates database decay and keeps CRMs current without manual intervention.

Integration Capabilities

Data that lives in isolation delivers no value. Evaluate how easily provider data flows into your existing tech stack:

• Native CRM integrations: Pre-built connectors for Salesforce, HubSpot, and platforms your team uses daily

• API flexibility: Programmatic data pulls for custom workflows and applications

• Marketing automation compatibility: Direct syncs with Marketo, Eloqua, and Pardot for campaign execution

• Sales engagement tool support: Enriched data pushed directly into Outreach and Salesloft

The best DaaS providers offer multiple integration paths: native connectors for common tools, robust APIs for custom builds, and webhook support for real-time flows.

This flexibility ensures data reaches the teams and systems that need it most.

Turn B2B Data into Pipeline with ZoomInfo DaaS

Data-as-a-Service from ZoomInfo, the leader in GTM Intelligence, transforms how businesses access, analyze, and activate data to fuel scalable growth and predictable revenue.

In 2026, success depends on how you enrich, orchestrate, and activate data. The right DaaS solution delivers:

• Real-time, AI-ready data that enables faster, smarter decisions

• Multi-vendor enrichment for complete, accurate customer profiles

• Automated data orchestration for end-to-end GTM execution

• 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 actionable insights that accelerate sales cycles, increase conversion rates, and surface hidden revenue opportunities.

Talk to a data specialist today and discover how ZoomInfo's GTM Intelligence solutions turn data complexity into competitive advantage through active orchestration and deployment.