Cross-channel attribution can be a powerful marketing technique if it is implemented correctly.
When implemented poorly, however, many consider attribution to be more of a headache than it is worth. This is unfortunate, as attribution can be a very powerful tool for companies seeking to expand their reach and improve the effectiveness of their overall marketing tactics.
Because of the significant difference in performance based on how cross-channel attribution is implemented, some marketers still shy away from using it in any large scale. Given the potential for success when using attribution-marketing techniques there are definite advantages to pursuing attribution-marketing strategies and implementing full-scale cross-channel attribution for your organization. However, it is vital that you take the time to implement it properly.
How attribution marketing works
Instead of focusing on merely the act of converting leads, attribution looks at the factors that influence a consumer’s decision to purchase.
Beyond just the “what” of these points of influence, it also takes into account other external factors such as the context in which a factor is most influential when it exerts its influence and to what extent the point of influence actually influenced the decision. By collecting data on these points of influence, marketers can tailor ads to take optimal advantage of the way that these events influence consumer spending and commitment habits.
This can be particularly useful when evaluating new digital platforms as potential hosts for advertising. Attribution data can be used to determine how appealing the platform might be to the ad campaign’s target audience and how successful the campaign might be on the platform based on the presence or absence of points of influence. Attribution data collected over the course of an ad campaign may also be used to help plan the next campaign to make it more effective.
Common attribution pitfalls
While there is no one single reason for attribution-based campaigns to go wrong, there are usually a few common errors that marketers make when planning these campaigns out.
The most frequent of these mistakes include these:
- Instead of basing the attributions on a single pool of data collected from across multiple channels, attributions are made on a per-channel basis using data from multiple different sources.
- Instead of developing an attribution plan that accounts for every channel that your organization utilizes, the plan was developed using data from only certain channels (either accidentally or by design).
- When the attribution plan is implemented, a means of cross-device tracking hasn’t been put in place to keep track of data across multiple user devices.
- The marketing plan that utilizes attribution data functions on a cycle that’s out of sync with your tracked sales cycle, skewing the resultant data.
There may be other causes for attribution errors as well, such as using out-of-date data or restricting data to only what is relevant to certain demographics.
Getting cross-channel attribution right
If you want to develop a full-scale cross-channel attribution plan and have it succeed in the enterprise sector, make sure that you are prepared to implement it properly.
You will need an analytics platform in place to collect data and build attribution models. Marketing tools that are capable of using this data and implementing the campaign you desire are also necessary. Be sure to include a way to not only collect data across all of your channels but also to combine it for overall analysis.
Another key factor to cross-channel attribution is figuring out how the data will be viewed once it is collected from your channels. Determine how you would like to segment the data (by product, by product line, by price point, etc) and make sure that your data model has the necessary information to accomplish this.
If necessary, don’t be afraid to bring in an attribution-marketing firm or other specialist who can take care of the design and implementation of your attribution plan for you. These specialists often have years of experience working with attribution data specifically and can advise you on uses and implementations of the attribution approach that you might not have considered.