Growth Funnel Data Retrieval and Visualization from Hubspot

[krisnaBukitVista]

Description

This project aims to retrieve data from HubSpot and visualize it using DataVista to help users harvest strategic insights. The visualizations will provide critical insights into lead progression, latency between sales funnel stages, and contact categorization. By transforming raw data into actionable insights, users can make informed business decisions to optimize performance and engagement with contacts.

Problem

Currently, users lack a clear, visual representation of the progression of contacts through the sales funnel stages, which limits their ability to:

• Monitor the efficiency of contact conversion processes.
• Assess how many Market Qualified Leads (MQLs) progress to deal status or remain as potential opportunities.
• Categorize contacts to better allocate resources for business development.

This absence of structured data visualization leads to missed opportunities for optimizing lead conversion, managing contact relationships, and aligning resources.

Solution

We will retrieve data from HubSpot and build four key visualizations on DataVista:

• Funnel Visualization: A comprehensive sales funnel that tracks the progression from contacts → leads → Market Qualified Lead (MQL) → MQL with deal → conversion to partner. This will provide a high-level overview of the conversion process and enable users to see where drop-offs occur.
• MQL Analysis: This visualization will break down MQLs by their current status, showing how many have deals, are non-RMQL subscribers, or are marked as future potential. This will help users prioritize MQLs for follow-up actions.
• Contact Categorization: This visualization will count and categorize contacts in the database based on their roles: owner, seller, buyer, vendor, or contractor. This categorization will help in better segmenting contacts for targeted communication and relationship management.

Measurement Metrics

• Data Accuracy: Ensure that the data retrieved from HubSpot reflects the latest and correct information without discrepancies.
• Visualization Integrity: The generated visualizations should be free from errors, ensuring smooth data rendering and functionality.
• User Approval: The project will be considered successful upon receiving approval from the user who requested the project, ensuring that the output meets expectations.

SLA

• Data Accuracy: Guarantee accuracy of data retrieved from HubSpot.
• Visualization Reliability: Ensure all visualizations are generated and displayed without errors.
• User Satisfaction: Getting approval from revenue manager as the user

[katibpasha]

Final Evaluation

The team successfully completed the project, retrieving essential data from HubSpot and bringing it to life through visualizations in DataVista. This achievement empowers users with strategic insights into their lead progression, highlights any latency between stages in the sales funnel, and offers a clear view of contact categorization. By converting raw data into actionable insights, the team has provided users with the necessary tools to make data-driven business decisions, ultimately optimizing performance and strengthening engagement with contacts. Link

• Data Accuracy: Ensured precise data retrieval from HubSpot for trustworthy insights.
• Visualization Reliability: Verified that all visualizations generate and display without errors.
• User Satisfaction: Achieved revenue manager’s approval, confirming the solution meets user needs.

Room of Improvement

The user requested an enhancement to the dashboard filter to allow data selection based on growth from the launch date, which is currently only accommodated by the created date.

[Vidiskiu]

Overall Point: 5

Functional Complexity: 1.5

The requirement to track multiple stages in a lead's progression, categorize contacts, and provide a high-level data overview introduces moderate functional complexity.

Technical Complexity: 1.5

Integrating with HubSpot's API to retrieve data and ensuring the integrity of the visualization process is moderately complex, and involves working with external systems.

UI/UX Complexity and Impact: 1

Creating multiple, clear visual representations for strategic decision-making presents moderate UI/UX complexity that significantly impacts user experience.

Testing and Quality Assurance: 0.75

Testing will involve validating data accuracy and visualization integrity, which is moderately complex and requires thorough verification but can be done within existing frameworks.

Risk and Dependencies: 0.25

Low risk and dependencies are expected since the issue involves retrieving data from an established API with defined metrics for accuracy and user approval.