Increased online privacy, control of user data and walled gardens are common topics of discussions among digital marketers and will continue to make headlines with Google’s recent announcement to delay the removal of its third-party cookies yet again.
Post Apple’s iOS 14.5 update in April of last year, which introduced a new App Tracking Transparency (ATT) protocol, Google announced that they would remove third-party cookies on Chrome by the end of 2022. The move, which has been on the cards since 2020 came as no surprise as Chrome and other web browsers have been tightening their cookie policies and look-back windows for years, long before Apple made the update.
More recently, and to some marketer’s delight, it was announced that Google will delay the removal of third-party cookies at the end of 2023. Despite the delay, many marketers are already underway with plans and strategies to live in a cookie-less world as marketers have seen it coming for some time now. The rise of 1st party data, the incorporation of said data and the increased reliance on machine learning all within the privacy constraints has become common place, but there still lies a few additional factors marketers should be taking into consideration to ensure the transition has the least amount of impact on their businesses.
The growth of cookies
Cookie-based targeting is engrained in most digital marketing plans, but it was the rise of programmatic advertising that really enabled this now common practice to be so effective. Cookies have been a powerful tool for marketers and digital brands to reach the right audience, with the right message, at the right time, and sums up perfectly the synergy between cookies (the audience), creative (message) and programmatic (time). As start-ups and some digital brands across the world have boomed, they have become more reliant on digital marketing to grow their business and forgoing essential brand marketing. This poses a significant challenge ahead as the removal of third-party cookies may mean an estimated 30% decline in Return on Advertising Spend (ROAS), as the ability to target ads based on rich user-based profiles comes to an end.
What do marketers need to know:
The removal of third-party cookies is ultimately for the better in an aim at giving consumers more control over their privacy and information online, however there is no doubt that it won’t have a huge impact on online earnings, with Google, in a recent study, disabling third-party cookies publisher revenue, estimating that brands might be at the risk of losing circa 50% of their revenue when they can no longer tap into cookies. Put simply, the removal of third-party cookies will mean:
- Increased reliance on first-party data – Customers want more control and are happy to release their data if it is at a benefit to them. In a recent study , 79% of participants agreed that they wanted to have more control of their data online and 53% wanted companies to take more proactive steps in teaching them about their company’s online data privacy. To achieve a harmonious data exchange relationship with customers it’s important to first establish a foundation for customer data management, followed by a tailored data collection strategy that aligns with best practices including incentives to sign up. And lastly, the opportunity to create compelling touchpoints for data collection among owned channels, such as a loyalty programme. Marketers need to get customers to willingly share their preferences by building compelling touchpoints for data capture as consumers make their way to a purchase on owned channels.
 source: Gartner Consumer Community (2020) Survey n=325
- In-depth understanding of your customer – Customer surveys and feedback forms are important in understanding your customer and their experience with your product. Having a clear idea of who your “broad” audience is vs your “targeted” audience will help tailor creative messaging and improve product consideration among paid and owned channels.
- Brand positioning & creative messaging – While third-party cookies were revolutionary in their own right, brand positioning and creative messaging still remain in the forefront and are perhaps more important now than ever before. Having a deep understanding for what captures your target audience’s attention and what matters to them is imperative in ensuring creative and “look & feel” is tailored to them.
- Walled garden mentality and utilisation of assets – We have already started to see the shift with Google releasing “Performance Max” and recommending increased use of customer lists (first party data) to grow reach and enable more opportunities to reach customers. Get comfortable with the old “walled garden” scenarios and allocate media, tech, and data capabilities spend accordingly. Also, expect to manage an increasing number of direct media buys with platforms and publishers — and less cross-publisher programmatic display.
- Artificial intelligence – Machine learning has become a fundamental in marketing, enabling more targeted ways of engaging with audiences at the right time, with the right message. As machine learning and performance automation evolves, it’s slowly reducing the need for data scientists and paving the way for domain experts like Google and Facebook to automatically construct machine learning applications. As this evolves further into AI, utilising these automatic functions will become imperative in identifying micro-audiences of users that are likely to respond to your message with dynamic personalised creative (image & text) for each of those audiences.
Is AI the next big thing?
AI is on its way to becoming well established and machine learning itself is merely a subset of AI. But what role will AI play as cookies no longer become available? No matter how sophisticated a company’s first-party data infrastructure is, it’s unlikely to match cookies in terms of the availability, volume, and depth. And despite cookies no longer being available, the task for marketers remains the same, to match the right message, with the right audience, at the right time to ultimately encourage an action. Success relies on learning what works from the data available and success itself is relatively easy to measure, ‘did the customer take the desired action, or not?’.
Building out dedicated machine learning models with dedicated teams isn’t realistic for most companies. No company builds their own CRM system, they simply plug into one that already exists. It’s then how, when and if you choose to use it that delivers value. The same can be said for machine learning in digital marketing.
Integrated tech giants like Google, Facebook and Amazon have the capabilities to analyse post marketing data to learn how to best allocate digital marketing spend and through AI, micro-audiences of users can be identified. Perhaps woman aged 35-41 that like travel respond more favourably when a couple is placed more prominently in an ad for a hotel? Other audiences might engage when a special offer is more prominent. AI learns these variables and builds personalised campaigns that optimise results while functioning within today’s privacy constructs.
Main Take Outs:
First Party Data
- Establish a foundation for customer data management.
- Tailor your data collection strategy and ensure that it aligns with best practices, including incentives to sign up.
- Create compelling touch points for data collection that go beyond the initial sale among owned channels, such as a loyalty programme.
Gather a deeper understanding of your customers
- Utilise surveys and feedback forms to understand your customers and their experiences with your products. Turn points of churn or friction within the post purchase experience into an opportunity to collect valuable data and feedback.
Focus on brand and creative messaging
- While data and targeting are a key part of driving a sale, creative still contributes over 40%. A-B test messaging to gain a deeper understanding for what creative and messaging captures attention and drives response.
Walled Garden Mentality
- Review channel selection, tech and data capabilities. Expect to manage more direct buys and less cross-publisher programmatic buys.
Be ready to welcome AI
- Start thinking of the best way to develop your dynamic creative optimisation strategy, including multiple image and text asset variations to target micro audiences in real time with creative that is most relevant to them.