Customer acquisition costs (CAC) are through the roof these days. With so many new brands popping up, competition in online marketing has gotten steeper. Mary Meeker reported in her 2019 internet trends report that CAC is actually outpacing lifetime value.
So what do we do about this? We need to bring costs down, so you can acquire more customers and make more sales without paying an arm and a leg in marketing.
In our ongoing quest to help our clients lower their CAC, improve ROI, and sell more stuff, we’ve landed on one definite recommendation for where you should start: retargeting.
Solve Retargeting First to Conquer CAC
To help your brand sell more stuff, we guide clients through a KPI roadmap we call the “Growth Journey.” We apply machine learning solutions incrementally to specific, goal-oriented marketing functions. It starts with a model for maximizing the effectiveness of your retargeting.
Why? Here’s the first reason:
Because retargeting is a relatively small part of your budget that makes a big impact on your conversions. It’s what gets your customers across the finish line.
At first you might be thinking, “retargeting represents such a small part of the giant heap of money I’m forking over to ad platforms.” This is true. You’re undoubtedly spending way more money on your broader campaigns. With this perspective, it might be hard to see why we’re not tackling the bigger campaigns first. But we do intend to also bring those costs down as well. Improving retargeting performance is just the first step.
What we’re doing in this step is using machine learning to segment your audience between who is likely to make a purchase and who isn’t. This allows you to cut down the size of your retargeting audiences by at least half, capturing only the likely buyers.
Now, you’re still going to be using the other tried and true retargeting tactics you’re used to. Segmenting by product category, personalized messaging, etc. But focusing on likely buyers within those tactics adds a magical(don’t tell our engineers we used this word) timing and frequency element that greatly improves each customer’s experience with your ads.
You can read all about our clients’ successes with this here, here, and here. Not only did focusing on likely buyers help our clients reduce ad waste, it actually increased sales and average order value as well!
When it comes to implementing the technology, collecting data, and training the models, retargeting is low-hanging fruit. You don’t need to integrate every tech platform and data source under the sun. All you need is a simple site tag to collect website visitor data, and an integration with your retargeting platform (most likely Facebook or Google) so you have a place to send your machine-learning audiences.
It actually takes less than a day to get Velocidi set up. The most time-consuming part of the process is just giving the machine learning model time to learn your customers’ behavior so it can make accurate predictions. In a couple of weeks the optimized audiences are ready to be used in your campaigns. Then you just plug them in and run your campaigns as usual.
But back to conquering CAC
There is still one more awesome thing you can accomplish in the retargeting stage of the Growth Journey: Create lookalike audiences based on the “likely to buy” audiences you’re using for retargeting.
Facebook’s lookalike audiences are the most commonly used example of this strategy. It’s common practice to create lookalike audiences by uploading customer lists from your CRM of your most high-value customers. By using the “likely to buy” audience as the source for Facebook’s lookalike model, you can eliminate a lot of the work that goes into making those lists, and avoid unnecessary data sharing. You can read a little more about that here.
New customer acquisition is actually a later stage in the growth journey. But just by getting the retargeting audiences working, we can already have some impact there.
After solving retargeting, our next step in the Growth Journey takes you over to the lifetime value side of the equation. It’s not enough to bring down acquisition costs relative to itself. It has to be lower relative to your customer lifetime value.
The customer retention stage of the growth journey applies machine learning to help you predict when to re-engage each customer to prevent churn, and when to email them so they are most likely to engage.
We’ll come back with more on retention soon. For now, thanks for reading! Subscribe to our newsletter to get monthly updates. And follow us on Linkedin if you want to hear from us more often than that!