A beginners' guide to attribution modelling
John Murphy, head of multi-channel at Bloom Worldwide, has written a new whitepaper on the hot topic of attribution modelling. Here he provides a quick overview of what to expect.
John Murphy, head of multi-channel, Bloom Worldwide
Attribution modelling is the method used to measure the monetary impact a piece of communication has on real business goals, for example: sales, customer retention, revenue and profit.
In our new whitepaper paper, ‘Digital Marketing ROI: An introduction to attribution modelling’, we explore what attribution modelling is, how to implement it, and review common attribution models, which will help define the best starting point for your business.
Attribution modelling, in essence, means reporting on the impact of communication activity using metrics like:
• Customer retention
• Volume of sales
Instead of metrics like:
• Share of voice
• Web visits
• Click through rate (CTR)
There’s a big difference between these two lists. The second list contains important metrics, but businesses could survive without ever increasing them. The business metrics in the first list, however, are essential for all companies that want to survive and thrive.
Understanding the impact of communications on business metrics is – rightly - more important to senior executives.
This is the primary objective of attribution modelling; to provide holistic, accurate information about the financial return activities are delivering so you can refine them, adjust what you’re doing, and use the same budget to deliver more value to your business and your customers.
There are two steps to putting attribution in place:
Implement the right technology to start gathering the information about where your different digital touch points appear in the customer journeys. There are several ways to do this and the most common is to implement tracking tags across all online activity.
Tags allow individual user journeys to be tracked and analysed to see exactly how users behave when they are exposed to different marketing activities. This can all be done anonymously so you’re never violating users’ privacy.
To understand the data, you need analysis. The attribution model itself is the set of rules that determine the value of an interaction or touch point in a number of different scenarios.
By applying these rules to different activities, and comparing the value that each activity returns against the amount it costs to deliver, you can identify the return on investment from each of your digital marketing channels and campaigns.
It is worth emphasising, though, that even without the right technology in place, there is a great deal that can be done with the data you already have. By digging into your existing data, and looking at how it relates to business performance, you can make great progress towards developing an attribution model.
The different models
Our new whitepaper looks at six of the common attribution models (or sets of rules) and when they should and shouldn’t be used to attribute results to your marketing activity.
While there are many different ‘off the shelf’ attribution models, this paper concentrates on six of the most common:
Last Click is both the most commonly used model and one of the most inaccurate. The Last Click model assigns 100 per cent of revenue generated to the last customer touch point before a purchase.
In layman’s terms, First Click attribution is the polar opposite of Last Click, it attributes 100 per cent of revenue to the first consumer touch point. For example, if a customer first comes across your brand by clicking on an organic search listing, and then later spends £100 on your website, organic search is said to have driven £100 of revenue.
Last Non-Direct Click
This model is similar to Last Click, except for cases when the Last Click is a direct visit. In such cases, this model finds the latest click that isn’t a direct visit and attributes 100 per cent of the revenue to that channel instead. The rationale behind this model is the idea that once a visitor comes directly to your website they have already made the decision to buy from you, so the cause of that purchase is not the direct visit itself, but the one that pre-empted that direct visit.
Where the previous models deem that one part of the customer journey is solely responsible for the sale, the Linear model states that every step of the customer journey is equally responsible. It is the democratic attribution model; every touch point gets credit for an equal portion of the revenue a customer spends. Therefore, in a customer journey where the consumer had five interactions with the brand, each interaction will be credited with 20 per cent of the revenue from that customer.
While the familiar path of Awareness > Consideration > Conversion has become more sophisticated in recent years, the fact that there is a journey, which starts with a potential customer finding out about a brand, is undeniable.
The Positional model acknowledges and represents this by combining aspects of First Click, Last Click and Linear. Essentially it says that the first touch point and the last touch point are worth X per cent each, and all the other touch points in between have the remaining percentage divided up evenly among them.
In the Time Decay model the principle is that the closer (in terms of time) a touch point is to the conversion, the more influence that touch point had on the customer decision. While the Time Decay model is one of the more sophisticated, in both implementation and understanding, this does not make it the best or the one that everyone should use.
For more information on the pros and cons of each model, download our new whitepaper for free.