200 target customers from the Internet in one week - the systematic AI process

Introduction

In article 1, we defined who we are looking for. Now let's go on the hunt.

Many salespeople believe that you can't get qualified B2B leads without LinkedIn Sales Navigator or an expensive data provider. That's not true.

80% of all relevant information is publicly available online. On company websites. In business directories. In job advertisements. In association lists.

The problem is not access to the data - the problem is the lack of a method to use it systematically.

In this article, I'll show you four research sources and five ready-made AI prompts that you can use to identify 200 qualified companies in a week and collect them in a structured spreadsheet.

The four source pillars

Pillar 1: Google with advanced search operators

Google is your most powerful free research tool - if you know how to use it. Most people use it like a dictionary. Professionals use it like a filter.

The most important operators at a glance:

📋 PROMPT 4 - Develop a Google search strategy

You are a B2B research expert. I'm looking for companies,
that match the following ICP:  
[INSERT ICP FROM CONTRIBUTION 1]  

Create a complete Google search strategy for me:
PART A - 10 COMPANY RESEARCHQUERIES 
Formulate 10 specific Google search queries with 
advanced operators (intitle:, site:, filetype:, 
"phrase", OR, -exclusion) that provide me with companies from 
my ICP. For each search, explain why it works in a 
sentence.  
PART B - 5 GROWTH SIGNAL SEARCHES (job ads)
Formulate 5 searches that show me job ads from these 
companies. Job ads = growth signal = 
willingness to buy. 
(Which job titles tell me that a company 
is currently growing and needs my offer?)  
PART C - 5 TRIGGER SEARCHES 
(press releases + news) 
Formulate 5 searches for current company news,
which signal trigger events: Expansions, new 
products, management changes, digitization projects.  
All search queries in German, focus on the DACH region. 
Format as a numbered list with search query + 
1-sentence explanation.

Pillar 2: Public industry directories and association lists

Associations and industry organizations maintain public member lists. These are already pre-filtered for the target group - no ICP check necessary.

The most important sources for German SMEs:

📋 PROMPT 5 - Identify and structure industry sources

I am looking for B2B companies that fit the following profile 
  
[INSERT ICP FROM CONTRIBUTION 1]  

 Create a prioritized list of publicly 
accessible sources for the DACH region:  
For each source: 
 1. name of the source 
 2. URL 
 3. what data do I get there?(Company name, 
contact person, contact, size?) 
 4. How do I filter specifically for my ICP? 
(name specific filter settings) 
 5. free or fee-based? 
6. estimated number of relevant hits for my ICP 
Sort by: 
(1) relevance for my ICP, 
(2) free of charge Prioritize sources with at least 
50+ relevant hits. Focus on Germany, also 
Austria and Switzerland.

Pillar 3: AI-supported mass search

Individual Google searches deliver hits, but the compilation takes time. AI search tools such as Perplexity make it possible to query structured company lists in a single prompt.

Important: Always indicate that only real companies with a verifiable website should be listed. AI will otherwise invent company names.

PROMPT 6 - AI mass research (for Perplexity or bloo.research)

Research a list of B2B companies for me, 
that meet the following criteria.  
SEARCH PROFILE: 
 - Industry: [e.g. special machine construction / industrial automation
 / IT services] 
 - Region: [e.g. NRW / Ruhr area / DACH / Germany] 
 - Company size: [e.g. 50-500 employees] 
 - Special feature: [e.g. export-oriented / own 
production / multiple locations] 
 - Exclusion: [e.g.  no corporations, no startups under
 3 years]  

For each company provide: 
 1. company name (complete) 
 2. website URL 
 3. main location (city + state) 
 4. estimated number of employees 
 5. core business in 1-2 sentences 
 6. why does this company match my search profile?
(1 sentence)  
Target: 30+ companies per query. 
Format: Numbered list or table. 
Important: Only real existing companies with 
verifiable website. If unsure, rather omit
than invent.

Pillar 4: Website analysis and fit score

Not every company found is a real hit. A fit score helps you to set your priorities without having to read every website manually.

📋 PROMPT 7 - Fit score for a single company

Analyze the following company website and assign a
Fit Score.  
Website content or URL:  
[INSERT WEBSITE TEXT OR URL]  

My ICP: [INSERT ICP FROM CONTRIBUTION 1] 
My offer: [INSERT VALUE PROPOSITION FROM CONTRIBUTION 1] 

Evaluation according to four criteria (0-3 points each, max. 12 
points):  
CRITERION 1 - INDUSTRY MATCH (0-3 points) 
Does the company belong to my target industry?  
CRITERION 2 - SIZE CLASS (0-3 points) 
 Doesthe recognizable company size match my ICP? 
(Estimate from:  Number of employees, number of locations, 
product range, reference size)  
CRITERION 3 - PROBLEM AWARENESS (0-3 points) 
Is there any indication on the website of the problem I am  solving
? (Formulations, lack of digitization recognizable,
manual processes described?)  
CRITERION 4 - READINESS (0-3 points) 
Are there current signals of openness? (job advertisements,
news, growth, active blog, participation in trade fairs)  
Output: 
 - Total score: X/12 
 - Justification per criterion (1 sentence) 
 - Recommendation: Priority A (contact immediately) / 
 B(watchlist) / C (not now) 
 - Personalized interview entry: 
What would appeal to this company?

📋 PROMPT 8 - Batch analysis for many companies at once

I have researched the following list of companies 
and would like to prioritize them according to fit with my ICP:  
[INSERT LIST OF COMPANIES WITH WEBSITE - e.g. as a 
numbered list]  
My ICP: 
[INSERT ICP] 

My offer: [INSERT VALUE PROPOSITION]  
For each company on the list: 
 1.Fit score from 1-10 (10 = perfect match) 
 2. Strongest argument for or against the fit (1 sentence) 
 3. Priority: 
 A= contact immediately / B = watchlist / 
 C= exclude  

Output as table: 
| No. | Company name | Score | Reason | Priority |

The tracking spreadsheet

All companies found are moved to a central spreadsheet. Use this column structure:

The result after one week

With consistent application of this process:

In the third part, I'll show you how to find the right decision-maker for each of these 200 companies in under three minutes.

👉 Recommendation

In addition to manual research, we have developed automated processes for you:

bloo.research - Find the right B2B companies in minutes

bloo.radar - Find out what your competition will do next
before they do.

🚀 Next step

If you not only want to understand AI, but also use it in a structured way in your company, then:

👉 Find out more about our AI training:
https://bloo.school

👉 Find out about our Smart Market Fit offers:
https://bloola.com/smf - The Smart Market Fit course
https://bloola.com/smf-system - The Smart Market Fit system for companies

👉 Or find out more about our consulting and automation solutions:
https://bloola.com