Attribution no longer works as it did. Irrespective of the Google delay, Apple’s iOS changes and other browsers already limit tracking and measurement at an individual level.
While some of today’s challenges are new, it has always been that as the market changes, data comes in and out of availability.
We can still measure the impact of Facebook, Google or Tik Tok advertising, but attribution is, and always has been, based on an incomplete picture. And while granularity is still important, the granularity we had from attribution is lost. There is no magic solution to replacing it and chasing it is not the way forward.
The question then, is, where is the value in my measurement programme? What impact can I have and is what I am doing enough to influence a return? A question not just of what we measure, but why we measure it.
That means employing a range of statistical, business analysis and consulting techniques through a common framework, ensuring the best tool is used for the job in hand, but crucially, in an integrated fashion.
It also means ensuring the right skillsets are available. Instead of relying only on statisticians and econometricians, it is now critical to ensure data architects and engineers are involved to deliver insight at speed and the right levels of granularity. As well as having the right data science squad, business leaders need to be able to interpret and understand what the data is telling them in order to act upon it. This may come from upskilling themselves or ensuring they have good ‘translators’ in the team, who can act as the bridge between the business and data science – both would be ideal.
Holistic media measurement, such as Marketing Mix Modelling, is complex, requires data from many sources and only delivers a certain level of depth. This, when faced with the easy availability of digital data, generated an industry in analysing it to deliver instant returns, often at the expense of the bigger picture, either in attention or value. The result of which has been an over-emphasis on digital channels with the understanding of the genuine influences on customer behaviour de-prioritised.
The growth in walled gardens quickly limited deterministic visibility across different systems, denuding further the opportunity to use digital data expansively. Plus, ‘in the path’ doesn’t always mean impacting the path, and attribution misses a whole eco-system of other drivers of consumer behaviour. Attribution without understanding this risk has almost certainly led to mis-attribution. What’s more, it is impossible to build long-term brand measurement into path to purchase measurement.
More widely, many businesses are now faced with telling their finance teams that what they were saying they were getting from attribution isn’t actually the full picture. And with it, the need to move from an (apparent) detailed understanding of performance, with an unknown value associated with brand, to understanding marketing at every stage of the funnel.
Plus new systems arrive all of the time. Meaning large-scale, lengthy data infrastructure development programmes have to shift with them. Not only does this significantly hamper fast turnaround, and, importantly, reliable insights that can deliver real business benefit, the programme often becomes obsolete, and the cost sunk along with the opportunity.
We’ve been trapped in an ever-decreasing world of measurable digital that has narrowed opportunities. A different approach is needed.
So, what should we measure, how should we measure it and how should it be emphasised?
Very granular measurement allows you to make very granular decisions, which is useful when it works, but can take away from the broader strategic decisions. For example, figuring out where to put creative needs to start at the high level of optimising the whole budget. Then you can use granularity to make sure that every penny is efficient, having made sure you’re not wasting large pots of budget that can be used to better effect elsewhere.
That means starting with a holistic vision and using the complete view of measurement to underly the more granular view, so that when you want to measure things like creative testing or campaign efficiency, you have a credible starting point that makes the ROIs and impacts of the specialised components much more usable and stable when new data sources are introduced.
Further, it’s important to look beyond marketing activity at what is driving business. Marketing can account for driving business 5-40% of the time, which means 60-95% of the time, sales aren’t driven by marketing. Being able to quantify this is critical.
Finally, it’s essential that measurement is usable and can be translated to decision-making. Having robust and stable predictive models is critical to turning that into prescriptive and quantified recommendations. Understanding the structure of your business’ market place, its place in the market, and your customer, allows you to be more reactive as you can see the fundamental shifts in the things that impact your business outside of marketing, and react to them as they change and evolve.
Ekimetrics’ approach is to use econometrics at the core of measurement, which is then the integration point of other analyses to deliver a unified measurement solution.
This approach, “OneVision”, allows you to answer specific questions and take deep dives into specific channels, for example with Facebook or Google’s attribution system and deterministic data from within their environment, or your own customer data or first party partnerships with other publishers, all integrated within the common framework.
This framework, with a system of integrated solutions, delivers a far more valuable and strategic approach to marketing measurement that takes account of all aspects of marketing spend, to drive a complete understanding of ROI that can drive budget allocation across countries, channels, categories, media or other important delineations for a specific business.
Critical to any solution is an approach that is embedded right across the business. The advantage is that everyone across the business is speaking the same language and sourcing insight that informs decisions from the same analytical platform.
Ekimetrics takes a “Useful, Usable, Used” approach to industrialisation. Not only does this ensure alignment to the same measurement system, it also facilitates agile decision-making both at a strategic level and when looking at the newest and most difficult questions.
There are three key pillars to successful measurement in a cookieless world: Econometrics, Attribution, Test & Control.
Econometrics captures the full range of business drivers as an integration core for the measurement approach. The integration of walled garden attribution solutions allows for the opportunity to dig deep into the granularity and make granular decisions about campaigns, while bridging the gap between the buying options and econometrics-led measurement.
Using Test & Control means you can identify causal impacts through experiments and really understand true incrementality.
This combination of methods within the common framework allows brands to support decisions from strategy to tactics, budget planning and execution.
Understanding your key decision moments is not about the day-to-day performance but where performance sits overall, within the context of:
All of which enables strategic change through cookie-agnostic measurement.
To capitalise on the opportunity for change:
Assess and audit your data capabilities
Are you able to access holistic measurement now? How often? How can you get to the right level of data? What are the process changes that are needed?
Define decision moments
What is the right level of granularity for the decision you are making? Are they the right decisions?
Build cross-functional governance
Whatever your measurement solution, does it have the backing of those who control budgets? What about finance? How can you get access to the data you need through IT partners or third parties?
Measure the measurement
Are you able to see that you are creating an impact and return, rather than validating what has gone before?
Deep dive agility
How easily can you answer new questions or take a closer look at the different levers impacting channels or campaigns?
Build data science squads, don’t hire profiles
The world of data science requires a host of technical skills, from data architects, engineers and wranglers, to analysts and econometricians. Have you got the breadth of skills you need?
Tech is an enabler, don’t overcomplicate it
Are you looking at long time scales before you can make use of data? Can you take a more incremental approach to delivering benefit along the way with complete, if imperfect in granularity, solutions?
In summary, the best marketing measurement never has been all about digital attribution. The deprecation of the third-party cookie is a real opportunity to re-evaluate measurement and embrace a more rounded, strategic approach.
For more on this topic, contact Matt Andrew, Ekimetrics’ Partner and UK MD, email@example.com.