CoSupport AI
What is Dreamdata?
Dreamdata provides a comprehensive B2B go-to-market data platform designed to connect marketing activities directly to revenue outcomes. It automatically gathers and structures data across various touchpoints, offering businesses a unified view of their customer journeys. This allows for a clearer understanding of how different channels, campaigns, and content contribute to pipeline generation and overall revenue.
The platform enables detailed performance analysis through data-driven attribution models, helping marketing teams identify the true return on investment (ROI) for their initiatives. By tracking interactions and utilizing intent signals from multiple sources, including first-party tracking and integrations like LinkedIn ads and G2, Dreamdata helps prioritize sales and account-based marketing efforts towards high-potential accounts. It also facilitates the creation and activation of custom audiences by syncing data back to advertising platforms.
Features
- Customer Journey Mapping: Provides interactive timelines showing every touchpoint for each account.
- Performance Attribution: Utilizes data-driven attribution models to measure the revenue impact of channels, campaigns, and content.
- Revenue Analytics: Delivers detailed reporting on revenue, ROI, ROAS, and CAC.
- Intent Data Revelation (Reveal): Identifies buying signals from first-party tracking, LinkedIn ads, G2, and other sources.
- Audience Hub: Allows creation of custom audiences from go-to-market data and syncs them with ad platforms like LinkedIn and Google Ads.
- Data Platform: Offers robust data collection, modeling, tracking, and numerous integrations (CRM, ad platforms, marketing automation).
- B2B Benchmarking: Compares company performance against industry benchmarks based on size and ad budget.
- Unified Ad Spend Reporting: Consolidates ad spend data across multiple platforms.
Use Cases
- Measuring the ROI of marketing campaigns.
- Understanding the complete B2B customer journey.
- Attributing revenue to specific marketing channels and content.
- Optimizing ad spend based on performance data.
- Identifying and prioritizing high-intent accounts for sales outreach.
- Creating targeted audiences for ad campaigns.
- Improving alignment between marketing and sales teams.
- Reporting marketing's impact on pipeline and revenue to stakeholders.
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