Read Time: 4 mins 30 secs
By Chris Berger, Managing Consultant at DQ&A and Ian Estabrook, Platforms Account Manager at Google
Continuing in our Virtual Learning Series, we teamed up with Google to dive into the Importance of Lifetime Value. DQ&A’s Chris Berger was joined by Ian Estabrook, Platforms Account Manager at Google for this hugely practical webinar.
Not all customers are created equal. It’s a bold statement, but when it comes to advertising, everyone has their own set of segments of customers who will more or less effectively drive your business goals. Deciding which group your customer fits into will depend on their past, present, and predicted future engagement, as well as purchase behaviours. In short, this is how much value they can drive for your business in their lifetime as your customer.
One of the guiding principles here is the Pareto Principle, or the 80/20 rule. This concept purports 80% of the effects come from 20% of the causes. For marketers, this can be thought of as “80% of your business is driven by 20% of your customers,” and this group of customers should be treated as higher value.
With this mindset and an understanding of the theory behind Lifetime Value (LTV), we can take a look at some of its applications.
Building your LTV Foundations
You might think that the best way to set up your LTV pipeline is to work out who has made the most revenue for your business so far. The problem with this approach is that it only considers past behaviour. There’s no consideration of whether they will continue to drive revenue for you in the future. Focusing on the number of transactions and the revenue associated with a customer also doesn’t help you to determine actions off the back of your LTV pipeline.
A good step to give you a better foundation to your LTV pipeline is to use RFM modelling, which not only considers frequency and monetary value, but also the recency of the purchases. This allows you to rate customers based on the nature of their behaviour and spending habits, and even use predictive modelling techniques to estimate customer potential. You can also do this if you’re focused on lead generation – so long as you can attribute backend CRM sales data to GMP users.
If your business is content-focused, using RFM modelling becomes a bit more difficult. However, if your site serves ads, ad revenue might be key. The quality of ads a user sees, and the more time in view, can be used to determine a user’s monetary value. You can use site engagement metrics from Google Analytics to estimate how much exposure a user gets to ads; from page depth, to time on site, to scroll depth. If you’ve got access to the publisher data through Google Ad Manager, you can also use metrics like Impressions, Viewability, or CPCs. This will enable you to estimate the monetary value of a user, unlocking RFM modelling (and thus LTV) for content-focused businesses.
Applying LTV gives you a much more nuanced way of maximising your ad spend. Without this way of grouping your different users, you’ll likely be running a flat marketing spend across all audiences. This means that you could be overspending on low-value users, and underspending on high-value ones.
By applying an LTV strategy, you reallocate your spend away from low-value users – reducing overinvestment – and funnel that into users who might drive higher performance towards your business goals.
Maturity and LTV
In a joint study with Boston Consulting Group, Google established four benchmarks of digital marketing maturity: nascent, emerging, connected, and multi-moment. Those companies that achieve multi-moment maturity reported cost savings of up to 30% and revenue increases of up to 20%.
LTV modelling is one of the steps between connect and multi-moment, so applying LTV to your digital marketing strategy can pave the way for a whole host of benefits. Not only will you be able to begin getting more value out of your customer data and greater ROI from your campaigns, but it can also help to increase the overall sophistication and maturity of your digital marketing and organisation as a whole.
Doing this doesn’t have to be complicated; for example, you can start by leveraging the data that’s already stored in your Google Analytics to create audience lists based on transactions and revenue. You can also enrich your GA360 data with your CRM or other offline data sources to build a more robust, holistic picture of your customers’ LTV.
Taking the Next Step
For those who want to experiment with more advanced LTV applications, Google has a client-side application called CRMint which is for scheduling data flow between 1st party data and Google products. This is a great tool for connecting different products; whether you’re wanting to activate LTV audiences across certain publishers in DV360, where you’ve seen good performance in the past. Or maybe you want to dial up your search campaign efforts in SA360 or Google Ads by bidding more on high LTV audiences because it brings more future value. Whatever your use case may be, activating LTV audiences across your buy-side products is an effective way to improve marketing relevance to end business outcomes.