As a digital marketer trying to optimize paid media efforts to maximize online conversions and sales to drive revenue growth, proper attribution is paramount to evaluating your success. Choosing the right attribution model becomes critical for you to get it right, to understand the value of each channel in delivering against your specific business goals.
Attribution, in simple terms, is an exercise of assigning credit to each marketing touchpoint that helped drive a ‘common goal’, which is typically a sale or another form of conversion that takes place online. Traditionally, many advertisers have relied on the last-click attribution model to assign credit to online media. While this is the standard attribution model in some of the most popular web analytics tools available today, it is easy to see why this model is flawed. In today’s connected world, consumers are interacting with brands across multiple devices, channels, and types of media. With last-click attribution; however, only the very last touchpoint before the conversion event ends up getting 100% of the credit.
Without a model that considers the contributions of each touchpoint in the typical online ‘path to conversion,’ you risk overspending in media channels that tend to show up last, like paid search. On the other hand, you end up underutilizing channels that help drive overall conversion, but are not the last touchpoint in the online stack of engagements a consumer has with a brand. This is where cross-channel attribution comes in.
Cross-channel attribution does a better job of reflecting the dynamic purchase path of a customer by assigning proportional credit to each touchpoint, allowing you to make better spending decisions on each channel, tactic or even vendor. Whether the model is rules-based or uses a more sophisticated algorithm, cross-channel attribution involves looking at all the different touchpoints that led to a conversion, and just as importantly, ones that failed to become a conversion. By building a chronology of every touchpoint in a stack and assigning different attributes to each touchpoint, cross-channel attribution strives to measure the weight of each of those interactions and the importance of each attribute in driving the desired outcome.
Whichever cross-channel attribution solution you decide to go with, it is important to remember that it is only as strong as the quality of your data. Bill Muller, CMO of leading cross channel marketing attribution provider Visual IQ, agrees, “When it comes to attribution, both the quantity and quality of data matter. The more data sources used in the attribution equation, the more influences and synergies that can be identified between channels and tactics. At the same time, quality input is the key to quality output. Creating a data collection plan that details the level and type of data required, the frequency and method of collection, and the format the data should be presented are essential to success.”
With that in mind, here are three ways to ensure you are making the most out of the cross-channel attribution solution you choose to adapt:
- Consolidate how you track online media
Since cross-channel attribution involves looking at all of the different touchpoints, you need to ensure all of your online media is tracked using the same method to produce a ‘de-duplicated’ view of interactions and corresponding conversions. One way of doing this is to build a common cookie pool. If you are using an ad server for display media, for example, you can also use the same ad serving platform to track clicks and impressions for all other online media channels including Search, Social, Email and Affiliates. This allows for a 360 view of how your online channels are interacting together to produce the conversion event.
- Maintain a clean taxonomy or naming convention of media placements
You will want to make sure your reporting categories of dimensions are consistent and clean for all of the media placements you track using cross-channel attribution. At the end of the day, the right cross-channel attribution solution will provide a view of what is working within your current media mix and how to optimize campaigns to grow further. Therefore, it is important to align internally beforehand on what reporting dimensions you want to group results by so you can action on the insights it produces. For example, you may want to group results by line of business if you are responsible for multiple business lines or tactics if you want to break out specific prospecting or retargeting line items.
- Understand its potential limitations
As powerful as cross-channel attribution can be, it is important to understand the potential limitations based on the solution you choose. For example, if you are only tracking online media, but your business also drives conversions offline (e.g. a sales team or physical storefronts), you won’t be able to measure impact of cross-channel attribution that goes beyond digital media without the additional layering of marketing mix modelling (or top-down). Additionally, cross-device measurement is an area you should keep in mind as any cookie-based attribution will treat another device as another ID or user, therefore losing the single view of engagements from one individual. There are solutions out there that try to address this by matching statistical IDs between device types, and it may be worth exploring the value of adding this to your attribution modelling.
Implementing a cross-channel attribution solution across your digital marketing team requires commitment and support from within your organization, agency, and/or other external partners. When done correctly, however, it can provide your digital team with a much improved view of how each of your online media channel is truly performing against your objective and how they interact with one another. Furthermore, it can help you understand how your paid media helps drive ‘organic’ conversions (after all, organic conversions have to come from somewhere). Together these insights can inform your future media buying decisions - as part of campaign optimization and media mix modelling - and ultimately improve your ROAS and overall ROI on your marketing dollars moving forward.