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A business development manager at a pet care company was seeking wholesalers of veterinary cosmetics, nutraceuticals, and veterinary diagnostics across Scandinavia. Despite extensive efforts, he struggled to identify the right leads and quickly ran out of options.

A lead generation agency was tasked by a client to qualify a CRM database of 1,200 leads. The client was specifically interested in identifying heavy-duty vehicle resellers in the US. Traditionally, the agency would have involved three data assistants, each processing 100-150 leads per day, resulting in a total of 90-100 hours of work over 3-4 days. Instead, they decided to test Milda.ai.

A SaaS provider approached Milda.ai with a significant challenge: they had a list of approximately 12,000 Swiss IT companies in their CRM, each representing a potential market for various products. However, they lacked an efficient way to differentiate these companies based on their offerings. The provider needed to determine which companies specialised in HR solutions, which provided customer service solutions, and what specific software they supported to target their marketing effectively.

A business development representative needed a comprehensive list of manufacturers in Europe that produce corrugated cardboard using eco-friendly, recyclable, reusable, and biodegradable materials. However, no existing B2B buyers/suppliers platform provided the necessary level of detail.

A company specialising in sales to fitness supplement manufacturers was struggling to manage and update its lead information. With 150 existing customers and a list of 300 cold leads, the company needed to identify upsell opportunities for a new supplement technology. However, due to outdated information, they had to review all 450 leads.

A government funding agency in Europe needed to assess its investment portfolio, which consisted of over 160 high-tech companies and start-ups. The goal was to analyse these companies in terms of their technology, competition level, and market presence. An analyst representing the agency was preparing for an important meeting where he would brief stakeholders on the performance of these 160 companies.

A Swiss cancer diagnostics company sought to research the market for real-time confocal microscopy. They needed to identify companies operating in this field, as well as the products available and their specific features.

A large institution needed to enrich a database of 1.2 million companies to identify those involved in specific clean and renewable energy technologies. Additionally, they required detailed data on each company’s industry, activity type (e.g., manufacturer, distributor, logistics, design and engineering, maintenance), and investment activity. The goal was to produce this data every quarter.