Applying a single attribution model, like last-touch, to all channels is a mistake. It undervalues top-of-funnel activities and can lead to budget cuts that starve the pipeline. Instead, measure each channel based on its intended outcome and funnel stage.

While a blended CAC is the North Star metric, don't discard individual channel analysis. Use siloed metrics to diagnose problems. When your overall blended CAC increases, dive into the channel-specific data to identify the underperforming source, such as ad fatigue on a specific platform.

A blended CAC across all channels hides crucial information. By calculating CAC for each individual platform or method (e.g., paid ads, content, outreach), businesses can identify their most efficient channels. This allows them to reallocate budget and effort to the highest-performing areas for more profitable growth.

Don't combine branded and non-branded search when calculating channel CAC. Branded search converts users who already know you from other efforts, making its CAC artificially low. Separating them is crucial to accurately assess how well your ads are acquiring truly new customers.

A common attribution error is assigning all sales to paid marketing activities. In reality, most brands have a strong "baseline"—sales that would occur even without marketing. Accurate measurement requires modeling this baseline first, then attributing only the incremental lift from campaigns.

The business was profitable despite ad platform data showing a loss (LTV:CAC < 1), indicating a severe data attribution problem. Before optimizing or scaling ad spend, the first step must be to fix tracking to understand what is actually working, not just spend more.

Traditional digital attribution is broken. Marketers should adopt measurement models from the pre-digital era, like those used by ad agencies. This involves running controlled experiments (e.g., billboards in different cities) and measuring for lift and incrementality rather than last-click attribution.

Standard attribution models often fail to credit upper-funnel activities. A blended CAC mitigates this by focusing on total investment vs. total customers, implicitly valuing channels that influence conversions even if they don't get the final click. This prevents prematurely cutting channels that assist others.

Direct attribution models are flawed because platforms like Google and Facebook use tracking pixels to claim credit for sales that would have occurred anyway. Smart marketers are returning to older methods of measuring lift from campaigns rather than relying on misleading platform data.