In collaboration with Crimtan.
In this article written exclusively for ExchangeWire, the Crimtan team discusses how Dynamic Creative Optimization (DCO) can be used to maximize sales, the top mistakes marketers make when using DCO ads, and how they can continue to be used effectively in the post-cookie environment.
Are you taking full advantage of the power of DCO to achieve maximum performance for your ad campaigns? Or are you offering sales to your competitors through two important but common mistakes?
Dynamic Creative Optimization (DCO) is becoming increasingly popular with advertisers today, and for good reason. DCO is a type of programmatic advertising that allows brands to personalize and optimize the performance of their ad creative using real-time technology.
In DCO, agencies assemble a selection of advertising components, such as backgrounds, lead images, text, value propositions, and calls to action on a digital asset management system. The creative can include video, animation, native components, and interactive elements. Then, when an ad is shown, it is compiled in real time with elements adapted to the user who will see it – to obtain the optimal result.
What that outcome might be depends on where a user is in the customer lifecycle and can include everything from initial engagement or user interaction (e.g., a click or a hover), to a KPI such as a registration, a trial or a purchase.
There are many mistakes you can make when planning a DCO campaign. But even if you know the basics well, you can still miss out on the true power of DCO with two important missed opportunities.
First missed opportunity: lack of data
The first missed opportunity is the lack of data, or inability to use data depths in DCO.
DCO offers advertisers virtually unlimited possibilities to deliver an ad that is precisely relevant to a user – and therefore much more likely to prompt the desired action. But DCO campaigns are only as good as the data that powers them.
Obviously, if you get the data wrong, the ad won’t deliver the results you need. But the lack of data is equally disappointing. Why? Because it’s like having the keys to a Ferrari and never getting out of first gear; you have so much power at your disposal and you are not using it.
To give you an idea of the power, let’s take a look at a campaign we ran for a global leader in vehicle rental.
Most advertisers can use first-party and third-party data (where available) to produce ads that they hope reflect a customer’s current needs. But we went further with our client.
Not only is our unique identifier, ActiveID, able to combine deterministic, probabilistic and signal data to produce a rich hybrid targeting system that achieves a match rate of over 95% for targeting and tracking audiences, but we also have developed a way to use our customers’ own data. back-end data to deliver truly personalized DCO ads. Ads that can reflect the destination and model of car customers are looking for, and let them know the current price and availability of that model for their destination.
If your agency isn’t able to serve DCO ads powered by this depth and wealth of data, you’re missing out on an important opportunity — and potentially giving business to your competitors.
Second missed opportunity: lack of attribution
The second missed opportunity is lack of attribution. We’ve long campaigned against the use of the badly flawed last-click attribution model, and now even Google has abandoned it in an effort to “provide marketers with more accurate, more accurate, and more customer-centric metrics.” confidentiality”.
But the machine learning options offered by Google and others still fall short. Because rather than giving you granular, holistic information that you can act on with confidence, getting into abstract machine learning means you’ll actually have less insight into the interpretation. All you will know is that some strings are more valuable than others… for some unknown reason. So you still can’t make accurate predictions in the future.
So what is the alternative? For us, the only true and accurate attribution model is Total Media Attribution (TMA). The goal of TMA is to understand how media spend affects sales and optimize the allocation of spend across media to achieve the optimal media mix. TMA can track where online and offline conversions are coming from, across a variety of different channels. It can measure the success of ongoing campaigns and, more importantly, it can simulate conversion returns on future campaigns.
The TMA model works on everything from TV, radio, print and PR to digital, including Facebook ads, Google Ads, programmatic, DOOH, CTV and audio, and delivers prediction accuracy that reaches a statistical significance (over 95%) and aims to be around 99%.
TMA can predict exactly where your returns will come from and how you should weight your spend across your entire marketing campaign. It can even account for seasonal variations and geographic preferences. So if people in Germany prefer print, you can increase it. And if people in the US like the video, your predictions will reflect that.
You can also explore the returns your campaigns will get with each media balance, and what will happen if you do nothing at all in a particular channel.
As you can imagine, TMA is a powerful tool when used on your DCO campaigns and can ensure your budget is spent on ads that will actually deliver the results you need.
Are your DCO ads underperforming without you even realizing it?
DCO is a powerful tool; one with offers advertisers a world of exciting opportunities. But just think about the potential you lose if you don’t take advantage of all your data opportunities and fail to fully attribute your campaign performance.
If your DCO ads are currently progressing in first gear, isn’t it time to find out how far and how fast your campaign performance can improve with the right data and attribution?