In the beginning, there were clicks.
Back when search advertising started, Click-Through Rate (CTR) was our most valuable metric when measuring how effective our advertising was, and getting as many clicks to your site as possible was the primary objective.
The majority of us (hopefully) in the marketing world today have moved on to the point where our objectives are slightly more sophisticated than this. By connecting the dots between clicks and conversions and basing our KPIs on this data, we can look to drive results to the business, e.g. driving as many conversions as possible within the given budget without exceeding a $50 CPA.
But should we be looking beyond the conversion point at how valuable that conversion really is before deciding how much we are willing to pay for it? Those who advocate for lifetime value marketing would say yes.
Looking beyond the click
As an example let’s take two potential airline customers looking for flights online. They both type “flight to Brisbane next Wednesday” and both intend to purchase a flight in that browsing session.
Customer A is a young student who intends to fly to Brisbane to see one of his favourite bands in concert. He doesn’t leave Melbourne often due to lack of disposable income, but this is a once-in-a-lifetime opportunity for him.
Customer B is a retiree, whose son is living and working in Brisbane. She is close with her son and visits him at least 4-5 times per year.
Under a standard CPA bidding strategy which allows a $50 CPA target, the bids would be the same on both users. But which customer is likely to end up being of higher value to that business? If the answer is Customer B, should we not be more inclined to pay more for that conversion, as we are likely to get more back in the long run?
The concept of High Value or Lifetime Value models within marketing is nothing new. A quick Google search shows that Paid Search marketers were talking about Lifetime Value bidding as far back as 2011. So why are so few of us actually putting it into practice?
The short answer is because it’s not easy.
The difficulty barrier
An example on Think with Google about a loan company in Denmark and Sweden gives us an idea of why this is the case. CEO Andreas Linde explains:
“We’ve built our own data warehouse, where we store and combine information from a number of different sources to give a holistic view of the customer.
“Based on this, our data team has built a script that automatically calculates lifetime value across all markets and channels. This is absolutely key to gaining momentum in the market as it allows us to precisely know what a customer is worth and therefore how much we can pay for her or him.”
Simple as that, right?! The fact is that most brands and advertisers don’t have a data warehouse, a data team, the experience, or the resource to create an algorithmic script that will predict lifetime value.
The majority of us are lucky if our business has a fully functioning CRM system. But even with the access to CRM data, in order to start working towards LTV marketing, it requires a huge amount of data, and someone with the ability to efficiently label and segment that data.
Once that is done, you need to move onto modelling the data to enable the prediction of lifetime value, and then find a way to plug that into your marketing platforms in order to use it proactively.
As if that wasn’t daunting enough, you need buy-in from the whole business that value should be the new KPI, rather than bottom-line sales.
Optimising towards value may seem like a no-brainer to a performance marketer, but in reality, the majority of businesses have sales targets to hit, and if those numbers start to decline, alarm bells start to ring.
How to overcome the obstacles
So what can we do as marketers to get past these roadblocks? The same thing we always do: test on a smaller scale. If you don’t have the access or resource to 2-3 years of a customer’s CRM data or the knowledge to start labelling it as high or low value, take a step back and look at what data you do have.
You have a retail client, and your Google Ads data shows that women who live in Sydney and are not a parent are likely to be of higher value to you. You can use simple demographic modifiers to allow for a higher cost on these users.
Your client, a publisher of online news and magazines, has advised that those who subscribe or create an account are more valuable than those who don’t. You can tag the action of signing up on-site as a separate conversion point and create a bid strategy in Search Ads 360 optimising towards conversion and on-site sign-ups.
Your gaming client has advised that its internal teams have identified pockets of users within their data who they have deemed to be of high value. Ask your client to upload that list of users to your Ads platform create similar audience lists, and bid up on those users within search.
You could take this one step further by actively bidding on those lists of high-value customers with cross-sell or retention messaging. After all, once we have identified that a user is high value, we want to make sure we don’t lose them just as much as we want to acquire new customers.
If you can prove that you’ve moved a metric that your client’s business actually cares about using one of the above methods, you’re more likely to get their buy-in when you suggest a higher-level test using more sophisticated methods.
Take small steps towards your end goal, and prove the value of each step of the way. Play your cards right and you’ll have your own automated LTV script in no time.