Google Analytics Multi-Channel Attribution
Most businesses use Google Analytics to keep tabs on their multi-channel attribution data. Among the several attribution models available from Google are:
Last Interaction: Conversion value model based on the customer’s last touchpoint with your company.
Last Non-Direct Click: The last non-direct click model gives full credit for a conversion to the last channel used, regardless of whether or not that channel was used during the session.
Last Google Ads Click: A model that places a premium on the last Google ad a user interacted with before making a purchase.
First Interaction: Model in which a customer’s first touchpoint with your brands, such as a social network page or a Google ad, is solely accountable for the sale.
Linear: Each customer interaction point with your company on the way to conversion is weighted the same under the linear model.
Time Decay: Time decay is a model that rewards the sites of contact geographically closest to the conversion point.
Best Methodology For Attributing Sales Across Several Channels
Multi-channel attribution models considering linear and temporal decay provide businesses with a more comprehensive view of customer purchasing. If you desire a deeper dive into the decision-making process of your target market, these models will be more illuminating.
Since they focus on just one channel or point of contact with the consumer, the other Google attribution models cannot be considered “multi-attribution” conversion models.
Several factors will determine the best attribution model for tracking your advertising performance. Consider how much time and money you will put into marketing and how you communicate with your target audience.
Before choosing between multi-channel attribution strategies like the linear and temporal decay methodologies, it is vital to establish the relevance of time to your conversions. Businesses that have to wait longer to close a deal might benefit from the time decay model since customer interactions closer to the moment of conversion tend to have a higher impact on the customer’s final decision. If you’re investing money in sales enablement, this is especially true.
Attribution Models Categories
You can derive several benefits from your extensive network of promotional avenues. The following categories can be used to classify these models, which are also known as attribution models:
1. Linear Attribution
In the linear attribution model, each touchpoint along the way is assigned the same importance. Here, a change is triggered with a score of five. Thus, the value of a conversion would be divided equally across the touchpoints, with each receiving 20%.
2. Falling Attribution
With the falling attribution model, the emphasis is placed on the most recent contacts with the client. If their previous interactions had been good, why did they wait until now to make a purchase? The most recent action would account for 40% of the total value.
In the next engagement, the percentage would drop, and so on, down to the first meeting, which would only receive 1% or 2%.
3. Positional Attribution
The positional model takes a more nuanced approach, assigning a relatively high value to the initial encounter but also giving considerable weight to the subsequent contacts.
Since no single model can adequately describe all possible phenomena, there are many models to choose from. Considering that customers have varying degrees of familiarity with various brands, websites, products, and services, one engagement model may be more beneficial to your company.
Most businesses succeed most with position-based or fading models because they better allocate value to the highest-value clicks. However, the most successful companies using multi-channel attribution analysis create their unique models.
4. Unique Models
You may develop a one-of-a-kind attribution model based on your knowledge of conversion pathways. It takes all the data it collects and calculates a % number for each action, channel, and interaction.
This model is the most certain approach, but it requires a deep understanding of how your various marketing channels affect the customer’s path to purchase.
Starting with one of the examples given above is a good idea. After collecting enough data on conversions and user interactions across all your marketing channels, your data analysts may decide to modify or develop a new model.
Multi-Channel Attribution Is A Way To Go
For a long time, businesses have failed to see the value of allocating a portion of their digital marketing budget toward non-financial objectives like raising brand recognition or educating customers. Although it is possible to gauge consumers’ familiarity with and involvement with a brand, it hasn’t proven easy to connect these efforts’ worth to monetary gains directly.
Adopting multi-channel attribution models and technology has made it easier and more measurable to allocate resources toward campaigns that aim to raise brand awareness and encourage consumer participation.
