Manually enriching leads is an inefficient and costly process, and CRM data quickly becomes outdated. The solution is an autonomous AI system that transforms a single email into a complete, structured customer profile in real-time. Such a system, built using no-code tools, search APIs, and language models, allows you to create a lasting competitive advantage.
Why is manual lead enrichment a waste of time and money?
The problem of data quality in CRM systems is critical. Studies show that up to 40% of customer information can be incorrect, incomplete, or outdated, costing companies an average of $15 million annually. The situation is worsened by data decay, which progresses at a rate of 22-30% per year. This means that almost a quarter of your contact base becomes useless each year.
Traditional, manual searching for information about new leads is slow, error-prone, and inefficient. Sales Development Representatives (SDRs) can spend up to 21% of their workday on this - time they could be spending talking to customers. The delay in contact is crucial, as initiating a conversation within the first hour of lead registration increases the chance of success sevenfold. Manual processes prevent achieving such speed at scale.
What is the architecture of the Prospect AI system?
The Prospect AI engine is an integrated system based on the synergy of four platforms, each playing a crucial role. The architecture is designed for scalability, reliability, and rapid deployment, eliminating the need for traditional software development.
- HubSpot CRM: Acts as the central system for storing lead data. Most importantly, it serves as the trigger point for the entire process when a new contact appears in the system.
- Make.com: This is an iPaaS (Integration Platform as a Service) platform that forms the backbone of the automation. It visually manages the entire workflow, connecting the APIs of individual services without writing code.
- Google Enterprise Search (Vertex AI Search): A key technological component. It enables instant searching and indexing of public web data, including the prospect's company website and their official LinkedIn profile.
- OpenAI GPT-4: A generative AI model that acts as the intelligence layer. It analyzes large amounts of unstructured text, understands its context, and generates standardized data in JSON format according to predefined requirements.
How does the automated lead enrichment process work step-by-step?
The entire process takes place within a single, fully automated scenario on the Make.com platform. This ensures real-time lead enrichment, immediately after acquisition.
- Trigger - New Lead in HubSpot: The process starts automatically when a new contact appears in the CRM.
- Domain Processing: The system extracts the domain from the email address, retrieves the company website content, and converts it to clean text.
- Search - Google Enterprise Search: The processed text and company name are used to identify the company's official LinkedIn profile. This is a crucial step for acquiring the most up-to-date data.
- Analysis and Structuring (GPT-4): Text from the website and LinkedIn profile is sent to AI with instructions to analyze it and generate a JSON object containing the company profile, its value proposition, and industry categorization.
- Qualification (GPT-4): In the second query, the AI answers a precise business question (e.g., "Does the company operate in the iGaming industry?") based on all collected data, returning a "true/false" answer with justification.
- Summary (GPT-4): The final AI query creates a concise, human-readable summary containing a general profile description and unique selling points (USPs).
- Action - Create Note in HubSpot: The final, structured result is formatted and automatically added as a note to the contact record in HubSpot.
Build or buy? Comparing Prospect AI with off-the-shelf platforms.
The decision to implement a lead enrichment system comes down to choosing between a ready-made product ("buy") and creating your own solution ("build"). Platforms like ZoomInfo or Clearbit offer access to huge, proprietary databases, but come with high, recurring costs (often over $15,000 annually) and limited flexibility. The data is standard and not always tailored to niche needs.
The "build" model, such as Prospect AI, offers almost unlimited flexibility and control. It allows you to define exactly what data is collected and - most importantly - what proprietary analyses are performed. Instead of paying for data access, you pay for its processing, which is much more cost-effective when enriching a steady stream of leads. A key competitive advantage is the ability to implement your own business logic, creating unique, uncopyable analyses that perfectly match your ideal customer profile (ICP).
Strategic applications and the future: From enrichment to autonomy
An intelligent lead enrichment system is the foundation for more advanced strategies. High-quality, structured data generated by Prospect AI is ideal fuel for predictive lead scoring systems, which assess conversion chances with much greater accuracy. Instead of relying on simple rules, a machine learning model can use custom, AI-generated fields, such as "iGaming Potential: True," to prioritize leads more precisely.
The system's architecture can also be used to automate market research and competitor analysis. Simply provide a list of competitor domains, and the system will automatically analyze their websites, extract value propositions and key messages, and then present them in a standardized report. The future belongs to so-called AI agents - systems that autonomously plan and execute multi-stage tasks to achieve a business goal, e.g., "Find 10 companies in the fintech sector that have recently secured funding and are recruiting for marketing positions." This is an evolution from automation to true autonomy in sales and marketing processes.
Frequently Asked Questions (FAQ)
The main problem is rapid data decay. Customer information becomes outdated at a rate of 22-30% per year, as people change jobs and companies merge or change contact details. This leads to inefficient sales and marketing activities.
Prospect AI is the concept of an automated system that enriches new lead data in real-time. Using no-code tools (Make.com), a search engine (Google Enterprise Search), and generative AI (GPT-4), it transforms just an email address into a complete company profile, eliminating the problem of outdated data and manual work.
No. The key advantage of this approach is the use of no-code/low-code platforms like Make.com. They allow you to create complex processes in a visual interface, without the need to write traditional code. A prototype can be deployed within a few hours by someone with technical skills at an analyst level.
Choose a ready-made solution ("buy") if your primary goal is access to a massive contact database (including private phone numbers) for active prospecting and standard data is sufficient. Opt to build your own system if your qualification criteria are niche, you need maximum flexibility, and you want to generate unique analyses based on publicly available data for incoming leads.
The system is based on three pillars: an iPaaS integration platform (e.g., Make.com) for process orchestration, a public web search API (e.g., Google Enterprise Search) for finding reliable sources, and a generative AI model (e.g., GPT-4) for analyzing, structuring, and summarizing data.
Yes, and that is its biggest advantage. Unlike ready-made platforms, you can fully customize queries to the AI model to classify and evaluate leads according to your unique, proprietary criteria - for example, assessing suitability for a very specific market niche or analyzing text on a page for specific keywords.