{"id":10850,"date":"2026-05-05T17:02:20","date_gmt":"2026-05-05T14:02:20","guid":{"rendered":"https:\/\/mondiad.com\/blog\/?p=10850"},"modified":"2026-05-07T17:04:00","modified_gmt":"2026-05-07T14:04:00","slug":"reduced-cost-per-lead","status":"publish","type":"post","link":"https:\/\/mondiad.com\/blog\/reduced-cost-per-lead\/","title":{"rendered":"Mondiad Case Study: How We Reduced Cost Per Lead by 50%!"},"content":{"rendered":"\n

Cutting costs while scaling performance sounds like the ultimate balancing act… but what if you could do both at the same time?<\/p>\n\n\n\n

In this Mondiad case study, we break down exactly how we managed to reduce Cost Per Lead (CPL) by 50% without sacrificing traffic quality or campaign volume. The important part isn\u2019t the result. It\u2019s how it was achieved, and which levers actually moved performance.<\/p>\n\n\n\n

If you\u2019re looking to stretch your budget further and drive more efficient results, this is a story worth reading.<\/p>\n\n\n\n

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Mondiad Campaign Setup<\/strong><\/h2>\n\n\n\n

The offer was sourced from a private affiliate program we had previously tested, which provided baseline performance data to inform initial targeting decisions.<\/p>\n\n\n\n

Campaign observed during<\/strong><\/td>April 2026<\/td><\/tr>
Traffic Format<\/strong><\/td>Classic Push<\/a><\/td><\/tr>
Offer Vertical<\/strong><\/td>Sweepstakes<\/a><\/td><\/tr>
Targeting<\/strong><\/td>KZ, Desktop, Windows<\/td><\/tr>
Bidding<\/strong><\/td>CPC<\/td><\/tr>
Budget<\/strong><\/td>$50 daily budget<\/td><\/tr>
Creatives & Landing page<\/strong><\/td>Simple \u201cA prize is available for you!\u201d or \u201cGet a free iPhone\u201d type of creatives.
<\/td><\/tr>
Desired CPA<\/strong><\/td>$2<\/td><\/tr>
Conversion goal<\/strong><\/td>Leads
<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\"sweepstakes
push ads x sweepstakes<\/figcaption><\/figure>\n\n\n\n

Note<\/span>: Creatives shown in this article are illustrative. The original campaign used localised variations aligned with the same messaging style.<\/p>\n\n\n\n

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Campaign Optimisation Strategy<\/h2>\n\n\n\n

Once we had some data coming in, we started cleaning things up.<\/p>\n\n\n\n

First, a whitelist <\/strong>of high-performing zones was introduced. By identifying and prioritising placements that consistently delivered conversions, the campaign budget was reallocated toward the most profitable traffic sources, eliminating waste from underperforming inventory.<\/p>\n\n\n\n

To further automate performance management, we set up Mondiad optimisation rules<\/strong>.<\/a> If something started underperforming, it would get paused or adjusted automatically without us babysitting it 24\/7.<\/p>\n\n\n\n

\"Mondiad
Mondiad optimisation rules<\/figcaption><\/figure>\n\n\n\n

Low-performing creatives were disabled<\/strong>, allowing top-performing variations to receive more impressions and drive higher engagement and conversion rates.<\/p>\n\n\n\n

Same idea with targeting.<\/strong> We noticed some segments just weren\u2019t worth it, so we cut things like 3G traffic, certain browsers, and some browser languages that weren\u2019t converting. That helped tighten things up and focus only on better-quality users.<\/p>\n\n\n\n

\"Mondiad
Mondiad campaign targeting tweaks<\/figcaption><\/figure>\n\n\n\n

And finally, we got a bit more precise with microbidding <\/strong>on ZoneID and SubID level. So instead of one general bid, we adjusted bids based on how each source was performing, pushing harder where it worked and pulling back where it didn\u2019t.<\/p>\n\n\n\n

Nothing too fancy on its own, but together these tweaks made a big difference in performance.<\/p>\n\n\n\n

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Case Study Results<\/strong><\/strong><\/h2>\n\n\n\n

In the end, the numbers tell the story: smarter strategy, better execution, stronger results.<\/p>\n\n\n\n

\"Mondiad
Mondiad case study final results<\/figcaption><\/figure>\n\n\n\n
Total spent<\/strong><\/td>$1,075<\/td><\/tr>
Total leads<\/strong><\/td>732<\/td><\/tr>
Initial CPL<\/strong><\/td>$2.8<\/td><\/tr>
Final CPL<\/strong><\/td>$1.4<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

After all those tweaks, things got a lot more efficient. The biggest win was the cost per lead dropping from $2.8 to $1.4. We basically cut it in half while keeping the volume steady.<\/p>\n\n\n\n

1. The CPL reduction was real (and sustainable).<\/strong>
Dropping from $2.8 to $1.4 CPL wasn\u2019t a short-term fluctuation. The blended CPL (~$1.47) confirms that optimisation gains held across the campaign lifecycle were not just in isolated segments.<\/p>\n\n\n\n

\"Mondiad
conversion cost before campaign optimisations<\/figcaption><\/figure>\n\n\n\n
\"Mondiad
conversion cost after campaign optimisations<\/figcaption><\/figure>\n\n\n\n

2. Volume was maintained while efficiency improved.<\/strong>
732 total leads on a relatively modest budget indicates that cost efficiency didn\u2019t come at the expense of scale.<\/p>\n\n\n\n

3. Ad spend efficiency improved significantly.<\/strong>
At the initial CPL ($2.8), the same $1,075 budget would have generated ~384 leads.
Instead, it delivered 732 leads. (~90% more volume for the same spend.)<\/p>\n\n\n\n

These results are just the beginning. With a solid foundation in place, the next step is scaling what works and unlocking even greater performance.<\/p>\n\n\n\n

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Why This Worked (Key Takeaways)<\/h2>\n\n\n\n

If there\u2019s one thing to take away, it\u2019s this: don\u2019t rely on broad settings for too long.<\/strong> The real gains come when you go deeper(zone-level, Sub ID-level, creative-level) and start treating each part of your traffic differently based on how it performs.<\/p>\n\n\n\n

Most CPL reductions don\u2019t come from a single change. They come from:<\/p>\n\n\n\n