Let’s say you’re a home decor brand. Like a lot of home decor brands, you do virtually all of your business on Amazon, and spend a lot of your time trying to figure out what works on the platform. How to cut through the noise? What are customers responding to? And how do you know you’re acquiring the right customers—the ones that will return to your brand again and again?

In the days before tightened privacy restrictions, when the third-party cookie was ubiquitous, this process was somewhat easier: you simply tracked a customer through the open internet. These days, things are somewhat more complicated. The adtech world has spent much of the last few years trying to find a workable middle ground—one that provides actionable insights for brands while still protecting customer privacy in meaningful ways.

Amazon Marketing Cloud (AMC) is currently a sterling example of what is possible in this new environment. As a privacy-safe data clean room, it only accepts pseudonymized information and exclusively provides aggregated, anonymous outputs. New integrations and tools are allowing for even finer-grained insights into customer behavior, helping marketers make smarter decisions at every stage of the funnel.

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Return on ad spend (ROAS) vs. lifetime value (LTV)

The nature of the change at hand comes down to two key metrics: ROAS and Lifetime Value (LTV).

ROAS, while a useful metric in and of itself, is also a fairly blunt instrument. Its formula is simple: the revenue from the ads in question, divided by how much it cost to run them. You can get a sense of how your campaigns are faring from ROAS, but they won’t tell the whole story.

There are a few reasons for this. One is that ROAS is an aggregated statistic: it mixes existing and new customers. What that means is that it counts already acquired customers towards its total. In theory, you could be spending money on “acquiring” customers who were already going to buy the product in question even without your targeting. What might look like momentum may actually be stasis.

Previously, it was thought that this was a necessary tradeoff of the new privacy paradigm. But recent developments are demonstrating that this isn’t the case. With the right integrations, AMC can now also show the lifetime value of acquired customers.

This is a key metric: it allows brands to distinguish between one-off customers—perhaps those lured in by a sale—and those who will be returning to your brand again and again, in the process meaningfully (and sustainably) growing your business.  And LTV isn’t the only new metric here: integrations are also giving brands insight into New Customer Acquisition Cost (CAC) and New Customer ROAS.

For instance, a 5:1 ROAS might look great, but if 90% of that revenue came from customers already loyal to your brand, your growth engine isn’t firing on all cylinders.

Collectively, these are metrics that tell you whether you’re moving past your established customer base or simply running in circles. Leveraging them, brands can automatically adjust bid weights to prioritize new customer acquisition and increase the share of new users.

Data science made simple

What’s crucial to stress about this shift is that you don’t need to be a data scientist to benefit from it. Previous generations of automation tools were highly complex. Built primarily by and for specialists, they required an understanding of statistical models, as well as the ability to interpret complex outputs without much user guidance. And that’s not to speak of the tremendous difficulty involved in getting them up and running in the first place—manual data integrations have never been easy, and in many cases have stalled promising initiatives before they could fully take root.

This new generation of automated tools, by contrast, can be easily used by non-technical marketers. There’s no custom setup, and the platform handles the data-matching process behind the scenes. The bidding adjustments happen automatically and in real time—enabling continuous optimization without daily hands-on tuning or manual oversight. What this means is that non-technical marketers are newly empowered: they don’t have to wait for the data science team to send crucial insights their way.

Where marketers once waited weeks for analysts to deliver reports, AMC now surfaces actionable LTV insights instantly—no SQL queries required.

Given the current online retail landscape, this is a necessary shift. The marketplace is more crowded than it has ever been, and this trend shows no signs of reversing. Marketers are spending more than they ever have, and getting less for their ad dollar than ever before. In this new environment, short-term ROAS no longer cuts it: quality over quantity is now the name of the game.

Put otherwise: the era of spray-and-pray advertising has conclusively come to an end. Long-term value is what marketers need to be chasing, and the new generation of automated marketing tools are helping them get there.

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