How a Colombo International School Achieved a 15.2% Lower Cost Per Lead by Prioritizing Conversion

Client / Background

• Client: A prominent International School located in Colombo, known for its strong academic record and well-established reputation in the local and expatriate community.
• Market Context: The education sector in Colombo is highly competitive, with multiple international schools vying for a limited pool of affluent parents. Lead generation campaigns are common, making the cost of reaching and converting a qualified parent expensive.
• Why this project mattered: The client needed to efficiently fill spots for the high-value “December Intake,” requiring a strategy that could both generate high-volume leads and maintain a low acquisition cost to ensure campaign profitability.

Challenge / Problem

The core challenge was to determine which creative direction, Ad A or Ad B, would produce the most qualified leads at the lowest cost.

• Pain Point: Relying on instinct when scaling creative is risky; a single, inefficient ad can quickly deplete the budget.
• Business Goal: The marketing team needed empirical evidence to confidently allocate the majority of the media budget to the highest-performing ad before the limited December Intake period closed.
• The Paradox: Initial metrics showed a conflict: Ad B was cheaper to deliver (lower Cost per 1,000 Reached) and more engaging (higher CTR), but the ultimate goal was the conversion event itself (the Lead).

Objectives / Goals

The primary goal was to use the A/B test to isolate a single winning creative for scaling.

• Primary Goal: Identify the ad with the Lowest Cost Per Lead (CPL).
• Secondary Goal 1: Achieve a demonstrable difference in the CPL between the two variants.
• Secondary Goal 2: Gain an insight into whether high engagement (CTR) correlates with high-quality conversion (Conversion Rate).

Strategy / Approach

The strategy was to conduct a pure, controlled Creative Split Test to measure the relationship between engagement and conversion quality.

• Insight: We hypothesized that one ad (Creative A or B) would be better at qualifying the user, meaning it set clearer expectations about the landing page offer, even if it resulted in fewer clicks overall. The true measure of a creative is not how many people click, but how many of those clicks become a lead.
• Framework: A simple, high-impact A/B testing framework was used:
  • Variable: Only the Ad Creative (Visual and Primary Text) was changed.
  • Constant: The Audience (“Broad Parents”), Ad Placement, Landing Page, and Campaign Objective (“Leads”) were identical.
  • Success Metric: CPL was established as the non-negotiable metric for declaring the winner.

Execution

The test was executed within the Meta Ads platform as a “Creative Test.”

• Channels Used: Meta Ads (Facebook/Instagram).
• Key Creative Elements:
  • Ad A: Focused on a specific visual/text combination that, based on prior hypotheses, was expected to qualify users effectively.
  • Ad B: Focused on a highly engaging, high-CTR visual/text combination designed to maximize clicks.
• Technology Involved: Facebook’s native A/B testing tool was used to automatically divide the audience and budget (though the algorithm quickly favored Ad A). Analytics were pulled from the Ads Manager.

Results

The test ran for 72 hours, generating a conclusive result based on the conversion objective.

Hard Metric Success: Ad A achieved the target goal, delivering leads at a cost savings of Rs86.75 per lead compared to Ad B.

Soft Outcome: The test validated the theory that cost-efficiency is determined by post-click conversion rate, not by the initial cost of delivery or engagement.

Key Learnings / Insights

The High-CTR Trap: Ad B demonstrated that high engagement (CTR) is not an end in itself. Its creative was too broad, attracting a large volume of “junk traffic” that ultimately failed to convert. A higher CTR with a low conversion rate is simply a fast way to spend money.

Conversion Rate is the True Creative Metric: The success of Ad A was not in its popularity, but in its ability to generate high-quality clicks. Ad A’s superior Conversion Rate (10.85%) was the variable that overcame its higher cost per click.

The Algorithm was Right (But Opaque): Facebook’s algorithm quickly favored Ad A with a higher spend because it was achieving the optimal end-goal (Leads) more efficiently than Ad B. The initial overspend on Ad A was strategically justified by the better long-term performance.

Strategic Takeaway: For high-value lead campaigns, the focus of creative testing must shift from “How can we get them to click?” to “How can we get the right person to click and commit?” Future creative variants must be modelled after Ad A’s messaging and qualification tactics.