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Data Management

newsAugust 24, 2021

More Than Just Technology

When we think about data management, we can be tempted to jump to the question “How do we do it?” which leads to a conversation around technology. Although this conversation is necessary, it is not sufficient to build a solid strategy. Why we collect the data (i.e., the specific purpose of this data in both the pursuit of business objectives and the improvement of consumer experience), and What data we collect (i.e., what data is really useful) are critical. 

The answers to the Why and What questions directly influence the How. They enlighten our tech investment decisions (e.g., infrastructure, partnerships) by helping refine our needs. We also know that people can decline to share their data or even game the system when they deem the reasons for data collection are not legitimate: 88% of them have already either refused to give or provided false personal information.[i]Additionally, sitting on data that has no potential for activation because it does not address a specific objective or it does not contain valid user information increases costs without contributing to growth and profits. 

The transition to a cookieless world is the perfect time for brands to ensure they define clear answers to the WhyWhat and How of their data management strategy.

 

Three considerations for efficient data management 

1. Define the right value exchange 

Finding the right balance in the data value exchange is no easy feat. According to the dentsu Digital Society Index, a third of people (32%) globally have opted out of receiving personalised ads in the last 12 months. [ii]

 Additional research shows that marketers generally tend to overestimate the value of the benefits they provide. Half (49%) believe they offer a fair exchange to consumers for the value of their data, [iii]while only 37% of consumers agree. [iv]

 However, as illustrated in the opposite table, marketers tend to underestimate consumers’ motivations to share their data. Interestingly, only 9% of marketers believe helping a company improve products or services is an incentive for consumers, while 44% of consumers believe so. 

 These disconnections can create a perceived imbalance in the value exchange, which can result in distrust from consumers or missed opportunities for brands. For that reason, it is important for brands to develop a clear understanding of the specific factors influencing their audiences’ attitudes and behaviours around privacy, and to build upon these insights to adjust the value exchange they propose to consumers. 

 Use Case #1: 

Invest in research to understand your perceived value exchange 

 User surveys and interviews can help you appreciate how audiences see your brand regarding privacy issues and to understand their expectations when sharing data with you. These insights are useful to define the best approaches for which your audiences would see an interest in logging in your website (e.g., rewards, gamification, product registration) – and, as a result, to build and nurture robust sources of first-party data. 

 Use Case #2: 

Tap into media consumption to identify opportunities for data partnerships 

 An in-depth analysis of your audiences’ media consumption can help you identify relevant publishers to partner with to access complementary data. We expect these second-party data partnerships to increase as companies look to build comprehensive portraits of their consumers while decreasing their reliance on third-party data sources. 

2. Invest in user education and transparent communications

 With two thirds of consumers (67%) having little to no understanding about how their data is used by companies,[v]brands that proactively reach out to customers about how they approach privacy can help alleviate concerns, explain the value they deliver in exchange for data, and seize the opportunity to differentiate from the competition by positioning themselves as trusted partners. 

 Use Case #1: 

Explaining privacy / cookie policies 

As only 22% of consumers declare they always read privacy policies,[vi]regularly educating your customers about your privacy practices in clear and concise language can demonstrate greater attention to consumer privacy needs compared to competitors only reaching out sporadically and in legal jargon when they update their policies or when a data breach happens. 

For example, this might include providing information in layers (with the most valuable information being provided in the initial layers), just-in-time notices, or using icons that convey important information (e.g., a bar graph icon in front of a description of analytics cookies). 

 Use Case #2: 

Making the case for opt-in 

 iOS 14.5 has officially been launched by Apple. After installing the update, an iPhone user opening an app is shown a popup notification asking the user to explicitly opt in to data tracking. 

Apple authorises application developers to explain to users why they would like permission to track before the prompt is shown. We encourage brands to make the most of this opportunity to explain the value they can provide in exchange for collecting data. 

However, there are strict guidelines to follow, and any incentive scheme or tactic to trick users into allowing tracking is against the App Store Review Guidelines39 and should be avoided. 

This is an excellent example of why proactively building trust is more important than ever—the brands that have been building this trust with consumers prior to launch are in a more advantageous position than those only addressing the issue after the update went live.

 Use Case #3: 

Improving user experience for privacy 

 A good user experience builds the trust needed for users to opt in and consent to marketing activities. Low consent rates are not necessarily due to a perceived lack of value in the exchange proposed by the brand, they could also be simply due to a poor user experience. 

So long as first-party cookies exist, so will cookie notifications - and cookie pop-up and banners are not created equally. These notifications should not be treated as afterthoughts and should be carefully handled by both legal and UX teams to ensure consent is properly collected and that the user choices are presently clearly and compliantly with legal requirements. 

 3. Adapt your technology infrastructure 

 The third key consideration for efficient data management is selecting and optimising the right piece of technology. The perfect out-of-the-box stack does not exist – it is all about each organisation’s needs, objectives, and operational capabilities. Many technology suppliers offer interesting solutions to support a cookieless future, such as Salesforce or Adobe. As a matter of simplicity, we will use Google’s solutions, which are prevalent among many organisations, as an illustration of how to reduce immediate reliance on third- party cookies. 

 Fundamental #1: 

Evolve your current tag setup 

 It is important that your tag setup is able to measure conversions even without third-party cookies. This means shifting to first-party cookies and identifiers, whether client-side or server-side. Client-side tagging solutions (i.e., living on the browser) are the easiest ones to implement on the short term, as this can be done through a tag management platform (e.g., Google Tag Manager). On the long term, server-side tagging solutions (i.e., living in the cloud) offer more durability and control, as you can leverage and customise them across partners. However, they require significantly more time and financial investment. 

Fundamental #2: 

Ensure you can differentiate tracking according to user consent 

 If you are not already using a Consent Management Platform, this addition to your tech stack is worth considering to help your organisation process user content on-site in a compliant way. You also need to configure your tags to automatically adjust tracking for activation and performance measurement according to the user’s consent or withheld consent: 

  • For users who consent, first-party cookies can be used to track the user journey and conversions. 
  • For users who do not consent, tracking cannot be deployed, and conversions must be modelled. To do so, several solutions are available to you. For instance, Google Analytics can integrate with IAB Europe’s Transparency and Consent Framework v2.0 to adjust tags. Another available option is to use Google’s Consent Mode to pass consent signals across the Google stack (e.g., Google Display & Video 360). 

You also need to remember that many privacy laws around the world require that once a user has consented to the use of cookies, they have the right to withdraw that consent. Consequently, you need to ensure that your chosen Consent Management Platform (or equivalent solution) allows users to easily withdraw consent or indicate their cookie preferences. In practice, for example, this may be achieved by having a "cookie" or "privacy" icon that continuously hovers at the bottom of a user's screen, which if clicked takes the user to a cookie preference window where the user can toggle specific cookies "on" or "off". 

 

Fundamental #3: 

Implement the foundational technology to prevent gaps 

 Google also offers many solutions to prevent gaps in measurement. Enhanced Conversions use hashed first- party customer data rather than relying on cookies or IDFAs. Conversion modelling through Consent Mode uses machine learning to model non-consenting conversions based on observable data. Google Analytics 4’s Enhanced measurement can also track engagements which were once difficult to monitor (e.g., video plays and exit link clicks). When using Google, we recommend marketers experiment with the different features offered by the platform - even when only available in beta – and to upgrade to Google Analytics 4 to maximise the full potential of their Google partnership. 

 

For more, download the full report today: http://ow.ly/KDTK50FKTaJ 

 

[i] Microsoft Advertising in partnership with iProspect, 2020 Consumer Privacy and Brand Trust Survey, Dec 2019 – Mar 2020, as featured in the report In Brands We Trust, published in April 2020

[ii] Dentsu, Decoding Data Dynamics: Digital Society Index 2020, Global survey of 32,000 respondents

[iii] iProspect, iProspect 2020 Global Client Survey, October 2020 

[iv] Microsoft Advertising and iProspect, Consumer Privacy and Data Survey Dec 2019 – Mar 2020, as featured in the report In Brands We Trust, published in April 2020 

[v] Microsoft Advertising and iProspect, Consumer Privacy and Data Survey Dec 2019 – Mar 2020, as featured in the report In Brands We Trust, published in April 2020

[vi] Microsoft Advertising and iProspect, Consumer Privacy and Data Survey Dec 2019 – Mar 2020, as featured in the report In Brands We Trust, published in April 2020