Case Study: 70 Qualified Leads in 30 Days for Bajada New Energy

A Malta-based energy company generated 70 qualified leads in 30 days after I rebuilt their Meta Ads targeting and creative strategy from scratch — with zero previous paid social infrastructure in place.

The Client

Bajada New Energy is a Malta-based company offering energy solutions including solar, heat pumps, and EV charging. They came to me wanting to generate consistent qualified leads through paid social — something they had not been able to achieve with previous attempts at Meta Ads.

The Challenge

Previous Meta Ads attempts had produced clicks but not qualified leads. The targeting was too broad, the creative was generic, and there was no structure to the campaign beyond a single ad set pointing at a general audience. The result: low-intent traffic, high cost per lead, and a sales team receiving enquiries that were not ready to buy.

What I Did

1. Rebuilt the Targeting From Scratch

I scrapped the existing campaign and rebuilt the targeting around specific buyer profiles: homeowners interested in energy efficiency, EV drivers, property developers, and businesses with high energy costs. Each audience got its own ad set with its own creative and message.

2. Rebuilt the Creative Strategy

The existing creative was product-focused. I shifted it to problem-focused: high energy bills, rising electricity costs, EV charging inconvenience. The creative now spoke directly to the pain the buyer was already feeling, which is what generates qualified enquiries rather than idle clicks.

3. Lead Form Optimisation

I used Meta Instant Forms with pre-fill enabled and a qualifying question about the type of property and timeline for installation. This filtered out low-intent enquiries and gave the sales team leads that were genuinely ready to progress.

4. Rapid Testing and Iteration

In the first two weeks I ran multiple creative variants across each audience. By week three, I had identified the top performers and concentrated budget on them. This is how you get 70 leads in 30 days — not by setting campaigns live and waiting, but by actively reading the data and adjusting.

The Results

• 70 qualified leads in 30 days
• Leads genuinely ready to purchase — sales team conversion rate improved significantly
• Cost per qualified lead brought to a commercially viable level
• A replicable campaign structure the client now runs month-to-month

What Made the Difference

The previous campaigns failed because they treated Meta Ads like a billboard — show the product, add a ‘Contact Us’ button, hope for the best. Paid social does not work that way. The audience does not know they need you yet. Your job is to make them feel the problem first, then offer the solution. That mindset shift — from product-push to problem-pull — is what drove the results.

If your Meta Ads are generating clicks but not leads, request a free audit and I’ll tell you exactly what’s wrong.

Frequently Asked Questions

How many leads should I expect from Meta Ads in the first month?

It depends on budget, targeting, and offer. For a local B2C service with a budget of €1,500–2,500/month, 30–80 qualified leads in the first 30 days is achievable with a well-structured campaign. The key word is qualified — volume without quality just wastes the sales team’s time.

What is the difference between a lead and a qualified lead on Meta Ads?

A lead is anyone who submits a form. A qualified lead is someone who matches your ideal buyer profile and has genuine purchase intent. The difference is usually in how the form is structured and how specific your targeting is. Generic targeting produces generic leads.

Why do Meta Ads campaigns fail to generate leads even with a good budget?

The most common reasons I see: wrong audience (too broad or wrong demographics), product-focused creative instead of problem-focused, no qualifying mechanism in the lead form, and no testing structure. Budget is rarely the issue — strategy is.

How quickly can a Meta Ads campaign be turned around?

A complete rebuild typically takes 1–2 weeks to set up and launch. Results start appearing in week 2–3 as the algorithm optimises. By week 4, you have enough data to know whether the approach is working and what to adjust.