Dreamdata

What is Dreamdata?

Dreamdata is a B2B revenue attribution platform designed to help companies analyze, understand, and optimize their customer journeys. Unlike traditional web analytics tools that focus mainly on visitor behavior, Dreamdata connects marketing and sales data across multiple platforms to show how different touchpoints contribute to revenue.

It is purpose-built for B2B companies, where buying cycles are often long, complex, and involve multiple stakeholders. Dreamdata specializes in stitching together scattered interactions (ads, emails, website visits, CRM activities) to build full-funnel, multi-touch attribution models — helping businesses understand which marketing activities actually drive revenue.

Key Features

• Revenue attribution: Connects marketing efforts to closed deals to see which activities generate real value.

• Multi-touch tracking: Captures all touches across the customer journey, from first ad click to signed contract.

• Data unification: Integrates with CRM systems (like HubSpot, Salesforce), ad platforms (Google Ads, LinkedIn), web analytics, and more.

• Customizable attribution models: Choose between first-touch, last-touch, linear, or custom attribution strategies.

• Pipeline analytics: See what is generating qualified leads, opportunities, and pipeline value — not just traffic.

• Account-based analytics: Understand how entire accounts (not just individual users) interact across the funnel.

• Self-service dashboards: Flexible, no-code reports that marketing and sales teams can use independently.

• Revenue analytics: Visualize sales cycles, deal sizes, and customer acquisition costs in relation to marketing efforts.

Technical Foundation

• Backend: Built on modern cloud data infrastructure, heavily uses ETL (Extract, Transform, Load) processes to combine and clean data.

• Hosting: Secure, scalable cloud hosting (typically AWS or similar) with compliance to GDPR and other data privacy standards.

• Integrations: Native connectors for popular tools like HubSpot, Salesforce, Marketo, Google Ads, Facebook Ads, LinkedIn Ads, Google Analytics, Snowflake, and more.

Use Cases

• Marketing teams: Who need to justify spend by showing revenue impact.

• Sales teams: To understand which marketing channels deliver sales-ready leads.

• Growth teams: To optimize funnels based on real revenue data rather than surface-level metrics.

• C-level executives: To make budget decisions based on objective, revenue-linked insights rather than gut feeling.

Pricing

Dreamdata uses a custom pricing model based on:

• Company size

• Number of CRM records (leads, contacts, accounts)

• Volume of tracked activity

• Features needed (e.g., basic attribution vs. full pipeline analytics)

Typically, pricing starts at mid to high four-figure amounts annually for small teams and scales up significantly for enterprises.

They often offer:

• A free trial or demo

• Pilot programs for evaluation before full commitment

Pros and Cons

Pros:

• B2B-focused (accounts for long, complex sales cycles)

• Deep integrations with CRM and marketing tools

• True revenue attribution, not just lead attribution

• Transparent, customizable reporting

• Very strong multi-touch modeling

Cons:

• Pricing can be high for smaller businesses

• Requires reasonably clean CRM and marketing data for best results

• Initial setup can be complex if data is siloed or messy

• Focuses heavily on B2B; not ideal for pure B2C companies

How It Differs From Alternatives

• Versus Google Analytics: Dreamdata connects marketing data to revenue, while Google Analytics mainly tracks website behavior without revenue linkage.

• Versus HubSpot: While HubSpot has basic attribution reports, Dreamdata offers far deeper and more customizable attribution models, especially for multi-touch.

• Versus Bizible (Adobe): Dreamdata is often simpler to implement and more flexible for companies not already locked into Adobe ecosystems.

• Versus Windsor.ai, HockeyStack: Dreamdata is very B2B-specific and offers strong account-based reporting, where others are sometimes more generalized.

Typical Metrics You Can Track

• Revenue per marketing channel

• Average deal size per channel or campaign

• Customer acquisition cost (CAC) by channel

• Lead-to-customer conversion rates

• Sales cycle length by acquisition source

• Number of touches to close a deal

• Pipeline contribution by content piece (e.g., blog posts, webinars)

Best Practices for Using Dreamdata

• Invest early in CRM hygiene: Accurate, consistent CRM data makes Dreamdata much more powerful.

• Map multi-channel journeys: Understand that most B2B buyers will interact across several channels over months.

• Start simple with attribution models and increase complexity over time.

• Combine Dreamdata’s insights with regular marketing performance reviews to adjust budgets and tactics.

• Clearly define attribution rules across teams to ensure consistent understanding.