Google’s privacy changes are coming amidst an overhaul for digital advertising as the industry looks to address user privacy concerns around access to personal data. So, what exactly does this mean for marketers? And how can they best prepare for a future without third-party data?
The loss of third-party data will change how ads are targeted, restricting the ability to identify and track user activity and interactions with a company. This will have a notable impact on digital advertising, making practices like ad targeting, remarketing, and personalisation more difficult – and leaving 54% of marketers feeling unprepared for a privacy-first future.
Many marketers are still struggling to find viable alternatives to inform their advertising strategy, and while Google has provided some leeway by postponing the death of the cookie for another two years, its demise is inevitable. However, it’s not all doom and gloom. Digital advertisers can pivot their strategy to reflect the privacy-first sentiment of the industry – they just need to look at the data they already have on hand.
Leveraging first-party data in a privacy-first world
This is where first-party data comes in. Digital advertisers have a unique opportunity to look beyond the frothy third-party data stream to existing user data from their own apps.
Leveraging first-party data which is provided, with consent, by their own users is already enabling 61% of high-growth companies to adapt to the changing digital marketing landscape. By tapping into the data they already have on-hand and investing in technology that delivers and acts on insights from first-party data, marketers can map user touchpoints and engagements, without sacrificing privacy or relying on potentially erroneous or non-compliant data from third parties.
This privacy adaptive advertising strategy enables digital advertisers to ensure their campaigns are laser-targeted and customised to the specific users most likely to engage. Leveraging first-party data is only beneficial, however, if marketers can gain accurate insights at scale.
Gaining user insights at scale with machine learning
Digital advertisers need to up-level their use of customer insights by implementing machine learning capabilities to manage them at scale. This is all the more crucial today, when many legacy adtech solutions are no longer suited to a privacy-first era.
Automated machine learning-based approaches have a distinct benefit here, as they can adapt to the changing digital landscape quickly and holistically, whilst prioritising customer privacy. Machine learning solutions are not all the same, however, so marketers should ensure that the solution they implement uses deep neural networks to enable them to analyse and contextualise first-party data to rapidly adapt to user data in real-time.
The shift to privacy-first advertising has been a significant change for the digital marketing industry. But, through the use of first-party data and machine learning solutions, marketers can pivot their advertising strategy to provide targeted ads for their users, without relying on third-party insights or sacrificing consumer privacy. It is this privacy-first approach that will set savvy marketers apart and enable companies to navigate the looming industry changes successfully.
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