Synchronizes B2B attribution data to ad platforms, refining revenue-focused bidding.
Pushing attribution modeling results back to ad networks addresses the limitation of platforms focusing solely on immediate lead generation. Typically, ad networks optimize for low-cost leads rather than actual revenue. Syncing 'offline' CRM conversions, such as 'Sales Qualified' or 'Closed Won' deals, directly to platforms like Google Ads, LinkedIn Ads, and Facebook Ads via API, trains the ad networks' machine learning algorithms to target users who generate B2B revenue. This significantly improves ad efficiency by aligning bidding strategies with revenue outcomes. The process enhances the quality of leads by focusing on those that contribute to actual business growth.
Offers dashboards analyzing campaign performance through B2B pipeline generation and closed revenue.
Campaign analytics focus on business impact rather than vanity metrics. Dashboards illustrate how specific campaigns generate Leads, Sales Qualified Leads (SQLs), Opportunities, and Revenue. A key feature is filtering reports by B2B firmographics, such as company size or industry. This allows marketers to assess if campaigns engage target accounts that drive business value. The platform's focus on meaningful metrics enhances strategic decision-making for B2B marketers.
Historical touchpoint and CRM data are generally retained indefinitely for active customers.
B2B sales cycles often span many months, making short-term data purging unsuitable for accurate attribution. The platform retains digital touchpoints, CRM activities, and ad impressions indefinitely for active accounts, supporting long-term analysis. This allows for accurate connection of early interactions to later sales outcomes. Organizations needing data minimization can request purges, but the platform is designed for deep historical analysis. This setup supports detailed B2B sales cycle tracking.
Operates as a data processor with EU data residency and tools for B2B privacy compliance.
Handling complex B2B data flows, the platform adheres to GDPR and CCPA. Operating as a Data Processor, it ensures B2B organizations retain data ownership. EU data residency is default, keeping European data off US servers. Native tools execute Data Subject Access Requests (DSARs) for contact profile deletion. Businesses must operate under a valid legal basis before passing CRM data to the platform. Proper legal frameworks are important for compliance.
Delivers detailed B2B multi-touch attribution for extended buyer journeys.
Central to the system is multi-touch attribution, which maps every touchpoint across B2B accounts. Users can switch between models like Linear, W-Shaped, U-Shaped, and Time Decay, offering nuanced perspectives on how content aids sales activities. This approach eliminates bias toward immediate conversion channels, providing RevOps teams with insights into revenue-driving interactions. Analysts benefit from the ability to understand the full impact of marketing efforts over long sales cycles. The detailed attribution models ensure that all interactions are accounted for, enhancing strategic decision-making.
Integrates with CRM systems to import offline sales activity, merging it with digital marketing touchpoints.
Merging offline data with digital activity is a foundational feature of this B2B revenue attribution platform. It integrates with CRMs like Salesforce and HubSpot to import offline data such as sales calls, meetings, emails, and contract values. The identity resolution engine matches these offline activities with digital footprints, ensuring accurate representation in the customer journey. This prevents attribution credit from being solely given to digital marketing clicks, highlighting the importance of offline sales efforts.
Natively pushes cleaned, unified B2B attribution datasets to major data warehouses.
A major competitive advantage is its approach to data ownership, explicitly encouraging data extraction. Native, automated pipelines push the cleaned, unified B2B identity graph and touchpoint data directly into cloud data warehouses like Google BigQuery, Snowflake, Amazon Redshift, and Azure Synapse. This is a significant asset for RevOps and data engineering teams. It allows them to bypass the platform's standard UI and use the perfectly mapped attribution data in custom BI tools or merge it with internal financial models. This capability enhances the flexibility and utility of the data for strategic decision-making.
Directly connects marketing activities to actual CRM pipeline value.
Bridging the gap between marketing clicks and actual business revenue is a primary value proposition. By natively integrating with CRMs, it pulls in the exact financial value of 'Closed Won' deals and open pipeline opportunities. The attribution engine maps this real-world dollar value backward across all marketing and sales touchpoints that influenced the account. This definitively answers the question of marketing ROI, showing exactly how much actual revenue a specific LinkedIn ad campaign, webinar, or SEO strategy generated. It moves far beyond basic metrics like 'cost per lead,' providing a clear picture of marketing effectiveness.
Delivers precise B2B ROAS and CAC metrics.
Specialized reporting focuses on Return on Ad Spend (ROAS) and Customer Acquisition Cost (CAC) tailored for B2B contexts. Daily ad spend data from platforms such as Google, LinkedIn, and Facebook is automatically ingested and compared against attributed revenue from the CRM. Multi-touch attribution across the entire account journey enhances the accuracy of ROAS calculations beyond the flawed metrics from ad platforms. This precision enables marketing leaders to discern which campaigns are profitable and which are not contributing to the pipeline. The result is a clearer understanding of marketing effectiveness and resource allocation.
Enhances data accuracy with server-side conversion tracking, requiring technical setup.
Server-side conversion tracking captures events directly on the server, enhancing data accuracy by reducing losses from ad blockers or privacy settings. This approach offers a more reliable view of customer interactions, especially valuable for B2B marketers needing precise attribution across extended sales cycles. While it significantly improves data accuracy, implementing this feature requires technical coordination with IT teams. The result is a more dependable dataset for analyzing customer behavior and marketing effectiveness.
Enterprise security is ensured via native SAML 2.0 Single Sign-On, integrating seamlessly with Okta, Azure AD, and Google Workspace.
Recognizing its target market of mid-market and enterprise B2B organizations, the platform fully supports SAML 2.0 Single Sign-On (SSO). This allows IT departments to integrate the attribution platform directly with centralized identity providers such as Okta, Microsoft Entra ID (Azure AD), Google Workspace, or OneLogin. By implementing SSO, organizations can enforce strict password policies, mandate multi-factor authentication, and automatically provision or revoke access to sensitive revenue data based on corporate directories. This is a critical feature for mitigating the security risks associated with shared credentials and managing access for large RevOps and marketing teams.
