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Digital Measurement in a Nutshell

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Digital Measurement in a Nutshell Digital Measurement in a nutshell (Okay, not quite a nut, maybe a coconut) Introduction The aim of this 10 minute read is to provide a constructive, practical introduction to the jargon- packed, data dominated world of digital measurement and attribution. It is aimed at digital professionals, who have encountered terms like analytics, online measurement, click-path analysis and attribution but have rarely used them in practice or are unsure how they can be properly applied to their work. This guide will give an overview of how digital measurement works, why it’s important and how it powers online attribution analysis. We’ll take a detailed look at the basics of digital attribution, understand different attribution models and finally address the common end result of attribution analysis…the ‘so what’? Analytics and Attribution are not the same thing Digital measurement and attribution has entered the mainstream. It is now a widely respected discipline served by the world’s biggest technology providers. A report by Adroll said more than 80% of e-commerce brands are running active attribution programmes. That said, the basics of digital measurement and attribution are often overlooked. Too much brain power is spent debating the merits of different attribution methods without ever really remembering that the overarching purpose is to understand and interpret connected internet journeys. With this thought in our minds, let’s take a stripped back look at digital measurement and attribution; how the two concepts work together and why e-commerce companies need them. Digital measurement and attribution are two wonderfully intertwined concepts. You can’t perform digital attribution without first implementing a solid system for digital measurement. And these two things don’t have to be delivered by the same company…but it helps…sometimes! Analytics understands what customers experience Attribution understands the effectiveness of marketing Who can help? All businesses should start with a free web analytics package to help them understand traffic generation. Google Analytics is the mainstay of this market. The free Google Analytics version comes with limitations, such as a restriction on native marketing integrations and a limit on reporting options/usage. Here are some more details on this. Once a business reaches a certain size an enterprise level web analytics platform will be necessary. The enterprise version of Google Analytics – now branded as Analytics 360 – is a natural progression for many companies. However, Adobe also offer a comprehensive and popular enterprise level web analytics package, while Fospha, Conversion Logic, VisualIQ, Impact, Cake and Kissmetrics are among a large number of independent alternatives. There is also a buoyant market in dedicated measurement solutions for Apps, with companies like Kochava, AppsFlyer, Tune and Adjust being the most popular. Sometimes measurement companies refer to a ‘Single Source of Record/Truth’, because their solutions provide an over-arching, definitive reporting view of everything and everybody that passes through an online business. The technical stuff All digital measurement solutions work by first aiming to ‘tag-up’ inbound traffic to a company’s website and/or app. This will allow measurement solutions to recognise and report back on customer journeys. This is most commonly achieved by adding URL parameters to inbound website links and firing a http/s request or a piece of code every time a user lands on the business’s website. Measurement providers will not only want to understand how customers reach a business, but what those customers do when they get to that business. This is normally done by placing a non-intrusive piece of code on a website/app to track conversion events, like entering an email address, filling in a form or completing a transaction. This closes the loop, allowing the measurement of a customer X, who reached www.connectedpath.com by clicking on an organic search listing and signed up to our database. Any business looking to perform digital measurement must be open to placing URL parameters and small pieces of third-party code throughout their properties. This is analytics in its most basic form. The technical stuff continued Modern digital measurement is not content to only know how customers find a business. It also wants to understand who those customers are and crucially what their journey looks like. This is where measurement companies start to profile customers using either unique first-party identifiers (email address, customer ID) or a combination of third-party identifiers (device, IP, location) to ‘tag’ a customer. This allows online measurement to record much more detail about an inbound customer. So, we can expand the earlier example, and say we now know this customer is called Dorothy, and before clicking on Connected Path’s organic search listing, she also viewed one of our display ads, visited our blog, left without completing any action, and then came back via an organic search ad before signing up to our database. We might even know that Dorothy used two different devices to complete this journey. This type of customer journey analysis is now a staple of all good digital measurement companies, and importantly for our work at Connected Path, it makes the science we call digital attribution possible. Who gets the credit? If analytics is about understanding, then digital attribution is about credit. Knowing the steps Dorothy took to find and sign up to Connected Path, we now want to use attribution analysis to know which of these steps was the most important. Why do want to do this? Well, partly to satisfy the curiosity of diligent marketing professionals! But more importantly because this information will tell us how we should spend money to market our business to people like Dorothy in the future. The original, and still common, way of doing this was to assume the last thing Dorothy did before signing up to our database was the most important. Commonly called last-click attribution, this view is now much maligned by digital attribution commentators keen to look clever in the face of a naturally evolving technology. The reality is last-click attribution is very logical. Who wouldn’t assume Dorothy’s last touchpoint before signing up to our database was the crucial factor in driving her action. It’s an assumption many e- commerce companies still use to determine the relative success of their marketing efforts. Who gets the credit? continued As the digital marketing world was drifting along in the logical equilibrium of last-click credit, it was derailed by a question even more logical. Does last-click mean viewing our display ad or reading a blog post about us contributed absolutely nothing to Dorothy’s desire to sign up to our database? Of course not. We have known for generations that marketing does not affect us in isolation. This is why marketers need cross-channel digital attribution, to assign appropriate credit to a variety of tactical marketing efforts that are all working in tandem to influence potential customers. Different Attribution Models A wide variety of attribution models exist, many specifically designed for the businesses they serve. Here are some standard ones: The marketing touchpoint that is closest to the action receives total credit for influencing the user. No other touchpoints Last receive any credit. This model is Click underpinned by the principle that the marketing closest to the action should take precedent over any other marketing that user has engaged with. The marketing touchpoint that initiates the customer’s journey receives total credit for influencing the user. No other touchpoints First receive any credit. Working to the opposite principle of last-click this model believes Click that the marketing touchpoint that initiated a user’s journey should take precedent over all others. Different Attribution Models continued Each touchpoint in a path-to-conversion is given equal weighting. A simple model that allows marketers to recognise the contribution of multiple marketing channels Linear and assumes marketing touchpoints all have an equal impact on a customer’s purchasing decision. This principle has lost credit with attribution analysts because it does not account for important factors like latency and consumer awareness. Each touchpoint receives a different weighting based on its position in the user’s journey. This is the most popular model for multi-touch attribution analysis, adjusting the attribution weight of each touchpoint in Position a customer journey based on its position in Based the path-to-conversion, normally giving more value to the first and last click. Position-based models are designed to avoid over-crediting the first and last click by assigning some value to each touchpoint. Different Attribution Models continued Powered by machine-learning these models use algorithms to analyse all touchpoints Algorithmic and conversions to calculate weightings based on how important a channel is to driving actions. The aim is to identify how important the presence of a customer touch point is to influence the customer to make complete their purchase journey. This type of algorithmic modelling is sometimes referred to as regression analysis. These models are all different ways of measuring the “ same outcome. For example, the outcome of Dorothy signing up to our database is always the same. But a linear model will apply equal credit to all the touch points in Dorothy’s journey. A last-click model will only credit the final touch point. ” So What? All this data…what’s the outcome? So What? Given that attribution is effectively different ways to slice the same cake, how does it turn understanding into action. Where is the ‘So What?’ The telling impact of a well-executed digital attribution programme will be how it changes a marketing budget. The best way to think of this is to show a practical (and hypothetical) example.
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