How we built a contact data acquisition and lead qualification system for the industrial maintenance sector

Client

Orvaldi is a Polish manufacturer of UPS power supplies, inverters, PV systems, and generators. For over 30 years, they have provided reliable power solutions for homes, offices, server rooms, industry, and public institutions. The company works with clients in Poland, Czechia, Slovakia, Slovenia, and Italy, focusing on high quality, durability, and energy security.

Challenge

Orvaldi asked us to identify and acquire the best-matched companies and decision-makers in the B2B maintenance industry across five markets: Poland, Czechia, Slovakia, Slovenia, and Italy. The primary goal was to obtain personal phone numbers of technical and management personnel, general information about the companies, and overall contact data available on their websites.

Solution

Strategic workshop with the client

We began the collaboration with a workshop involving the Orvaldi team. This helped us understand who their ideal customer is and why. Crucially, we explored how potential clients describe themselves online and what the model companies within that group look like.

Based on the workshop, we identified target company categories and keywords used by Orvaldi’s existing clients.

Traditional segmentation that didn’t work

Following the workshop, we focused on three industry labels: Commercial and Industrial Machinery Maintenance, Repair and Maintenance, and Electronic and Precision Equipment Maintenance. We identified 305 companies and analyzed their personas and websites. However, only 13 of these companies truly fit the Ideal Customer Profile (ICP), leading us to conclude that a second iteration and a new lead identification approach were necessary..

Model ICP and use of keywords

We created a profile of the ideal maintenance company based on data provided by the client and insights from the 13 companies identified during the first round of research. Rather than relying on assigned industry categories as the first filter, we focused on the functions that companies actually perform within their respective industries.

What does this mean in practice? Many companies offering maintenance services do not classify themselves as "maintenance" firms. Instead, they position themselves in the industries they serve - for example, as machinery manufacturers, industrial service providers, automation suppliers, or engineering services companies. For this reason, we built a custom AI assistant that analyzed each found record using keywords to determine whether the company description matched the ideal ICP description.

We conducted research separately for each of the five target markets in their native languages: Polish, Czech, Slovak, Slovenian, and Italian. This allowed us to adapt our queries to local semantics instead of translating mechanically from English. It helped us capture nuances that were critical to precise search results. This approach can increase the volume of discovered data by up to 30%, especially in more traditional sectors.

In the end, we identified 564 entirely new companies and qualified 298 records as potential target customers for Orvaldi.

Automation with AI Agent (ClayGent)

We built an AI agent that searched company websites for contact information and identified people responsible for technical operations and management.

The assistant visited the websites of discovered companies and returned data such as:

• Full name
• Business email address
• Personal email address
• Company phone number
• Personal phone number
• Company description
• Additional confirmation of semantic match to the desired model