Definition
The practice of using advanced statistical approaches to allocate proportional credit to marketing communications and media activity across all channels, which ultimately leads to the desired customer action.
This is the definition from "The Forrester Wave: Cross-Channel Attribution Providers, Q4 2014 report" that can be accessed here.
Importance
It is important for marketing and digital teams to understand which campaigns or channels are more effective in goal conversion. Investing in the right initiatives is becoming more important as companies are starting to focus on ROI for any customer initiatives.
However, with the multiplication of channels - digital and offline, increase in screens , increase in digital products - It is no longer easy to understand how users fulfill their objectives or if they do.
Variations
Multi-channel attribution could mean several things. There are some more popular variations. These are shamelessly copied from here.
Multi-Channel Attribution: Online to store
This variation refers to how the online channels impact the offline activity of the customer / user. For a retailer, this is typically the store walk-in that is as a result of a digital activity from the user.
Measuring how various channels help conversion to the offline activity is very important.
Multi-Channel Attribution: Across multiple screens
With the number of screens that an average user uses increasing - tablet, desktop, mobile, TV) - It is increasingly common that the user's journey is from one screen to the other before it translates to a specific action.
With this, it is becoming increasingly difficult to users progress , unless they are signed in. Most of the times, the interactions might not really need the user to be logged in, making it tough to track.
Multi-Channel Attribution: Across digital channels
With any organization, the number of digital channels that are used as a customer touch point is increasing. Be it from google search to paid ad to digital channels, companies have started finding more touch points in the customer journey from discovery to browse with aspects of interaction, engagement and reflection.
All the existing analytic tools are looking at last-click conversion which measure which digital channel was responsible for conversion. We should go beyond that and look at the path the customer used for a specific interaction.
The measurement of which channel attributed to what percentage of user interaction is still up for debate with various modelling that help marketers find that out.
Decision Making
With all these variations, it becomes very important to understand , as an organization, where do we want to focus our effort.
For example, if we want to target a specific user segment or a specific user journey, Can we choose one or more variations of Multi-channel attribution and choose the right set of models to measure and draw inferences from the report.
It is also important to note that statistics is not going to reveal causation.
Correlation does not mean causation
It is also important to note that the only way out is to be able to experiment and learn from the data. With the pace of technology and user preferences, it is not possible to invest in too much marketing research or technology to try and figure this out.
We need to experiment , collect data and learn faster. The decisions that we take from some of the inferences could be the only way to define causation. Some of these decisions cannot be replicated even if there are the same set of data. This is because it is not possible to measure all aspects of the user's interaction.
Build incrementally with fast, integrated learning cycles (SAFe agile principle)
Conclusion
The topic of multi-channel attribution has been in the lime-light of marketers for the last 2 years and has now strongly come into the area of digital strategy.
With the ever-evolving digital space, organizations would have to move faster to understand the space and make smaller bets to learn and provide value to customers.
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