TL;DR
Customer acquisition cost is the metric every marketing leader has been judged on for the last fifteen years. It is also a metric that is getting harder to compute every quarter, for reasons that have nothing to do with the marketing team’s competence. Three different metrics are starting to take over the CAC conversation inside the marketing teams I work with. They are not perfect. They are more honest about what marketing actually does in an AI-first funnel. Below is each one, what it measures, and why it works better in 2026 than CAC.
I do not want to make this article more controversial than it is. CAC is not going to disappear. It is going to keep showing up in board decks for the next several years. What is changing is the relationship between CAC and the work that produced the customer. The metric is no longer measuring what people think it is measuring. The replacement portfolio is starting to do the work that CAC used to do, plus the work CAC was never able to do.
Here are the three I am tracking now, with some marketing teams using all three and some using only the first.
Metric one: cost per relevant inclusion
Cost per relevant inclusion is the amount you spent to get your brand cited, named, or referenced in an AI-generated response to a question your prospect is likely to ask. It is the AI-era equivalent of cost per impression, and it is more useful than cost per click for a reason that should be obvious by now. Clicks are increasingly downstream of inclusions, not the other way around.
How to compute it. Take the marketing spend tied to brand awareness, content production, and discovery optimization for a given quarter. Divide it by the number of relevant AI inclusions you earned in that quarter, measured by a citation audit. The number you get is rough. The trend line on the number is what matters.
Cost per relevant inclusion is moving inversely to CAC in many of the marketing teams I am working with. As inclusions go up, the eventual customer acquisition becomes more efficient because the prospects who do convert have already met your brand in the discovery surface. The CAC dashboard will catch up to this trend three or four quarters late. The cost per relevant inclusion will see it first.
Metric two: branded demand index
The branded demand index is a composite metric that combines branded search volume, direct traffic to product pages, and the velocity of returning visitors to your top-of-funnel content. It is one number. It moves slowly. It is harder to fake than any single component.
The reason this metric matters in an AI-first funnel is that the funnel itself is no longer linear. A prospect who saw your brand in an AI response, then read a piece of your content, then searched your name, then visited your homepage, then returned to a product page three weeks later is a high-intent prospect. The traditional attribution stack will see one or two of those touches. The branded demand index will see the pattern.
What it replaces in the CAC conversation is the false confidence that the last touch caused the conversion. The branded demand index argues that the conversion was caused by a relationship that took six to twelve weeks to build, and that the marketing function should be measured on whether the relationship was being built, not on which touch closed the loop.
This is a hard conversation to have with a CFO the first time. It gets easier the second time, because the trend line in the branded demand index usually leads the trend line in the actual member or customer growth by a quarter or two.
Metric three: time to first relevant intent signal
This one is the most operational and the most underused. Time to first relevant intent signal is the average number of days between a prospect first showing up in any of your trackable surfaces and the prospect taking a measurable intent action on your site. Subscribing to an email. Starting an application. Bookmarking a page. Returning a second time.
The shorter this metric is, the more efficient your top of funnel is at converting attention into intent. The longer it is, the more friction lives in the experience between discovery and intent.
What it replaces in the CAC conversation is the dependence on a conversion rate as the only measure of funnel efficiency. Conversion rate is a lagging signal. Time to first relevant intent signal is a leading one. A marketing team that is shipping discovery improvements should see this number compress quarter over quarter, before the CAC dashboard catches up.
Why these three together
Each of the three measures a different stage of the AI-first funnel. Cost per relevant inclusion measures the discovery surface. Branded demand index measures the consideration phase. Time to first relevant intent signal measures the conversion path. Together, they cover the journey CAC used to cover with a single number that increasingly lies.
The portfolio is also more honest about uncertainty. No single metric in the three claims to attribute revenue to a touch. Each one claims to measure a directional signal about a stage. The marketing leader who reports on all three is making a different argument to the board than the marketing leader who reports CAC alone. The argument is. We can see what is happening. We can see it earlier than the dashboard does. We are investing accordingly.
That is the conversation the marketing function needs to be able to have in 2026.
Where CAC still belongs
CAC still belongs in the deck. It is the metric finance is going to ask for, and the historical comparison is still meaningful. What changes is the framing. CAC moves from being the primary metric to being one of four, paired with the three above. The marketing function reports the portfolio. The board sees the trend lines together.
The shift is not difficult. It is mostly a matter of choosing to report it. The teams I work with that have made the shift are getting more strategic conversations with their boards than the teams that are still defending the CAC number alone.
The bottom line
Customer acquisition cost is not the wrong metric. It is the wrong only metric. The three above are more honest about what marketing actually does in an AI-first funnel, and they catch the leading indicators that CAC will not see for two or three quarters.
Pick one of the three to start tracking this quarter. Add a second next quarter. By the end of the year, you will have a portfolio that does what CAC was supposed to do, plus what CAC was never able to.
Kevin Farley writes about AI visibility, AI readiness, and strategic growth for financial services. Read more on the blog.