Assisted Conversions & Multi-Channel Attribution
There are a myriad of analytics and metrics that eCommerce, fashion and retail digital marketing teams can track through Google Analytics. Companies need to deep-dive into the granularity of these analytics to understand how, when and why a customer buys. Without that in-depth knowledge, it’s all guesswork, and an inbound marketing strategy can’t work on assumptions. Assisted conversions through multi-channel attribution is one metric most teams ignore, but that must change.
While it's important to monitor a landing page’s bounce rates, time spent on page, click-through rates on advertising, and conversion rates, it’s ultimately what leads up to that conversion that indicates whether a customer’s journey has truly been rewarding. Why? Because it’s all those interactions that eventually lead to a purchase. After all, it’s extremely rare for customers to buy on the first visit. As such, it’s time for digital marketing teams to start tracking assisted conversions through multi-channel attribution.
So, what are assisted conversions? Well, Google defines assisted conversions as “the number (and monetary value) of sales and conversions the channel assisted. If a channel appears anywhere—except as the final interaction—on a conversion path, it is considered an assist for that conversion. The higher these numbers, the more important the assist role of the channel.” However, if that explanation is less than clear, then think of assisted conversions as the number of channels or interactions a customer has with a website before that customer is converted.
Each channel plays a role in the customer’s final decision to buy. Some channels are more important than others. Understanding why helps to determine what to focus on and when. Google Analytics assigns a value based on how a transaction or channel attributed to the conversion. While it might seem confusing, it’s common for certain channel conversion values to have a higher value than the total conversion itself.
Assisted conversions help define the relevance of different channels and allow an inbound marketing team to decipher which interactions or channels are most important for the customer. Google uses “last-click” attribution by applying 100% purchase credit to the last page or media the customer used when buying. Tracking assisted conversions should become a high-priority task moving forward. By doing so, your digital marketing team will be able to assess the effectiveness of your multi-channel strategy.
Understanding the different paths to conversion that customers take will help identify how new customers are converted, when they’re converted and what channels facilitate conversion or offer the best source of information. Consider assisted conversions your ultimate “voice-of-customer” resource. This analytic shows you exactly which channel customers prefer and how many different sessions, pages and channels lead to the customer buying. It’s the sum of the individual parts that lead to conversion, and since today’s customer is all about researching options, it's essential your channels are seamlessly integrated.
Focus on cohesiveness between channels. How will tracking assisted conversions help your business? Do you have a cohesive multi-channel strategy with a seamless message between channels? Or, are each of your channels conveying a different message and offering a disjointed solution? Answering these questions will help you improve each channel while creating a more enjoyable customer journey.
Using a Real-Life Application
Let’s assume you have an unprofitable channel and need to decide whether to upgrade that channel or redesign it all together. First, review that channel’s conversion values before making any decision. You may just find that channel isn’t the final channel the customer converts on, but is still a critical channel during the customer’s research phase.
Second, define whether that channel is driving traffic or diverting it to another channel as you intended. Is that what you wanted for this channel or did you have another purpose in mind?
Third, assess each of the channels one at a time with the same assumptions. Finally, measure your multi-channel strategy as a whole. After reviewing each channel’s performance, and understanding their limitations and values, do you feel your multi-channel strategy helps your customers along their journey? If not, then changes need to be made. Once you've done this, you can move on to using the following variations of models.
Last Interaction Model: Google attributes 100% of the conversion to the last channel the customer interacted with before conversion or purchase.
Last Non-Direct Click Model: This model ignores direct traffic and attributes 100% of the conversion value to the last channel the customer clicked through before buying or converting.
Last AdWords Click Model: This model attributes 100% of the conversion value to the most recent advertisement that the customer clicked on before conversion.
Linear Model: This model gives equal credit to each customer interaction within channels. The Position Based Model is somewhat similar in that it allows you to create a hybrid of the last and first interaction models allowing you to split the credit value between both.
Time Decay Model: This model is more applicable to a short consideration phase, one where the customer quickly makes a purchase or is converted. The Time Decay model has a default half-life of seven days. This means that a customer interaction occurring seven days prior to a conversion will receive half the credit than a customer interaction occurring the same day of conversion.
Get used to tracking assisted conversions. They'll provide your digital marketing team with invaluable information about each of your channels and the overall effectiveness of your multi-channel strategy. Once you get used to tracking that analytic, you can expand that analyses to include the other aforementioned models.
For other helpful Google insights, read our recent blog, Google Testing Expanded Text Headlines for Ads.
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