Third party data is collected without any prior agreement between yourself and the data processor. It is relevant and useful data you might want to feed into models to understand its impact on current or future performance. These three areas are vital to work out what you have access to and its level of reliability to help you understand remaining components you will need to fill in gaps as you go through.
Measurement: Why measurement matters?
If you have really advanced predictive modelling, Google has a range of built-in tools inside Cloud platform like AutoML allowing us to push this data into it and using pre-built tools that Google has got. It will then look at the attributes of a customer, your current customers and make a prediction on how valuable that customer will be to you. You can then use this to inform how much you want to bid on the CPA model if you’re looking at the overall lifetime value.
In conclusion
It matters because if you add poor data into Google’s bidding algorithm or don’t give it complete data, you are not getting into the nitty gritties. Google therefore isn’t going to understand the impact of the bidding, leading it to make poor bid decisions and overall result in poor performance. On the contrary, if you have great quality data, you’ve got your full journey mapped out, giving Google reliable data to yield really good performance. These will also be one of the things that will distinguish good advertisers on the platform from the really great ones; the ability to provide the bidding algorithms with the best possible data in line with key business objectives.
Measurement: Bidding towards Value
You can measure conversions, but if you have campaigns that are quite low volume, you might not be able to necessarily bid on funded loans if you’re only getting 30 a month.However, if you are getting 200 people to stage 3, it would give the platform plenty of data to optimise towards. So not only would it provide the platform the full customer journey but also useful things to bid towards if you are lacking in data, with regards to conversion actions slightly further down the funnel. You also attribute value to every micro conversion based on how likely users are likely to convert at that stage..
Measurement: Micro Conversions (Floodlights)
The advanced advertisers would further pull in things like offline core conversion tracking, so linking their call centres to Google analytics. This way you’ve got your CRM call centre, analytics and Google Ads all connected together allowing you to gain a complete picture of what’s going on. You could go a step ahead and take into account different channels within GA rather than a single channel where you’ve are cookied by Google when bidding towards value.
This is quite a good example because it encompasses the distinct type of journeys in financial services’ business. It eases the process of laying out an extremely clear roadmap of all the different touchpoints, online as well as offline journeys and most importantly micro-conversions involved. In terms of measuring micro conversions, this is quite simple to track in GA4, allowing you to give the platforms much more customer data.
Measurement: Micro Conversions
Offline conversions are primarily measured by using click IDs and the measurement API. When we typically go into clients, there’s usually a variety of ways they have done this. Some are using UTMs to measure offline activity and then stitch the two together with spreadsheets, which is quite common. Some might be measuring it just on Google Ads while others have it in Analytics, but ideally you’d have this data sent back to all the platforms that you’re using. So whatever that be, Facebook, Google Ads, Analytics, using the various different APIs. It is key you map out all the offline conversions throughout.
When someone goes into the website, the number changes and then Google records the phone number that people have called you on. You store that phone number in your CRM system and basically report it back the same way. Using a spreadsheet or the API, you could push back the phone number along with the conversion that happened and Google would register it as a conversion next to the ad. You could also pass back value once the loan has been funded, leaving you with a complete view of offline tracking of both, your clicks and call activity.
Measurement : Measuring and Modeling LTV with GCP
Below is an instance of doing it in a more advanced manner. Based on the way people fill out fields and forms, you can attach a micro conversion value if you’re using floodlights in a campaign manager. So if they’re a homeowner and you’re doing secured loans, you might want to up weight the conversion value if they select yes or down weight it if they select no. This would be a good way to indicate to Google the value of the leads if they are in the earlier stages of the purchase journey and haven’t got huge amounts of data. It’s a good way to give Google an indication of the quality of the lead.
Measurement: Offline conversions
In case of a Cloud platform , if you’ve got a CRM like HubSpot, Salesforce, you are able to easily push data for your opportunities into Google Cloud in a tabular format and consequently stitch those together, to get a glimpse of views per customer and an overall count of your customers, their loans, the timeline of the loans and their LTV. These points are then vital to determine the value of the customer and perhaps what your CPA bid will be if you’re focusing on bidding towards lifetime value as opposed to short term bidding where you’re looking at value or CPA in the short term.
Similar to the data maturity framework for Google Analytics, we have another one more focused on Google Ads and the process to bid towards value as opposed to lead quality. Here we go from beginner to pioneer as we call them. Beginners being people who are probably measuring online conversions and might have core conversion tracking. They are advertisers who haven’t yet invested heavily in data, but have considered it as part of their roadmap. The more intermediate advertisers would already be bringing in offline data. Here you’d expect to start a bid towards value. We would actually now begin to give Google a much fuller picture of what’s going on.
These are who we refer to as Pioneers. They would have in place full multi channel attribution and start really thinking about micro conversions. In insurance, for example, you’d also want to be looking at LTV as part of setting your bids and targets. You might want to take advantage of AutoML inside Google Cloud platform so you could push in your current customer data and attributes and provide a predictive LTV out the other end which can then be used to inform the sort of CPAs that you might want to bid towards. So that’s the stages we sort of see people going through and obviously the further down you are, the better results we expect to see from your performance activity.
Measurement: Plot all of your Conversion (Lending example)
You gain key competitive advantage if you are able to correctly leverage existing predictive models and more importantly, build your own advanced ones. It puts you in a better position than your competitors who may not have that functionality or rely on stock models already built into your tools. This really draws a strong focus on initiatives that will increase the propensity to purchase or likelihood to churn. Reliable data is consequently a crucial component in order to do this. Without it, you’re likely to have unreliable models leading you to the wrong direction and decisions.
The type of data we can draw on..
It’s time to embrace the future of marketing and harness the power of predictive insights to drive business growth. Do you want to learn more about the power of data and predictive marketing for your marketing strategy? Check out this insightful article by Gary Stubbenhagen, our Head of Data at Builtvisible or redirect to our data product page to learn more.