The challenges brought on by iOS 14.5 led to a rise in user acquisition costs, and in order to keep up with their goals, growth teams behind DTC companies understood that their strategy needed to be changed.
It has become clear that with each update that is being implemented on growth marketing platforms and ad networks, their behavior is becoming less predictable and stable. That explains why, in the last six years, the cost of acquiring new customers has increased by 60 percent for most industries. It’s not that high for DTC companies however, which have seen CAC only up 25 to 30 percent compared to five years ago. Where did many D2C brands luck out? Many chose to capitalize on the pinpoint targeting capabilities across ad networks by zeroing in on customers that demonstrate greater LTV. They, in turn, made adjustments in shifting from a CAC strategy, to a payback strategy.
CAC strategy limits a brands ability to scale, because it only “locks” the price they are willing to pay. Inversely, payback/return based strategy allows growth teams to “stretch” that limit by focusing on the return and not limiting networks to “fish” in a limited pool.
Going from CAC to payback
Traditionally, DTC companies would manage their user acquisition campaigns in a way such that they were constantly shifting and optimizing with CAC in mind. Budgets would consistently increase and decrease, and campaigns would be tweaked on a daily basis. The process itself was relatively complicated, considering the many variables that come into play. It’s also an effort that calls for the attention from multiple departments, from marketing, to creative, to growth, to engineering, and even CX.
Today, this strategy is less feasible, not only because of the element of hassle, but also because optimization capabilities have become limited across the ad networks. As a result, the shift marketers should do is look beyond the CAC, by also considering payback and profitability, focusing on how the brand can recoup the money that was spent on marketing to acquire customers faster (and therefore start to return a profit faster).
* HubSpot found that 67% of companies that had a greater marketing ROI than the previous year ramped up their marketing budgets.
This shift is changing the way UA teams are building, optimizing and measuring their campaigns from setup to ongoing.
Locking your price implicitly assumes locking your customer's LTV. That works, on average, but does not scale well, as it does not distinguish between "somewhat good" and "terrific" customers. Conversely, switching to a strategy that distinguishes between payback of different customer segments, coupled with the ability to target them, allows D2C brands to pay differential CAC for those different segments. This allows them to win higher bids on impressions at a higher scale on the "terrific" users.
Here is how campaigns are built and measured with a payback strategy:
- First, you need to understand your customer data - cross your own data with the marketing data cost. Find out how much it costs to acquire new customers, and how long it takes your high-value users payback.
- Analyze the ROAS when the seven-day conversion window ends. Does the average ROAS for those users match the payback? Is it more or less? The answer will help you determine your ROAS for the limited time frame of the conversion window.
- Change your campaign objective, switching from the standard cost cap calculated CAC, to maximizing your customer acquisition value through minimum ROAS needed after finding out the required ROAS in your customer cycle data.
The connection between payback period and LTV
There is a connection between the payback period and LTV.
In general, the payback period refers to how long it takes for a customer to “pay back” the amount of money that was spent to acquire them—but what about the rest of their relationship with the brand? This is where LTV comes in, which is richer based on the amount of data at hand. The more, the merrier.
As we mentioned in a previous post, there are numerous benefits that go hand-in-hand with LTV optimization, including reduced churn, increased ROI, and significantly greater returns on CAC.
Growth marketers and user acquisition managers can optimize their campaigns based on LTV data, combined with the payback they want, and when they want it. It all starts with the initial learning phase on ad networks such as Facebook and Google. In the learning phase, ad sets are typically less stable and usually have a higher CPA. To avoid behaviors that prevent ad sets from exiting the learning phase, it is recommended to use realistic budgets, avoid high ad volumes, and avoid edits to the ad set. Loyalty-focused marketing, with a heavy focus on LTV, helps ensure all is done right the first time.
In closing, here are some additional insights from the Voyantis team that growth teams of DTC companies should know:
- Understand the importance of determining your market fit. When you know exactly who you're selling to, and the pain points you’re addressing, your brand message becomes much more effective and each dollar spent becomes that much more effective. Taking the time to create buyer personas, conduct market research, perform customer segmentation and formalize other sales and marketing due diligence will keep you from spending sales and marketing dollars targeted at the wrong buyers.
- Take advantage of upsell and cross-sell for greater LTV. It is easier to sell to an existing customer than a new one, and customers who expand from their initial purchase achieve payback more quickly. If you can pay to acquire a customer once and then sell them additional features, or products, you will soon find yourself dramatically improving ARPU.
- Drive funnel efficiencies. Powering up your marketing funnel is a two-part endeavor. The first step is to build a funnel that encompasses every stage of the buyer journey from the top to the bottom. The second step is to take advantage of automation. Marketing automation tools help brands scale sales and marketing efforts easily and effectively without the need for additional costly overhead.