Alasco

Alasco is a fintech company specializing in environmental, social, and governance (ESG) management, offering a platform tailored for ESG managers, sustainability managers, and asset managers. Their platform supports financial controlling and ESG management, helping clients navigate the complexities of sustainable investing and governance. Despite having a clear understanding of their ideal customer profile (ICP), Alasco sought external expertise to optimize their ICP scoring model within HubSpot. Their goal was to enhance their sales team’s ability to prioritize and qualify leads effectively by quantifying fit and engagement scores.


Alasco approached ATAK to leverage best practices in building a robust ICP scoring model. They aimed to create a system that would provide actionable insights into their target companies, focusing on asset managers and investment managers. The model needed to incorporate key data points such as company activity, assets under management, and asset classes, while also integrating engagement scoring for both low and high-intent interactions. Additionally, Alasco wanted to incorporate dynamic scoring elements, such as score decay over time, to ensure their data remained current and relevant.

ATAK collaborated with Alasco to design and implement a comprehensive ICP scoring model within HubSpot. The solution involved several key components:

1. ICP Scoring Model:

   • Fit Score: A score ranging from 0 to 100 was developed to quantify how well a company aligns with Alasco’s ICP. This score was based on two primary properties: company activity (industry focus) and assets under management. Asset classes, such as real estate (retail, healthcare, etc.), were also integrated into the scoring model.

   • Engagement Scoring:

     • Low Intent Engagement: This score tracked lower-intent interactions such as website visits, email opens, LinkedIn ad engagements, and content downloads (e.g., white papers, newsletter subscriptions). Scores decayed to zero after 30 days if no further activity was detected.

     • High Intent Engagement: This score focused on higher-intent actions like event registrations (webinars, roundtables, physical events) and form submissions (e.g., "Book a Demo," "Talk to Sales"). These activities were weighted more heavily in the overall scoring model.

2. Dynamic Scoring and Decay:

   • To ensure the scoring model remained accurate and up-to-date, ATAK implemented a decay mechanism for engagement scores. For example, website session scores would reset to zero after 30 days if no additional activity occurred. This dynamic approach ensured that only recent and relevant interactions influenced the scoring.

3. Data Enrichment with Clay:

   • ATAK utilized Clay, a data enrichment and automation tool, to enhance Alasco’s data capabilities. Clay was used to:

     • Enrich Asset Classes: Since asset class data was not initially available in HubSpot, Clay was employed to scrape and enrich this information from external sources, including PDFs and company websites. The enriched data was then integrated into HubSpot.

     • Monitor Hiring Signals: Clay was configured to track new C-level hires and job postings within Alasco’s target companies. This data was used to create a "timing score," which added points to companies that recently hired key roles (e.g., CSO, Director of Sustainability) or posted relevant job openings.

     • Automate Data Updates: Clay’s integration with HubSpot ensured that new data points (e.g., asset classes, hiring signals) were automatically updated in real-time, reducing manual effort and improving data accuracy.

4. Custom Workarounds for Complexities:

   • ATAK addressed challenges such as parent-child company relationships (e.g., Deloitte UK vs. Deloitte US) by implementing custom solutions to ensure accurate data attribution. While Alasco opted for a manual review process for these cases, ATAK provided the framework for future automation.

The implementation of the ICP scoring model and data enrichment processes delivered significant value to Alasco:

1. Enhanced Lead Prioritization:

   • The Fit Score and engagement scoring provided Alasco’s sales team with a clear, quantifiable method to prioritize leads. For example, a company with a Fit Score of 70 or higher was identified as a strong prospect, enabling the sales team to focus their efforts on high-potential opportunities.

2. Improved Data Accuracy and Insights:

   • The integration of Clay allowed Alasco to enrich their data with critical information, such as asset classes and hiring signals, that was previously unavailable. This enriched data provided deeper insights into their target companies, enabling more informed decision-making.

3. Dynamic and Actionable Scoring:

   • The decay mechanism ensured that engagement scores remained relevant, while the timing score provided additional context based on recent hiring and job posting activities. This dynamic approach allowed Alasco to adapt their outreach strategies based on real-time data.

4. Scalability and Efficiency:

   • The automated data enrichment and scoring processes reduced manual effort and improved operational efficiency. Alasco’s team could now focus on strategic activities rather than data entry or validation.

5. Future-Proofing:

   • The solution was designed to evolve with Alasco’s needs. The ICP scoring model and data enrichment processes can be iterated and expanded as Alasco’s business grows, ensuring long-term scalability.