With the evolvement of search in form and function, many marketers are faced with the challenge on how to find and make good use of attribution models that work. Unfortunately, understanding the full picture of a multichannel environment is not as easy as it seems.
Obviously, marketers in the business world are faced with several challenges and proper attribution modeling is one of them. Throughout a customer’s decision journey, there are several individual touchpoints along the path that need to be assigned values and attribution is the science behind such.
Solving an attribution problem
Is there really an attribution problem that needs to be solved? A good number of startups and companies are just scratching the surface of multichannel and multi-device attribution. Even the components required to provide a full solution to cover for the lapses of current attribution models are still being pieced together by technology companies. If this is actually a problem, it is sad to know that people are not yet in the know.
Over the years, some incredible progress has been made in the marketing space particularly in the area of attribution modeling. Ultimately, better solutions have been offered to effectively track touchpoints throughout a conversion. Though significant progress has been well-observed in the industry, there are so many companies and business organizations that are yet to fully benefit from the use of these attribution models. Many of these businesses are still making use of models that can only track channels and conversions.
When planning your digital marketing campaigns, there is the need to think more holistically on ways of solving problems. Take the time to examine your analytics data to see if a substantial aspect of your overall conversations has a lengthy multistep path. Simply put, it is your responsibility to check and observe if your prospects are engaging well across multiple channels. You must like to be faced with an attribution issue if most of your conversions are derived from paths with two or more steps.
You can examine the Path Length report yourself by navigating to Conversion in Google Analytics and check the Multi-Channel Funnels Report. From this report, you stand to obtain a clear breakdown of the quantity of paths. You can know the channels that play a vital at each step of your customer’s digital journey by viewing the Top Conversion Paths report. As long as you are not drawing additional conversion data into analytics from offline channels, this report will only concern your digital channels.
When it comes to applying attribution models, it is very expedient for marketers to be aware of the major attribution gaps that can affect their overall outcome. They include
– Cross-device attribution
– Online-to-offline attribution
Measuring consumer interactions and behaviors across devices and screens presents one of the most difficult gaps in attribution. If you are tracking consumers across channels and devices then you are not doing well to know how they engage with your brand across devices. As an advertiser, you need to know how and where they interact with your brand for effective marketing. Find out the device on which your consumers finally convert, as well as the channels they engaged with on each device.
Since consumers are known to employ several devices (such as the smartphone, tablet, desktop, TV, etc.) along the sales cycle or journey, cross-device attribution tends to pose one of the greatest challenges in attribution. No doubt, it’s difficult to track consumer paths while they switch across devices. Whether online or offline, maintain the unique IDs to track customer journeys can prove nearly impossible. Due to the complexity required to effectively track unique users across multiple devices, this is likely going to be the most problematic gap to close.
Today, many marketers are looking to bridge this gap by considering data and searching for correlations between interactions across screens. Though this may not cover for all the regular devices and screens consumers use, however, it is good to know that there are certain companies like Facebook and Apple that close the gap across multiple devices and screens through logged-in states.
As search drives experiences away from the search box, such as voice search through Virtual Reality or Augmented Reality technology and personal digital assistants, there every tendency for the cross-screen multi-channel attribution to get more difficult than it seems. The purpose of attribution still remains unchanged regardless of the chosen attribution model and the existing gaps across all attribution models. It’s all about understanding the value introduced to the marketing mix by each channel necessary for carrying customers along their decision journey.
As marketers, it is important to focus on integrating search into the journey. Your main goal should be established on how to create more holistic campaigns that concentrate mainly on the consumer. Coming from the higher aim of creating a deeper, lasting customer relationship, it may be detracting to tally touchpoints from a rules-based model.
Understanding the impact of the ability of online channels to power offline revenue is obviously the most important gap to identify in attribution. In case you do not know, many analytics platforms out there are only focusing on the digital conversions and revenue thereby providing a partial solution with their attribution models. Without including the online impact of offline in-store, leads, and sales visits, your attribution campaign will surely go wrong.
Based on extrapolating information obtained from available data sources to connect online activity to offline user behavior, online-to-offline attribution is one of the easiest and simplest gaps that can be resolved with moderate accuracy. Many businesses employ some sort of unique promotion code to link attribution together by channels which is an easy solution. While allowing marketers track the conversation, consumers on their own part are also given a choice to convert properly.
Interestingly, Google is using its “In-Store Visits” metric to solve this attribution problem. The metric employs a range of signals to measure online-to-offline impact which includes data, visitor queries, WiFi, GPS, and Google Maps data from numerous opted-in users. With these, store visit estimates can be created. Most advertising platforms and analytics are established to leverage data obtained from smartphones such as GPS, WiFi, and beacons linked to in-app networks.
The online-to-offline attribution question is now been answered by mobile forms of payment like mobile wallets. Though these methods offer a start in the right direction to proffer solution to the online-to-offline gap, they, however, aren’t a perfect solution.