Marketing Attribution: A Complete Guide

11/22/2022

The customer journey has become more and more complex over time, and this has made it challenging to determine which marketing initiatives, channels, and campaigns are contributing to the bottom line. This is the problem that marketing attribution is meant to solve.

So if you’re looking for a comprehensive guide on all things marketing attribution, you’ve come to the right place. From how it works, to its benefits and challenges, to the different types of attribution models, to best practices… OptiMine has it all mapped out for you, here.

What is Marketing Attribution?

The short definition: marketing attribution is the way advertisers determine how their marketing strategies contribute to sales, conversions, or other business goals.

The long definition: marketing attribution is the process of evaluating the marketing touchpoints a consumer encounters on their path to purchase. It then assigns value or credit to a set of advertisement impressions that contribute to a desired outcome (Example: conversions). So, it is essentially the means by which a customer came to know and buy your product/service.

How Marketing Attribution Works

Marketing attribution and the customer journey graphic

One of the most common approaches to marketing attribution is Multi-Touch Attribution (“MTA”). For MTA to work, a brand must align ad impressions with consumer and device identity data in order to know “who saw which ad” and whether a conversion occurred. Traditionally this was accomplished using cookie data but this method has all but been shut down as a result of browser cookie blocking. Now, a brand must use identity graphs along with their own first party data to attempt to stitch this picture together. Complicating this are major technology industry changes from Apple’s iOS 14.5 update which has blocked a major portion of mobile device tracking and Google’s Privacy Sandbox which will stop all consumer-level targeting and tracking for Google-owned ad networks and the Chrome browser.

Once a consumer’s identity has been matched to an ad, a device, and a purchase transaction, the MTA solution must then compare conversion performance of those customers who’ve seen the ad with those consumers who haven’t, in order to determine whether the ad has generated any true lift. Compounding this complexity is that the MTA solution must also compare sequences of ads seen, keep the identity straight across multiple devices and understand the order of the ads seen, in order to measure the magic combination of ads that leads to the highest conversion lift. Doing this with any level of accuracy requires evaluating billions of comparisons as even a small set of campaigns across channels generates an enormous number of potential sequences and combinations. And this is fraught with accuracy problems when even a small number of conversion identities is mistakenly mis-matched with ads (or not matched at all).

Finally, building a marketing attribution solution requires an enormous amount of data, server-to-server integrations with third parties, the exchange of PII, as well as user-ad level impression data, which is now increasingly difficult to obtain from the walled gardens. The result is typically a lengthy deployment cycle, added costs with external identity data graphs, brittle solutions that are difficult to maintain (or change), and measurement without known accuracy.

Why is Marketing Attribution Important?

There are a variety of reasons why marketing attribution is important. Especially in the current state of economic uncertainty, the pressure and scrutiny of marketing budgets is forcing marketers to truly understand the value of their investments.

Additionally, complex multi-channel marketing requires advanced measurement. Campaigns in one channel impact the performance of other marketing channels, and it is crucial that marketers have the ability to prove the value, ROI and effectiveness of these campaigns, especially upper-funnel channels that don’t have clicks.

Really, brands are looking to move past last-click measurement to understand the value of all channels, which is what marketing attribution is about.

The Benefits of Marketing Attribution

Moving on from Last-Click (or No Measurement at All)

The original, and still often used attribution method, is last-click measurement. By moving to attribution of all channels, including upper-funnel channels with few clicks, a brand can hope to measure the value of these channels regardless of whether there are any clicks at all. This has the potential to value all media more fairly and drive better overall budgeting.

Helps Muster Understanding for Upper-Funnel Marketing

Upper-funnel media such as video, or even traditional media such as TV, radio and print, has no direct click-based engagement, making these investments more difficult to justify. Full marketing attribution measures these channels and more.

Avoids Over-Measurement of Lower-Funnel Marketing Such as Paid Search

The main beneficiary of click-based measurement is lower-funnel media such as paid search. Many other channels have a role to play, as do non-marketing factors such as seasonality or pricing promotions, so lower-funnel efforts shouldn’t get all of the credit. Proper marketing attribution accounts for and evaluates all these factors.

Instills a Focus on Measuring Marketing ROI and Driving Accountability

The hard-dollar value of marketing is often times missing in measurement. By measuring the economic impacts of a campaign, marketers can properly allocate budget and drive better overall performance.

What Makes Marketing Attribution Difficult?

Not Future-Proof

The main challenge that marketing attribution solutions face is that they are not future-proof due to the wave of privacy regulations and other tech industry changes gaining momentum in the market today. These privacy changes are causing Marketing Attribution solutions to suffer significant data gaps and accuracy issues. Plus, new state-by-state privacy regulations are creating major regulatory risks with the handling (and mishandling) of consumer identity data.

Subject to Correlation-Based Biases

When analyzing thew customer journey, Marketing Attribution methods are subject to correlation-based biases. This causes it to look like one event caused another, when that is not actually the case. Many marketing attribution solutions fail to account for non-marketing drivers such as seasonality, weather, economic factors and more. As a result, their measures are highly inaccurate.

The Determined ROI is Often Far from the Real ROI

The determined ROI is often far from the real ROI of any brand because it only considers touchpoint conversions while calculating the return on investment. In reality there are several other contributing factors.

Does Not Account for Offline to Online Effects

Marketing Attribution does not account for offline to online effects, such as a customer seeing a brand’s ad offline and then actually purchasing the product in-store or receiving a brand’s direct mail advertisement and then ordering the actual product online. This is one of Marketing Attribution’s biggest drawbacks as most solutions only measure digital media and online conversions.

How Do You Measure Marketing Attribution?

Measuring marketing attribution involves tracking and analyzing the various touchpoints and interactions a customer has with your brand before making a conversion. First, you’ll need to implement a robust analytics system that can capture data across different channels and platforms. Next, define a clear set of conversion goals, such as purchases, sign-ups, or downloads, and assign a value to each goal. Then, use attribution models (first-touch, last-touch, fractional, algorithmic, etc.) to distribute credit to different touchpoints along the customer journey. Analyze the data to understand which channels and touchpoints are most influential in driving conversions and adjust your marketing strategies accordingly. Regularly monitor and refine your attribution model to adapt to changing customer behavior and market dynamics, ensuring that your marketing efforts remain effective and efficient.

This method of measurement is essentially supposed to allow marketers to define their most successful channels and optimize their omni-channel strategies.

Types of Marketing Attribution Models and Methods

There are many Marketing Attribution models available in the market, from very simple unsophisticated approaches to extremely complex deployments requiring heavy resources and technology. Below is a brief overview of the most common approaches, from simplest to most complex:

Last-Touch Attribution

Last-Touch Attribution is the simplest form of marketing attribution. It assigns full credit for the conversion to the last ad clicked. This is the default approach of free attribution tools within Google Analytics or other web analytics solutions.

The Pros of Last-Touch Attribution:

Last-touch is simple and easy to understand
It doesn’t require any PII
It is easily measured for free and doesn’t require complex software

The Cons of Last-Touch Attribution:

It almost always over-values lower funnel ads such as paid search
It almost always under-values all other media, especially media with low-click rates such as video, display, non-brand search, as well as any media that doesn’t have direct engagement (e.g. clicks)
It makes a poor assumption that only clicks drive purchases, and that other media without clicks does not
It can lead to extremely poor marketing investment decisions that will harm the brand in the long run

First-Touch Attribution

First-Touch Attribution is also a simple form of marketing attribution. It assigns full credit for the conversion to the first ad clicked. This is a common attribution option in free attribution tools within Google Analytics or other web analytics solutions.

The Pros of First-Touch Attribution:

It gives more credit to earlier funnel media, and avoids giving all of the credit to lower funnel media
It doesn’t require any PII
It is easily measured for free and doesn’t require complex software

The Cons of First-Touch Attribution:

It almost always over-values upper funnel ads that have been seen within short windows of time (1-2 weeks before conversion)
Cookie windows and cookie expiration dramatically shorten the measurement window (and potential effects) of longer-term awareness building ads
It relies on clicks thereby ignoring the awareness building effects of ad impressions
It can lead to extremely poor marketing investment decisions that will harm the brand in the long run

Fractional (or Rules-Based) Attribution

Rules-Based Attribution attempts to assign weights, factors or “rules” to give credit to different points in the funnel. While it is noble in its attempt to overcome the weaknesses of more simplistic attribution approaches such as last-touch, the weights or rules can be overly simplistic, or even just flat-out incorrect, which creates more problems than it solves.

The Pros of Rules-Based Attribution:

Rules-Based Attribution tries to address the weaknesses of Last-Touch Attribution by giving more credit to ads that don’t usually get credit
It can lead to more investment in upper-funnel media
It doesn’t require any PII
It is easily measured for free and doesn’t require complex software

The Cons of Rules-Based Attribution:

Most of the weights are arbitrary and are not rooted in any data or evidence
The weights are too simplistic and assign the same credit for channels that likely have significant differences among specific campaigns or ads within them
It is usually highly inaccurate and will lead to extremely poor marketing investment decisions that will harm the brand in the long run

“U” and “W” Shaped Attribution

These Attribution methods also attempt to assign weights, factors or “rules” to give credit to different points in the funnel— usually by assigning more credit to the first and last ads in the sequence. In the “W”, more credit is given to the “mid-funnel” with the assumption that it contributes more too.

The Pros of “U” and “W” Shaped Attribution:

These approaches try to address the weaknesses of Last-Touch Attribution by giving more credit to ads that don’t usually get credit
They can lead to more investment in upper-funnel media by assuming that the first ad “seen” introduces the brand to the consumer
They don’t require any PII
They are easily measured for free and don’t require complex software

The Cons of “U” and “W” Shaped Attribution:

Most of the weights are arbitrary and are not rooted in any data or evidence
The weights are too simplistic and assign the same credit for channels that likely have significant differences among specific campaigns or ads within them
First-touch ads are usually cut off from consideration due to cookie expiration, especially as browsers, ad platforms and mobile operating systems have moved to reduce cookies and cookie lifetimes.
They are usually highly inaccurate and will lead to extremely poor marketing investment decisions that will harm the brand in the long run

Algorithmic Attribution

Algorithmic Attribution is a more complex approach that sometimes uses predictive models and correlations to calculate credit across ad sequences. These computations are more sophisticated than simple rules-based methods and usually require an expensive 3^rd party solution to provide marketing measurement. Also, these approaches frequently move past cookie-based tracking to more complex identity-based tracking schemes.

The Pros of Algorithmic Attribution:

These approaches try to address the weaknesses of more simplistic rules-based methods
A model or algorithm assigns credit as opposed to simplistic methods
These methods attempt to compare ad sequences from customers who’ve seen the ads versus those that haven’t

The Cons of Algorithmic Attribution:

They require the use of PII and the sharing of customer data with external vendors and systems
They suffer accuracy problems with poor customer match rates and identity mis-matches
They require expensive software
They ignore traditional media (unless you buy an even more expensive Marketing Mix Modeling solution add-on)
They ignore non-marketing factors that drive conversions like promotions & discounts, the economy, the effects of the pandemic, weather, competitive factors and many other elements
They are suffering major new gaps due to Apple iOS 14.5, Google’s upcoming FLoC initiative and other consumer data privacy moves in the market
They are not future-proof due to the wave of privacy regulations and other tech industry changes

Marketing Attribution Strategies and Best Practices

Using a marketing attribution solution to its fullest value requires more than just a technology solution. Changes to culture and accountability are required, new decisioning processes must be put in place, and capability management and analytic support are needed for full enterprise success. We explore each of these elements further:

Culture and Accountability

An attribution solution sitting by itself does not create positive marketing change. For real change to occur, leadership is required to guide the team or organization to adopt and drive a change in approach. One key is to ensure decisions are made using the measurement data. Teams must be held accountable to for their use— or lack thereof— of the solution.

New Decisioning Processes

Once an attribution solution delivers the first set of guidance across channels, a new challenge is presented: if the solution advocates taking budget from one channel and allocating it to another, this may put two teams at odds with each other. Decisioning must account for these conflicts and a process must be in place to hold teams accountable for making budget changes. A move to more cross-team collaboration will help navigate these inherent budget allocation challenges.

Capability Management and Analytic Support

Many brands deploy measurement solutions without staffing “owners” to operate and drive the solution. Worse, ownership may reside in one part of the organization without coordination and collaboration with other stakeholders and teams. And when questions arise about the measures themselves, analytic skill and experience is required to coach the organization through analysis, testing, and validation. These are all components of a successful capability management structure and these leads to higher solution success and ROI.

What is the Best Marketing Attribution Model for Your Business?

Selecting the best marketing attribution model for your business requires a thoughtful approach tailored to your specific circumstances. Begin by analyzing your industry, target audience, and the complexity of your customer journey. Consider whether a simple, rules-based model like first-touch or last-touch would suffice, or if a more advanced algorithmic model is needed to capture the nuances of customer interactions. Assess your data availability and quality, as some models may require more data than others to function effectively. Moreover, align the model with your business goals and the customer’s typical path to conversion. Collaborate with your team and stakeholders to gain consensus on the model that best suits your objectives and resources. Keep in mind that it’s often beneficial to employ a combination of models or even experiment with different ones to find the one that provides the most accurate insights into your marketing efforts. Regularly review and refine your chosen attribution model as your business evolves and customer behavior changes. In this way, you can ensure that your attribution model remains a valuable tool for optimizing your marketing strategies.

Marketing Attribution Tools and Software

Like any marketing measurement approach, there are many considerations to keep in mind as you seek the best tool for the job at hand. With marketing attribution, there are some serious challenges to keep front and center, whether you already have an attribution solution deployed or are looking to implement a new one:

Data loss
Privacy
Cost

For a more in-depth breakdown of how to select the best marketing attribution solution for your brand, read OptiMine’s “How to Select the Best Marketing Attribution Tool” blog post.

See What OptiMine Can Do for YOU!

We are currently in an era of privacy-driven marketing measurement disruption. However, OptiMine’s marketing attribution and optimization solution does not rely on PII, cookies, tracking pixels, or any other identity data, and will not be impacted by any of the privacy regulations or privacy related technology changes now nor in the future.

OptiMine’s solution is 100% future-proof—and the time to future-proof your measurement is NOW. OptiMine’s deeply experienced team can guide you and your organization through the change, solution adoption and analytic support to achieve greater success.

Interested in learning more about how OptiMine’s solution can help you? Contact us today!