Navigating the evolving landscape of targeted advertising and marketing measurement

The recent developments in data availability for targeted advertising and marketing measurement have been significant. It is key to understand the different stages of human reaction to fundamental change. The ‘Change Curve’ model, developed by Elisabeth Kubler-Ross, provides a useful framework for conceptualizing the stages of response to change, from shock and denial to acceptance. As we navigate this evolving landscape, it is essential to remain aware of the industry’s movement towards a new standard for the appropriate and fair use of consumer data in advertising.

Shock

There is no denying that the digital advertising and data processing industries have undergone significant disruption in recent years. The implementation of regulatory and technological changes has resulted in a series of systemic shocks, fundamentally altering the approaches to target, measure, and attribute advertising. Specifically, the technologies and identification methods, such as Double click IDs and third-party cookies the industry had come to rely on have been depreciated.

This, coupled with a growing public awareness and concern for digital privacy, has led to the undermining of the already questionable feasibility of comprehensive attribution throughout the customer acquisition journey. This (Read more...) of transition has left the industry navigating the stages of change as it adapts to this new reality.

Denial

Traditionally, marketers often use ad-platform tools to measure performance because they’re free and easy to use. But these tools have some downsides when it comes to accurately measuring cross-channel marketing efforts. For example, they mostly just measure the platform’s own media, which raises concerns about bias and lack of incentive for the platform to tell marketers when to stop spending.

Additionally, these tools tend to over-index on attribution of credit to marketing touchpoints that they can see and prove, leading to an overestimation of their contribution. It is widely acknowledged in the industry that using platform tools should be used as context and not as the sole tool for attribution and optimization. However, many in the industry remain in denial of this fact, particularly in less innovative agencies who are accustomed to using these tools despite their limitations.

Brands must consider if their interests are truly aligned with those of their agency and platform partners when making channel spend allocation decisions, incentivize based on measurable goals that align with their brand’s strategy, and properly address any resistance to change.

Bargaining

Unified ID is getting a lot of attention lately with various initiatives in play and support from organizations like the IAB. The goal is to have a shared ID for the independent web for targeting and measuring in a post-cookie world. But it is also seen as a way to handle the end of third-party cookies.

Unified ID is kind of like a band-aid solution. We can’t use cookies anymore, so now we’re trying to use hashed emails instead. Both are just strings of characters that let us follow people around the web. The proponents of Unified ID say that people have given their consent, but did they really know what they agreed to? Sharing data with a brand you have a relationship with is one thing, but sharing it across the whole network? That’s a big difference.

As more people become aware of data privacy, there will be more pressure from regulators to make sure these IDs are used responsibly. And, even if it does work, it still won’t solve the problem of fragmentation. With big ad platforms keeping their data to themselves, we’re still left with a fragmented web.

In the end, Unified ID is a good idea for targeting ads to a big audience, but not for measuring and tracking them.

Depression

With cookies gone and the recent changes to Facebook Attribution, it’s normal to feel worried about spending marketing budget effectively.

The changes brought about by iOS14/ATT have affected data availability and look-back windows for those using Facebook Attribution. It is important to consider how to effectively allocate marketing budget in a post-third party cookie world without resorting to simplistic heuristics. The use of technology and science can still help optimize spending, but it may require a shift in thinking and approach to achieve our goals.

Acceptance

The current state of the world is vastly different from what it was a few years ago, with the pandemic accelerating existing trends. It is unlikely that society will return to its previous state, but certain aspects may be retained. Will the consumer attitudes towards the collection and processing of their data also shift? It is unlikely, not to mention undesirable, that they will revert to their previous attitudes. Consumers may be willing to provide their data in exchange for a benefit, but currently, the conversation raises ethical concerns, and it is not appropriate to seek regressive solutions.

What we need is a re-evaluation to the approach to consumer data and privacy and accept that there is some data that can be used for targeting and measuring advertising and some that should not be used. It is imperative to create new solutions and technologies that are suitable for the present world, instead of replicating past practices.

Levelling Up

There is a significant amount of innovation taking place across the industry, with forward-thinking vendors and agencies developing solutions that prioritize privacy. This is not only beneficial for consumers but also for businesses and brands. By focusing on first-party data and utilizing it to understand customers and their journey, vendors and brands can address their key challenges without the risk of facing repercussions from regulators or large advertising companies. By taking this approach, you’ll also dodge any potential harm to your reputation that might come with using data of questionable origin. We’ve seen this be a common problem in recent years, but with this approach, you’ll steer clear of any drama!

Additionally, by being conscious and strategic about utilizing other available datasets, it is possible to measure the effectiveness of advertising while still adhering to privacy regulations. A new wave of forward-looking Adtech/Martech companies that are aligned with the emerging data settlement of the 2020s are not only presenting great survival instinct but thriving during the rapid growth of ecommerce and digital competition. By levelling up industry practices and reputations while delivering value to clients, it is possible to shape a positive trajectory for the industry.

In conclusion

The Change Curve model is a useful tool for marketers to understand the behavioral triggers that occur when individuals are faced with change. This model outlines the typical stages that individuals go through when they experience change, including denial, resistance, exploration, and eventually, acceptance. By understanding these stages, marketers can anticipate the various reactions that consumers may have to changes in the advertising industry, such as the shift towards the appropriate and fair use of consumer data.

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Jamie Bolton is a ClickZ Advisory Board Member and head of Growth at Fospha, a leading marketing measurement platform for ecommerce.