Why Marketers, not Ad Tech & Agencies should care about Privacy Changes A Spotlight on Google’s Limited Ads Solution

There is nothing better than getting something that suits you perfectly, or being presented with something that is just right for the given moment – but with consumer data becoming more private and less accessible, these changes make it more challenging for marketers to address consumers in a relevant and privacy compliant way.

Dynamic Creative Optimisation (DCO) Solutions have played a rewarding role in marketing strategies over the years. Advertisers and tech giants have shared countless studies on how personalized creatives contribute to increased revenue and increased marketing-spend efficiency, so it goes without saying that we need to continue driving to improve the quality and variety of ad creative.

However, DCO flourishes with data enrichment – so does this mean that the recent announcements by tech giants will change the efforts that marketers have poured into effective and efficient creative solutions? In short, absolutely not. This will be the renaissance of creative – with the death of 3rd party cookies, it only takes adaptation to again lead with a rewarding data-driven strategy.

With the introduction of major privacy changes it’s important for marketers to  consider the following :

Take total control of first-party data

Make it as comprehensive and usable as possible – if you haven’t already started to prepare your marketing strategy, now is the time. Companies that have already prioritized first party data are assured for market dominance.

Example: Use dynamic creative strategies such as geo, feed-based product campaigns, demographic targeting and modelled behavioural prospecting combined with high-quality data that has been derived from 1st party audience lists and continue to deliver a personalized experience and send consumers messaging they expect.

Context will be King

Future proof your DCO setup with a ready to deploy contextual strategy that can scale.

Example: Activate a contextual creative strategy using keywords as signals. Creative variants should match content on webpages. These strategies are great for relevant product placing. When modelling new audience insights, choose to use a keyword approach, where your ad can be matched with keywords on the page, example, if you sell hair products, and a user is searching for information about damaged hair, you can place your relevant product on a page using “hair” as the keyword of focus; or choose a category approach to show your product that is relevant to certain categories – for example, if you are selling runners shoes, you can place your product on a webpage that is all about running.

Prepare for conversational creative

Using ‘tailored help’ strategies, you can provide a better landing page experience for consumers, but the real reward is the data you collect in this process.

Example: Use smart AI-powered technology such as AdLingo and simply start a conversation with your consumer. Keep it fun and engaging whilst you gather more information about the user in order to create a more personalized experience. Over time these strategies will become more refined as you gain valuable learnings each time.

The aforementioned considerations will set you well on your way, but it does not yet take care of all the blindspots. Online advertising relies heavily on retargeting as a means to fuel revenue. Cookies make retargeting easy, as it provides a lot of customer specific data. We have been using this data to tailor our ads to focus on specific audiences who are most likely to buy or show interest in our products or services. However, with cookies losing their relevance, what are the alternatives for us to better model our audiences?

Give a warm welcome to the return of profiling personas, but this time around we graduate with smarter technologies to help better model our next consumer interaction – Machine learning models can help identify the individual makeup of elements in an ad and correlate what elements, such as images and colors, resonate best with specific audience segments.

Using creative solutions, such as Seamless Creative, Advertisers can keep up with the velocity of changes required to build up all of these learnings. Feeding this data into creative scoring models can then help assess the performance of creative as well as create predictive audience pools.

Another consideration is using real-world signals as additional signs of enrichment, for example Google Trends, Stocks or Weather. Using our Seamless Audience technology we are able to define what these rules are. We can then monitor what is most relevant at any given moment, and use these insights to define how we want our campaigns and creatives to adjust. When the moment is most opportune we can ensure we capitalize on it by automatically adjusting campaign bids.

Using technologies such as Ads Data Hub, Advertisers can now combine newly created and existing 1st party audiences with campaign level data and use machine learning results to create a predictive audience segmentation for activation.

The key takeaway, we are absolutely in the midst of an important shift in marketing. Data collection and use as we know it is changing rapidly, we simply need to get ahead of the inevitable restricted access and continue to innovate with smart solutions to help set us back on track.

For more information on the upcoming privacy changes, and the logistics of Dynamic Creative Optimisation Solutions in a cookie-less world, get in touch today.

This blog was originally published on Incubeta.

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