Financial consulting | Social Media Lead Generation / US

The client is a financial and legal consulting firm specializing in the registration of small investment funds and asset management companies with the Czech National Bank. The company provides a full range of services, including the administration of these funds, handling communications with state regulatory bodies, managing fund accounting, and submitting annual reports. The service is positioned at a high price point compared to local Czech competitors, hence the focus is exclusively on the international market.

 

The primary objective of the advertising campaigns was to generate a consistent flow of client leads through online lead forms to plan budgets and workload effectively.

The target audience is defined as:

• Demographics: Primarily males, aged 30-60. This was later adjusted to 27-57 and then expanded to 27-65+ during optimization.
• Social Status: Owners and top management (managing partners, financial directors) of investment companies, financial companies, and payment systems.
• Key Characteristic: The core audience consists of individuals and companies already searching for jurisdictions and methods to establish an investment fund but may be unaware of the advantages offered by the Czech jurisdiction.
• Geography: The initial strategy focused on Dubai, English-speaking countries, Italy, and the UK. The geographic targeting evolved significantly throughout the campaign, including tests in Argentina, Switzerland, China, Hong Kong, France, Spain, Monaco, various luxury holiday locations, and specific EU countries like Austria, Denmark, and Portugal.

 

Solution

The strategy was built on precise audience segmentation and iterative testing across multiple platforms, primarily Meta (Facebook & Instagram) and LinkedIn.

 

Audience Segmentation Logic: The core of the strategy involved creating distinct audience segments based on professional roles and interests to target decision-makers in the financial sector. Initial segments included:

1. Owners of Investment Companies
2. Owners of Financial Companies
3. Retargeting (targeting users who had previously visited the website)

 

Over time, these segments were expanded and refined to include:

• Bankers: Targeting individuals in investment banking roles.
• High Net-Worth Individuals (HNWI): A segment created to target affluent individuals.
• Look-a-Like Audiences: Created based on existing lead data to find similar users, with specific tests for the US and UAE.
• AlphaAudience: A custom aggregated audience combining the parameters of the best-performing segments.

 

Targeting Parameters:

• Demographics: Age initially set to 30-60, later adjusted based on performance. Gender was predominantly set to Male. Language was set to English.
• Geographic: A multi-tiered geographic strategy was employed, starting with key financial hubs like Dubai, the UK, and Italy, and expanding to a broad list of countries including the USA, Canada, Singapore, Hong Kong, and numerous European nations. Specific financial districts in major cities were also targeted.
• Interests & Behaviors:
  • For Investment Company Owners, interests included «Investment strategy,» «Stock market,» «Crypto Trading,» and «Investment management».
  • For Financial Company Owners, interests included «Financial services,» «Financial market,» and various financial job titles.
  • For Bankers, the interest was «Investment banking».
• Job Titles/Employers: A crucial layer of targeting involved matching interests with job titles like «Business Owner,» «CEO,» «Founder,» «Managing Director,» and «Chief Financial Officer» to ensure the ads reached decision-makers.

 

Workflow

The campaign was executed through an iterative process of testing and optimization across various platforms, formats, and creatives.

Format and Platforms:

• The primary mechanism for lead capture was the Meta Lead Form, used across almost all campaigns. This format allows users to submit their information without leaving the platform.
• Advertisements were delivered on Facebook and Instagram, with placements optimized for both Feed and Stories.
• LinkedIn Ads were also tested, targeting users by job title («CEO + Asset Management,» «Owner + Finance») and using both lead forms and website traffic objectives. However, LinkedIn campaigns were later paused due to poor performance (1 lead for $377.65 spent).
• TikTok Ads were introduced later in the campaign to test a new channel, with 9 leads generated at an average cost of $15.96 in one period.

 

Creative and Copy Testing (A/B Testing): A systematic A/B testing approach was central to the workflow.

• Hypothesis-Driven Testing: Each reporting period concluded with hypotheses for the next phase, such as testing new creatives, audience segments, offers, or geo-locations.
• Creative Iteration: The team regularly developed and tested new ad creatives (referred to as «var» versions, e.g., var5, var12, var13). Performance was closely monitored, with low-performing creatives paused and budget reallocated to winners. For example, in one test, «var 5» generated 62% of leads, while «var 1» and «var 3» were paused due to poor performance.
• Ad Copy Examples: The ad copy was tailored to specific audience segments, highlighting key benefits.
  • • For Investment Company Owners: «Ready to launch your investment fund in the EU 🇪🇺? Our turnkey registration services have got you covered! … 👉 Contact us today to take your investment company to new heights!».
  • • For a broader audience: «Are you seeking an opportunity to bring your holdings into a legal framework? We offer fund registration and asset management services. ➤ Tax rates as low as 5% ➤ Full beneficiary confidentiality … Please click on the button and fill in the form to get a consultation from our expert».
  • • Offer variations: Some creatives included the price («Only for 40K Euro») to pre-qualify leads.

 

 

Campaign Optimization: The workflow was highly dynamic, with frequent adjustments based on performance data:

• Budget Rebalancing: Budgets were regularly shifted from underperforming campaigns, ad sets, and locations to those delivering a lower cost per lead.
• Pausing Low Performers: Ineffective segments (e.g., Argentina due to low-quality leads, HNWI segment) and campaigns (e.g., LinkedIn, TikTok campaigns with high CPL) were paused to optimize spending.
• Launching New Campaigns: Successful tests led to the launch of new, scaled campaigns, such as the «2.4.4 WWA — LeadForm — 2024 — Advantage+» campaign, which became the top performer.

 

Results

The campaign successfully generated a significant volume of leads over its duration. The following table summarizes the overall performance across the main documented campaigns on Meta platforms.

 

 

Overall Performance Summary (Meta Campaigns):

• Total Leads: 4359
• Total Amount Spent: $43023
• Average Cost Per Lead (CPL): $9.87 

• Total Reach: 824,422
• Total Impressions: 3,425,003

 

Performance Evolution: The average cost per lead fluctuated based on the tests being run, but the continuous optimization efforts kept it within a target range.

• Early Phase (Sep 2023): CPL was high at $33.37.
• Optimization Phase (Oct 2023): CPL dropped significantly to $9.85 after refining geo-targeting and creatives.
• Scaling Phase (Jul — Sep 2025): The CPL reached its lowest points during this period, with monthly averages of $5.52 and $6.34 as the Advantage+ campaign was scaled.

 

Lead Qualification Insights: The lead form included qualifying questions to segment incoming leads by interest and scale. Analysis of responses shows:

• Most Requested Service: «Asset management company registration» was the most frequently selected option.
• Company Scale: The majority of leads were interested in registering «small-scale» (up to 5 million euros) or «medium-scale» (5 to 50 million euros) funds.

Conclusion: The targeted advertising strategy on Meta platforms proved highly effective for generating qualified leads in a niche B2B financial consulting market. 

The success was driven by a rigorous, data-led approach to audience segmentation, continuous A/B testing of creatives and offers, and dynamic budget optimization.