In digital marketing, one of the most important metrics is calculating the ROI of digital campaigns from each channel. Once you understand how each channel contributes to the overall success of your marketing, you could easily optimize your spend across the best performing channels to get the most bang for your buck. However, there are serious challenges associate with the current attribution model.
Today, a typical marketer uses 8 channels to drive their marketing objective. It is important to know which channel does the important in driving the customers to make the purchase. For serious purchases, a customer will go through omni-channel experience before making a decision. For example, Jenny wants to replace her old TV and she started doing her research on her desktop on the latest models. She saw some TV ads on the search result and clicked through some of them to learn more. After work, she saw an ad on her facebook feed on her mobile about a deal on the TV she was researching about. She wanted to do some comparison on all the models and started reading blog posts on the latest features. She has a good idea of the TV she wants to purchase. After a few days, she saw a display ad on the TV she wanted to purchase and she decided to click through it and saw it was on sale. She went ahead and made the purchase.
This is a very simple example of how a typical customer navigate through different channels before making the final decision. It is important for companies to be part of the customer’s decision process. To figure out which channels and which ads truly made a difference in the process, marketers turn to attribution model.
What is an Attribution Model
Attribution modeling is a process marketers use to assign conversion credits to various different channels in order to help them allocate their budget for the optimized result. The default attribution model in many popular advertising publishers (facebook, google adwords…etc) is Last Click. In Google Adwords, there are other options such as Time decay, linear, position based and first click. You can also customize your own attribution model.
Last Click: the last touch point before the conversion receives 100% of credit
First Click: the first touch point of customer journey receives 100% of credit
Linear: every touch point in customer’s path receives equal amount of credit
Position Based: 40% of credit is assigned to the first and last interaction in the customer’s journey while the remaining 20% is distributed evenly to the middle touch points.
Time Decay: the touch points closest in time to the conversion get the most of the credit and the touch points furthest away from the conversion in time get the least amount of the credit.
Data Driven: this attribution model uses machine learning to evaluate all the converting and non converting paths in your advertising and assign the proper amount of credit for each interaction.
But what about MMM?
MMM stands for Media Mix Modeling and it is an analysis technique used by mostly larger CPG companies to measure the impact of their marketing and advertising campaigns to understand how each individual channel contributes to their goals. It is mostly used for broadcast & mass media, and more of top-down analysis and very macro in scale.
On the other hand, attribution models are used for measuring customer journey and targeted media. It tracks customer’s path to purchase and could be updated in real-time. For a typical direct to consumer company, attribution modeling should be used.
Choosing a perfect attribution strategy for your marketing is not easy, the best way to go about it is to test it out different attribution models and see which one works best for your business.