CAC vs CPL in telecom:
why optimizing CPL destroys the business

This is the costliest trap in the telecom industry: an agency delivers a report showing a $18 MXN CPL, the business celebrates, and six months later it is losing money on every customer acquired. The agency was right about the CPL. The problem is that CPL was the wrong metric.

The fundamental difference

CPL (Cost Per Lead) is what you pay for someone to fill out a form or ask to be contacted. It is a platform metric: easy to measure, easy to optimize, and completely disconnected from what the business cares about.

CAC (Customer Acquisition Cost) is what you pay for someone to become a paying customer. It includes CPL, the real conversion rate (not the platform's), the operating cost of closing and any friction in the post-lead process.

Why telecom amplifies the problem

In most verticals, a low CPL with mediocre conversion can still be profitable because the average ticket absorbs it. In prepaid telecom, margins are thin and revenue per conversion is low. A CPL that looks excellent can hide an unsustainable CAC.

The mechanics are simple: to lower CPL, platforms optimize toward the kind of user who fills out forms most readily. Those people are not necessarily the ones who complete a port-in, activate a SIM or become customers with positive LTV. The algorithm is optimizing for the cheap lead, not the profitable customer.

How we solved it at BAIT

In the first months of the operation, the dashboard showed competitive CPLs. Real conversion was mediocre — leads who walked into the store and never completed the port-in, or contacts who never answered the call center's follow-up. The dashboard CPL told none of that story.

The correction came from three architectural decisions:

• Feeding lead quality back into the system: We fed real conversion data — completed port-ins — back into the campaign through CAPI. The algorithm stopped optimizing for "someone who fills out a form" and started optimizing for "someone with the profile that converts in store".
• Changing the campaign objective: We moved from Lead Ads with a leads objective to campaigns with custom conversions representing events closer to the real customer. That raised CPL in the short term — and improved CAC in the medium term.
• Segmenting by port-in behavior: Instead of generic telecom-interest audiences, we built audiences on specific behaviours that correlated with real conversion. Less volume. Better efficiency.

The question you should be asking

Before celebrating a low CPL, ask: what happens to those leads after the form? What share of them becomes a customer? Is there friction in the closing process that the dashboard never shows?

If you don't have those answers, your system is optimizing toward the wrong metric. The algorithm is extraordinarily good at doing what you ask of it. The problem is usually what you are asking for.