Data privacy is the future of digital marketing: Here's how to adapt

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This article by Peter Rice, AVP, Marketing Systems Strategy at Kepler was originally published on ClickZ.

The world of digital marketing is approaching a new normal. Consumer privacy is no longer just a movement to monitor, but one that is reshaping the industry through regulation and action by the tech giants.

Major brands are now coming to realize that the way they organize, invest, think about audiences, and engage with consumers, will be reorganized around people’s privacy preferences – rendering many traditional digital marketing strategies fundamentally different.

Changes to the data privacy landscape

With further regulation coming down the track soon and more walled gardens launching audience solutions with the implicit challenges this creates, huge swathes of audience visibility will be cloaked.

Although identity-secure solutions like Google’s Topics API should bring options to reach the now anonymous users, opt-out rates, and tighter regulation will likely mean a big fall in audience visibility. Brands and agencies need to begin re-organizing and re-tooling their digital capability around a 70/30 privacy-orientated audience split – where 70% of users are opting for increasingly persistent digital anonymity, leaving just 30% of digital users known to a brand still directly targetable.

To successfully navigate this changing environment, brands will need a three-pronged approach to cope with the new realities of privacy.

Three dimensions to deal with data privacy

Build a tech infrastructure capable of maximizing first-party data

Marketers must continue to embrace a data-led approach and build a technical infrastructure that can support this.

Though data privacy is fundamentally changing the way brands can target users, owned data is still a foundational component of an efficient program. As brands consider making use of first-party data, the first and most important consideration brand marketers should ask should be “what” and “why”? That is, “what data do I have access to?” (currently or potentially) and “why might this be valuable to use in marketing?”

The answers to these questions will depend on a variety of factors, including: industry vertical, purchase consideration time, website interactivity/customizability, and customer complexity. However, this evaluation can start to form the basis for how a brand should be composing its infrastructure. The more data a brand can access – and more importantly, how granular that data is as a targeting signal – the more critical it is to invest in enabling fast and flexible utilization of its first-party data.

The ease and scale that pixels and third-party cookies have provided have enabled brands to avoid using many of the internal customer data tools, like CRMs, to send real-time data to marketing platforms. As a result, these tools don’t typically have the connectivity or speed to replace the critical targeting and measurement function pixels have played for many brands.

For a brand planning to make heavy use of first-party data, this should be the next consideration: even if you have the data, do you have sufficient access to it, and an ability to easily port it into platforms where you’re targeting your customers?

On the other hand, brands that don’t have access to large pools of valuable first-party data or the ability to use it for targeting and measurement in near real-time can spare the heavy upfront cost of a new data platform by simply creating an efficient batch audience upload process.

All this amounts to one important point. First-party data is not going to have the same utility for every advertiser, and it is crucial that brands on-board a set of tools that are appropriately scoped to their needs and the data they can access.

Acquiring a large new data platform and treating it as a solution for a lack of first-party data – or first-party data organization in the first place – will amount to a costly misstep.

Build for a cookie-less world

Marketers must build the capability to reach audiences in a cookie-free world and the ability to independently cope with at least three-walled garden audience solutions (and possibly a lot more).

It’s important for brands to consider how the removal of cookies next year will impact the broader organization and marketing efforts. Acquisition (including prospecting and remarketing), retention and reactivation all rely on a media platform being able to specifically differentiate each group from the other. Without cookies available to provide highly pervasive control over these consumer groups, brands will be forced to reconsider this hierarchy so they can appropriately rate the utility provided by various tools and frameworks. Brands will need to consider their strategy for reaching known users differently from their strategy for reaching unknown, anonymous users, and how to evaluate the performance of each strategy effectively.

For example, Google’s Topics API looks to be a potentially viable option for reaching a scalable group of broadly aligned, anonymized users. However, due to the dynamics of the Topics API, it is simultaneously (and intentionally) working against the utility of a deterministic identity framework like LiveRamp’s RampId.

Conversely, where RampId can provide highly deterministic targeting to a fixed set of known users via a Brand’s PII (Personally Identifiable information), this approach does not have the scale potential of Topics API because of the inherent limitation of the size of the brand’s known users.

Ultimately, neither of these approaches fully replace, nor fit neatly into the typical acquisition and retention media groupings noted earlier, and as a result should not be judged directly against one another in terms of their utility. In some respects, this represents a bigger shift mindset than in the effectiveness of digital media, and one that takes focused effort to get right.

A new measurement paradigm

Marketers must create a new measurement paradigm that can make sense of investment across opaque tech sandboxes and a permanently disrupted adtech ecosystem.

At its very core, measurement is as much an exercise in observing relative performance as it is in observing absolute performance. For example, one of the most challenging aspects of measurement in the last two years or so has been the changing amount of underlying data that platforms can access to attribute conversions to ad impressions and clicks, as  data privacy initiatives have continuously reduced the size of data pools.

As a result, advertisers have struggled to make month-over-month and year-over-year interpretations of performance. This is because it is difficult to differentiate between changes driven by marketing campaigns versus by an inherent difference in the baseline percentage of conversions available for attribution in the first place.

New measurement tools bring the potential to mitigate this problem, bringing back a level of stability to the underlying data, in exchange for a lower degree of granularity available in reporting.

For advertisers, this means three things.

  1. First, measurement frameworks that provide increased data privacy bring decreased granularity. Advertisers will need to be more strategic about what events and data they are passing to these measurement frameworks. They should consider prioritizing volume in important measurement events at the cost of having trackability across absolutely every event that a user can make on a site.
  2. Second, advertisers will need to be more capable of reading performance within the universe that a measurement protocol can access. For example, the Chrome Privacy Sandbox framework may be best for measuring the performance of display ads directing to the website in the Chrome browser, while Facebook may be the best place to get performance signals for the ads that run only on Facebook.
  3. Lastly, instead of attempting to stretch these tools across platforms and beyond their capabilities – resulting in undervaluing platforms with less compatibility with a given measurement protocol and overvaluing those with more – brands should also invest in tools like MMMs (Marketing Mix Models) that are designed to provide a cross-channel view but lack the visibility to deliver insight on a daily or weekly basis.

With the privacy-first era fast approaching, the answer is to manage the necessary complexity of systems and approaches that will enable brands to adapt well. Brands and agencies alike need to get a handle on how the role of data in digital marketing is changing and becoming more complex. Re-organizing digital capability to cope with this new reality is a necessity that requires action now.

Read more of Peter's thoughts on navigating the new realities of consumer privacy in digital marketing in MediaPost.

Data privacy is the future of digital marketing: Here's how to adapt

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This article by Peter Rice, AVP, Marketing Systems Strategy at Kepler was originally published on ClickZ.

The world of digital marketing is approaching a new normal. Consumer privacy is no longer just a movement to monitor, but one that is reshaping the industry through regulation and action by the tech giants.

Major brands are now coming to realize that the way they organize, invest, think about audiences, and engage with consumers, will be reorganized around people’s privacy preferences – rendering many traditional digital marketing strategies fundamentally different.

Changes to the data privacy landscape

With further regulation coming down the track soon and more walled gardens launching audience solutions with the implicit challenges this creates, huge swathes of audience visibility will be cloaked.

Although identity-secure solutions like Google’s Topics API should bring options to reach the now anonymous users, opt-out rates, and tighter regulation will likely mean a big fall in audience visibility. Brands and agencies need to begin re-organizing and re-tooling their digital capability around a 70/30 privacy-orientated audience split – where 70% of users are opting for increasingly persistent digital anonymity, leaving just 30% of digital users known to a brand still directly targetable.

To successfully navigate this changing environment, brands will need a three-pronged approach to cope with the new realities of privacy.

Three dimensions to deal with data privacy

Build a tech infrastructure capable of maximizing first-party data

Marketers must continue to embrace a data-led approach and build a technical infrastructure that can support this.

Though data privacy is fundamentally changing the way brands can target users, owned data is still a foundational component of an efficient program. As brands consider making use of first-party data, the first and most important consideration brand marketers should ask should be “what” and “why”? That is, “what data do I have access to?” (currently or potentially) and “why might this be valuable to use in marketing?”

The answers to these questions will depend on a variety of factors, including: industry vertical, purchase consideration time, website interactivity/customizability, and customer complexity. However, this evaluation can start to form the basis for how a brand should be composing its infrastructure. The more data a brand can access – and more importantly, how granular that data is as a targeting signal – the more critical it is to invest in enabling fast and flexible utilization of its first-party data.

The ease and scale that pixels and third-party cookies have provided have enabled brands to avoid using many of the internal customer data tools, like CRMs, to send real-time data to marketing platforms. As a result, these tools don’t typically have the connectivity or speed to replace the critical targeting and measurement function pixels have played for many brands.

For a brand planning to make heavy use of first-party data, this should be the next consideration: even if you have the data, do you have sufficient access to it, and an ability to easily port it into platforms where you’re targeting your customers?

On the other hand, brands that don’t have access to large pools of valuable first-party data or the ability to use it for targeting and measurement in near real-time can spare the heavy upfront cost of a new data platform by simply creating an efficient batch audience upload process.

All this amounts to one important point. First-party data is not going to have the same utility for every advertiser, and it is crucial that brands on-board a set of tools that are appropriately scoped to their needs and the data they can access.

Acquiring a large new data platform and treating it as a solution for a lack of first-party data – or first-party data organization in the first place – will amount to a costly misstep.

Build for a cookie-less world

Marketers must build the capability to reach audiences in a cookie-free world and the ability to independently cope with at least three-walled garden audience solutions (and possibly a lot more).

It’s important for brands to consider how the removal of cookies next year will impact the broader organization and marketing efforts. Acquisition (including prospecting and remarketing), retention and reactivation all rely on a media platform being able to specifically differentiate each group from the other. Without cookies available to provide highly pervasive control over these consumer groups, brands will be forced to reconsider this hierarchy so they can appropriately rate the utility provided by various tools and frameworks. Brands will need to consider their strategy for reaching known users differently from their strategy for reaching unknown, anonymous users, and how to evaluate the performance of each strategy effectively.

For example, Google’s Topics API looks to be a potentially viable option for reaching a scalable group of broadly aligned, anonymized users. However, due to the dynamics of the Topics API, it is simultaneously (and intentionally) working against the utility of a deterministic identity framework like LiveRamp’s RampId.

Conversely, where RampId can provide highly deterministic targeting to a fixed set of known users via a Brand’s PII (Personally Identifiable information), this approach does not have the scale potential of Topics API because of the inherent limitation of the size of the brand’s known users.

Ultimately, neither of these approaches fully replace, nor fit neatly into the typical acquisition and retention media groupings noted earlier, and as a result should not be judged directly against one another in terms of their utility. In some respects, this represents a bigger shift mindset than in the effectiveness of digital media, and one that takes focused effort to get right.

A new measurement paradigm

Marketers must create a new measurement paradigm that can make sense of investment across opaque tech sandboxes and a permanently disrupted adtech ecosystem.

At its very core, measurement is as much an exercise in observing relative performance as it is in observing absolute performance. For example, one of the most challenging aspects of measurement in the last two years or so has been the changing amount of underlying data that platforms can access to attribute conversions to ad impressions and clicks, as  data privacy initiatives have continuously reduced the size of data pools.

As a result, advertisers have struggled to make month-over-month and year-over-year interpretations of performance. This is because it is difficult to differentiate between changes driven by marketing campaigns versus by an inherent difference in the baseline percentage of conversions available for attribution in the first place.

New measurement tools bring the potential to mitigate this problem, bringing back a level of stability to the underlying data, in exchange for a lower degree of granularity available in reporting.

For advertisers, this means three things.

  1. First, measurement frameworks that provide increased data privacy bring decreased granularity. Advertisers will need to be more strategic about what events and data they are passing to these measurement frameworks. They should consider prioritizing volume in important measurement events at the cost of having trackability across absolutely every event that a user can make on a site.
  2. Second, advertisers will need to be more capable of reading performance within the universe that a measurement protocol can access. For example, the Chrome Privacy Sandbox framework may be best for measuring the performance of display ads directing to the website in the Chrome browser, while Facebook may be the best place to get performance signals for the ads that run only on Facebook.
  3. Lastly, instead of attempting to stretch these tools across platforms and beyond their capabilities – resulting in undervaluing platforms with less compatibility with a given measurement protocol and overvaluing those with more – brands should also invest in tools like MMMs (Marketing Mix Models) that are designed to provide a cross-channel view but lack the visibility to deliver insight on a daily or weekly basis.

With the privacy-first era fast approaching, the answer is to manage the necessary complexity of systems and approaches that will enable brands to adapt well. Brands and agencies alike need to get a handle on how the role of data in digital marketing is changing and becoming more complex. Re-organizing digital capability to cope with this new reality is a necessity that requires action now.

Read more of Peter's thoughts on navigating the new realities of consumer privacy in digital marketing in MediaPost.

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