Understanding customer behaviour helps to effectively allocate budgets where it will matter most. In part 4 of the Google on Air series, we take a look at how a solid measurement strategy forms the baseline for evaluating your customers and ensures you are reaching the correct target audience.
The changing measurement ecosystem
In recent marketing evaluations, there has been a big shift in cross-device behaviour as well as online to offline behaviour. So what do we see? Well, the number of touchpoints before a customer can reach up to 900+ engagements. 30% of people now use 5 or more devices and roughly 76% of people who search on their smartphones for something nearby visit a business within a day. User journeys are fragmenting and it’s expected that by the end of 2020, you would see people using up to 7 different devices to connect online. If you think about it, these devices can include TVs, laptops, computers, desktops, mobile phones, smartwatches and even your car! So even though it might sound like a lot, it’s reasonable to expect this number to become a reality.
That being said, in 2020 it’s clear that measuring all the various devises is becoming increasingly difficult and this is why it’s important to go over a few crucial tips to measure accurately.
Firstly, it’s important to establish what matters, so you will need to clearly define your customer value KPIs (key performance indicators), such as a completed purchase. Secondly, once you have your KPI based data, start to understand where to prioritise marketing spend and how you can leverage machine learning throughout the process. Thirdly, put your insights to use in order to find the most important prospects and customers to maximize the value you get from your customers and marketing spend.
Privacy-safe Conversion Measurement
User expectations are rising, as people demand more transparency, choice and control over how their online data is used. That being said, first-party data is an incredibly valuable asset. Both marketers and publishers are having an increased focus on their own audience data, including greater attention to first-party data management, activation, and measurement.
So how can you keep measuring data in a privacy safe environment? A very well known method is by using Google Tag Manager to measure first party data, which allows you to measure all website engagements while keeping user data safe. Keep in mind that you have to make sure you have updated your own policies on how data is collected and shared through your website.
Measurement can take place across various pre-purchase or pre-conversion actions, such as certain product views, cart engagements, service page drop-offs and much much more. This allows you to perform user segmentation and get a clearer picture of each website touchpoint and how users engage with them.
In addition to online conversion tracking, a valuable method is to record offline conversions and lead information into your CRM database and upload them back onto Google Ads. This provides you with additional user and conversion data. It’s needless to say that having additional user and conversion information included in your data set will provide you with a much higher ROI.
Attribution Across Solutions
What is attribution? In short, it’s about assigning credit to a specific ‘act’ by a user. These “acts” or attribution models help us understand how each of our channels or touchpoints perform or how they lead to a conversion.
There are various types of attribution models that you can assign as well, split between Single Touch Points and Multi Touch Point models. Single touch points offer the least value as it assigns 100% of the conversion value to a single action. The most beneficial way of using these models would be through Multi Touchpoint, where the value of an action gets shared amongst various touch points throughout the user journey to conversion.
Without getting stuck too much in the nitty gritty of attribution modelling, it’s important to note that you want to end up at a point where you can use Data-Driven modelling. This model can only be used once you’ve recorded enough data and conversions.
So what is data-driven attribution? Machine learning algorithms evaluate converting and non-converting paths to learn how different touchpoints impact conversion outcomes. The Data-Driven model attributes credit to each touchpoint based on its likelihood to drive conversions. It incorporates factors such as time to conversion, device type, number of interactions, the order of ad interactions and the type of creative seen/engaged with.
When can you use this model? Well, Google requires a minimum of 600 conversions + 10,000 clicks in order for you to start using this model.
Activating Measurements Strategy
Once you have your attribution model in place, you can look at your reports and realise the value of your data, but what you really want to do is to make sure you optimise your campaigns around what you see in your data.
A few years ago, account bidding was a lot simpler. With more targeting methods available, more devices being used, and customers being on the go and looking for more products at a wider range of times throughout the day it became more and more difficult to keep track and optimise towards these various trends and changes. This is where smart bidding plays a big role. The smart bidding system keeps track of all the micro-data points throughout the conversion process and optimises towards that. The key to masterful bidding is to adjust your bids based on each user’s unique combination of signals. Assessing all of these manually, for every auction, is impossible. Trying to control all of the factors involved in bid optimisation also takes up a lot of time. Why sacrifice time and manpower on manual bidding when you could be focusing your effort on more impactful, strategic initiatives?
There are various types of bid strategies available as well. So be sure to choose one that’s the most relevant to your campaign goals.
Data-Driven Attribution models and Smart bidding is “better together”. Google’s specialists note that there is an average uplift in conversions of 14% when opting into fully automated bid strategies and a further 3-5% increase when adopting Data-Driven Attribution.
Below are some top tips on best practices when moving away from single touch point attributions such as “Last Click” to Data-Driven Attribution.
The Future Of Measurement
Measure cross-everything! Marketers must be able to measure cross-channel, cross-platform, cross-device, and eventually cross-media while protecting user data. The easiest way to do so is by using Google Analytics in conjunction with Google Ads.
You need to prove business impact by focusing on metrics that show a direct impact on business outcomes like sales, revenue, and profit.
Harness machine learning & automation. Customer expectations are rising for immediacy and relevance, and marketers will rely on machine learning and automation to achieve personalisation experiences at scale.
Embrace simplicity and choose tools that are simpler, easier to use, and better integrated in order to deal with growing complexity.
At Elemental we look ahead and try to understand what will impact performance in the weeks, months and years to come. If you are looking for detailed strategies and a complete ROI based paid media approach, give us a call.