Dollar in, dollars out: The over-simplification of ROI

The first time I had an espresso martini I felt like a poser.

Not because I was surrounded by advertising types far cooler than me. Though I was. But because it was at a Twitter Christmas party which I’d been invited to as a client from a high growth startup, which had gone bust a month earlier. The good folks at Twitter didn’t pull the invites, but it made the name badge situation more awkward. 

Twitter at that time, like Google and Facebook, felt like magic to me. Put this many dollars in, get this many results out, and scale as much as possible. Brilliant. My colleagues and I would stress over CPAs and LTVs and CACs and there’d be long arguments about attribution models, brand vs performance budgets, and ROI. You could, with a straight face, say things like “If we look at last click data PoP, the ROI based on current CPAs looks down because our CAC is rising, but LTV is actually up…” and people would nod their heads gravely. Good times.

The promise and simplicity of spend more on a channel, get this result was very compelling. Largely because it gave marketing hard numbers to send back to finance to justify cost, with return, and forecast more scale for more budget. Never mind that those compelling promises were from platforms that simultaneously sold the ads, the inventory and the black-box measurement touting their own efficacy…

The apparent data transparency from digital has created a lasting expectation that ROI in modern marketing is easy to figure out because everything is measurable. Most marketers I speak to, or whose work I follow, understand the real-world complexity. They get that return on this quarter, or this year’s investment will not be fully ‘returned’ this quarter or this year, or even next year, that different channels come with different measures, that much of marketing is probabilistic rather than deterministic, as Rory Sutherland reminds us.

Subsequently, a lot of folks a lot smarter than me are fed up with basic ROI as a metric. I get it. But does your Finance Business Partner, or CFO, or CEO? Or have they come up through the last-click, demand-harvesting, PPC era where dollar in = dollars out?

AI creates yet more promise, because in theory it has the capacity to move everyone closer to the data, get questions answered faster, with more specific context. But even if your AI platform can access and make sense of your marketing data (…that’s a whole other post), if you ask it the wrong question it will still answer using the framework you give it, and you may well then pay that answer forward.

If you're chasing a closed loop concept of money spent - measurable data touch points - money returned, you’ll always be chasing. Marketing is a growth engine for the enterprise. Where you're forecasting market share growth, product sales growth, revenue growth, those are all outcomes where marketing is having an influence. And for each there will be measurement concepts that everyone at the table needs to have an understanding of in order to properly articulate marketing's value creation.

Some of that includes direct return from advertising, but some of it will be the result of years of good work creating fame which compounds over time, and creates more opportunity for potential upside as it compounds. Using the language of finance alone without the deeper work of a shared understanding of how value is being created over time leaves you at risk of feeling much like I did, in East London at a tech platform party drinking espresso martinis… like a poser.

If you want to get specific on how you’re measuring and demonstrating your marketing impact, get in touch, I’d love to help.

Simon Jared is a Co-Founder of Latent and directly manages all Build Operations engagements.