A customer today goes through an entire online journey- before they make a purchase from your brand, they may encounter several types of communication and ads from you along the way to conversion. Marketers aim to determine what actions or elements impact purchasers' decisions, and attribution models are a key part of that.
An attribution model lets you specify how much credit you give each interaction. You can optimize the conversion journey with the help of an attribution model, which will provide better clarity on how each acquisition channel performs.
Since Apple's iOS 14 changes and a few other updates in the performance marketing world, we have seen data accuracy issues go up significantly. Many of our customers have reported issues such as the total orders or revenue reported by Google and Facebook Ads being more than the revenue/ orders seen by them from the website information.
Does it mean that they can't rely on numbers reported by Google and Facebook?
If the numbers from Google and Facebook are more than the actual numbers, then does it mean that the efforts put in by us on organic channels or other inorganic channels are not yielding fruitful results?
Graas is addressing these questions through its attribution models. An attribution model is a collection of rules that together determine how much credit each marketing channel gets for a conversion. There are various attribution models available which can be used based on your specific use case.
Before actually purchasing an item from your website, customers can visit your website from various channels. For example, one customer may follow this chain:
Facebook Ad - Abandoned cart email - SEO - Direct
and someone else may have followed this pattern:
Google Ad - Whatsapp marketing
Depending on the product category and Average Order Value for your brand, generally, most customers take anywhere from 3 days to 30 days and visit 2 times to 15 times before making the final decision of purchasing from your website.
So, it is very important for you to follow their journey and draw conclusions on what works best for you by using attribution models.
With Graas' help, you will be able to see the distribution of each marketing channel’s impact on your final sale. This will subsequently help you make decisions such as:
How much budget should I assign to Google vs. Facebook?
Are my SEO efforts giving positive results?
Should I focus on email marketing or Facebook for my retargeting efforts?
What % of conversions were influenced by the social media post we had created?
Which channel works best for pushing the customers to make the purchase decision?
Let's take a look at the different types of attribution models:
4. Linear Attribution Model
By analyzing each attribution model, you can get a better idea of the ROI for each marketing channel.
A single model is not applicable in all business cases. If the logistics business of your friend is fit for the time-decay model, then your brand cannot also follow the same. It is variable with your case history. You can either choose to look at one that works best according to you or look at a combination of models and arrive at conclusions.
Last Click (Non-Direct)
The Last Click (Non-Direct) Model is more helpful than standard tracking. 100% of the value is assigned to a single interaction. Any straightforward and 'direct' connections that occur right before the conversion are deleted with the last non-direct click.
When someone comes to your site directly by actively typing in your URL or clicking a saved bookmark link, it shows they are already familiar with your brand.
How did they learn about your brand? What is the x-factor that encourages or pushes them to go straight to your website? When you eliminate direct traffic from a last-click model, you can assign more value to marketing channels that lead to conversions.
Since all direct clicks are eliminated, this proves to be a more insightful model than the last interaction. However, it still assigns 100% of the value to one interaction. If a customer has 4 touchpoints before that final or last non-direct click, it is entirely ignored.
Last Click (Inorganic)
Last Click (Inorganic) is very similar to the Last Click (Non-Direct) attribution system. This model considers only Inorganic sources instead of considering all Non-Direct sources. This way, you can limit the attribution to only those channels where you are spending money to acquire users. This helps you to give maximum credit to inorganic sources.
First Click
The first click is similar to the Last click in that it gives 100% of the credit to one single click. First-Click gives all of the credit for a conversion to your brands' first interaction with the customer.
For example, if a consumer discovers your trade or business on Instagram, it receives full credit for any transaction that occurs as a result of that encounter.
It makes no difference if a buyer found you on Instagram, then clicked a display ad a week later, and then went straight to your website. In this case, Instagram is given full credit.
The simplicity and straightforwardness of adopting First Interaction attribution is its key appeal. However, this model has limitations; it excludes the impact of any later-appearing, potentially essential marketing channels, such as retargeting ads.
The first interaction is a fantastic technique for analyzing each channel if your main business aim is to bring in new top-of-the-funnel clients.
Linear Attribution Model
With a Linear attribution model, the credit for a conversion is split equally between marketing channels.
For instance, a customer finds you on Instagram, signs up for your email list and later clicks an email link. The next week they go to your site directly and make an $150 purchase.
There are 3 touchpoints in this situation. Each touchpoint gets equal credit of 33% or an $50 conversion value attributed to the channel when the purchase was made, in this case.
In comparison to a single-event attribution model, linear attribution provides a more balanced view of your entire marketing plan.
However, some marketing strategies are more effective than others, and this model will not highlight the most effective strategies.
Time Decay Attribution:
As with linear attribution, time decay attribution spreads out the value across multiple events. Unlike linear attribution, however, the Time Decay model considers when each touchpoint occurred. The time decay model is used to assess the entire conversion route, but as touchpoints approach closer to a conversion, they are given weighted credit.
When compared to a last-touch or last-click model, temporal decay more accurately depicts how all touchpoints contributed to a conversion, which may be more representative of how customers interact with and analyze ads as they approach closer to converting.
Interactions that take place closer to the time of purchase are given more weight and value. The initial interaction will receive the least amount of credit, while the last interaction will receive the most.
Attribution models can be very effective, or grossly ineffective, based on how they are applied to each context. For your retail brand, it is important that you consider which attribution model makes the most sense. For example, a time-decay model would be best suited to impulsive purchases, while the linear model would be more relevant for brands that depend heavily on content marketing.
Applying the right attribution model can guide your decisions on which marketing channels you should spend more time, money, and effort on.