What your customers come across before they make a purchase is perhaps the most important thing you need to know about them.
How did they find you? Where did they find you? When did they find you?
You need answers so that you can evaluate your marketing strategies and grow from there.
This is where marketing attribution models come in. They help you view the touchpoints that influenced people to convert and assign a different amount of value to certain interactions.
Some marketing attribution models only credit a single interaction the customer had with your company for the wholesale. This may simplify things a lot, but sadly it’s not how reality works.
A customer’s opinion of your business is affected by more than one interaction and each deserves at least some credit.
This brings us to the focus of this article: multi-channel attribution.
What is multi channel attribution?
Before a customer makes a purchase from your business or even considers making a purchase, they come across several influence points.
Marketing attribution is made up of many different models that assign value to all these points that customers interact with before a sale.
Multi-channel attribution is a subset of marketing attribution and it acknowledges that multiple channels have an impact on customers’ purchasing decisions.
Although there are several different types of multi-channel attribution, each one provides visibility to the success of each interaction while helping you see which channels acquire high-quality leads and will end up driving more revenue.
Each different model allocates appropriate values to each touchpoint based on its contribution to the conversion of the customer.
And it is important to realize that there is no one correct or best model to use. They all have their benefits and flaws. The key is to find the one that fits best for your company and will help you the most with your marketing.
Why is multi channel attribution important?
Multi-channel attribution models are different than others because they recognize that digital marketing is a complicated process and it takes more than one interaction to cause a conversion.
It helps you see your most effective marketing channels without ignoring that each touchpoint along the conversion process has an influence on people.
Most company leaders want to learn
- how many new opportunities marketing creates,
- which channels are the most beneficial and contribute most ROI,
- and how to allocate the budget for most efficient results.
With the feedback multi-channel attribution models provide you, you get the answers to those questions as well as how many conversions are made and which channels acquire the most leads.
What are the most often used multi channel attribution models?
As I mentioned before, there isn’t one perfect attribution model that works for everyone. There are several ones and you just need to find the one that works best for your business.
There are three multi-channel attribution models:
- Time-Decay Attribution
- Linear Attribution
- Position-Based Attribution
Let’s have a closer look at each one of them and their pros and cons.
A time-decay attribution model assigns more credit to interactions as they get closer to the time of the sale or conversion.
The last touchpoint gets the highest amount of credit while the first one gets the least amount.
Pros and Cons of Time-Decay Attribution
If you work in an industry with long sales cycles and relationship building is at the heart of your sales, this model can work really well for you.
However if you focus more on top-of-the-funnel conversions and if your sales process is not too long, this model may not work as well for you.
With a linear attribution model, all of the credit for the conversion or sale is distributed equally to each interaction made between your customer and your business.
If there were four touchpoints until the customer decided on making a purchase, each one is responsible of 25% of the value.
Pros and Cons of Linear Attribution
This is a great model to see every single channel and credit all of them, however it is not so efficient if you want to see which ones might have had a bigger influence on your leads.
This model is also known as the “u-shaped attribution model” and is a model that assigns specifically higher values to the first and last interactions.
The first touchpoint a customer has with your business is their first impression of you and the last one is the final action that promotes sales.
They are both significant and each get 40% of the credit with this model. The 20% that’s left is distributed equally among any other interactions made in between these two.
Pros and Cons of Position-Based Attribution
This model allows you to credit each channel customers come across during their conversion process and also highlights the two most important ones.
However, it allocates the same amount of value to each interaction in between the first and last. This may not always be the reality.
Common Challenges & Mistakes when using a multi channel attribution model
Not many marketers are able to fully look at all of their digital channels at once and collect convenient data that will lead to constructive improvements.
There are a few common obstacles almost every marketing team comes across when it comes to multi-channel attribution. Let’s have a closer look at what does challenges are.
The digital marketplace has become a huge part of marketing, however, it still isn’t all of it. There are many people who rely on face-to-face communication or phone calls before purchasing. Especially in industries like automotive, dental, legal, or real estate; offline attribution outperforms its online counterparts.
Most marketers are not able to bring together both online and offline touchpoints and analyze them together to create full comprehension of all marketing channels, despite being fully aware of the effects of both types of channels.
No matter how good you are at tracking online interactions, if you cannot bring them together with offline touchpoints, you will end up with inconsistent attribution data.
For example, with Google Analytics you can track online touchpoints successfully, but you will not be able to record any offline interactions, whether if they are phone calls or face-to-face meetings.
So, if a significant portion of your sales depends on one offline conversion, this online-to-offline attribution can create a distortion in your results and may affect your future marketing decisions and budget allocations negatively.
90-Day attribution window
Many analytics tools provide up to a 90-day look-back option. This means that you can’t reach any data that goes back more than three months.
For some companies, this may not be a problem at all, but if you rely on long sales cycles and complicated conversion processes, this might be an issue.
Full customer understanding isn’t only about considering all of the marketing channels, it is also about considering the entire path a customer takes to make a purchase.
Lack of conversion data
Not every lead brings the same revenue. It is important to realize that because most analytics tools will only tell you what channel caused what conversion, but they cannot tell you which one brings in more revenue.
Each different source, interaction, and channel acquire different types of customers and therefore different lifetime values and revenues.
So it might seem like you get the highest number of acquisitions from Google display ads, and this may lead you to pour in more money to that while actually, customers with higher revenues come from social media posts. That means that social media contributes the most to your ROI and it will be more beneficial to allocate more money for that channel.
Businesses need to know how customers found their companies and which channels lead them to make a purchase. Marketing attribution helps with that.
It consists of several different models that give certain amounts of credit to each interaction a person has had before purchasing.
Some models only credit a single touchpoint, but in this article, we focused on multi-channel attribution models —which acknowledge the significance of each interaction and give credit to all of them.
There are three main multi-channel attribution models:
- Time-Decay Attribution Model: The closer the interaction is to the time of the purchase, the more credit it gets.
- Linear Attribution Model: Each touchpoint gets the same amount of credit.
- Position-Based Attribution Model: The first and the last interaction gets 40% of the credit each, while any interaction in between those two are equally distributed the left 20%.
Each one of these models has its advantages, as well as its flaws. So, there is no “best” attribution model —you just need to find the one that works best for you.
Multi-channel attribution is very significant for growth and development, but just like any other aspect of marketing, it has its challenges. They are mainly:
- Online-to-offline attribution: The inability to take into consideration the interaction made outside of the digital world (phone calls, face-to-face meetings, etc.).
- 90-Day attribution window: Analytics tools only allowing to get data upto 90-days-old which may cause issues in industries with long sales cycles.
- Lack of conversion data: Channels that cause the most conversions create the illusion of bringing in the most revenue, whereas it isn’t the reality in most cases.