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The growth and marketing teams behind DTCs know all too well, paid media advertising is pretty much always in a state of evolution. Between rises in CAC, privacy restrictions, deprecations, and more—marketers have to put much more thought into their growth strategies to ensure that they get the most value out of every dollar spent. At the end of the day, the ultimate goal here is to maximize impact, scalability, and profitability for your brand. And this is exactly where value-based bidding (on Google campaigns) comes in.
The thing is, subscription DTC brands have a lot more to juggle than most, considering multiple subscription packages, prices, and plans. Should any and every potential customer be deemed as equally valuable? Well, most DTC brands would work off of the simplistic assumption that this is indeed the case. In reality, if we examine the actual LTV/retention of different customers, we find they are quite widely distributed (with an equal chance, for example, of being worth exactly $X or $3X+ by, say, Month 6. As such, when you decide to apply value-based bidding in your campaigns, you bid higher for users that are worth more, and less for users that are worth less. It’s only fair to base your budget on the true value of each customer, rather than the value of all your customers.
This is not a new capability (also called targetROAS or Value Optimization) - but without predictive modeling, the value of all of the users seems the same, in the first few days of the conversion window.
So let’s dive into the inner workings of value-based bidding for DTCs, how you can apply it in-house, and further amplify its impact for the long term.
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Value-based bidding (VBB), which is also known as “smart bidding” refers to some of the strategies used to let Google automate your bidding. tROAS, tCPA, Max Conversions and Max Conversion Value are the options there, and tROAS and Max Conversion Value are the ones that activate VBB. It is also worth noting that tROAS is also dubbed "Value-Based bidding" by Google. As I mentioned earlier, this is done by placing special focus on each customer, and placing greater emphasis (which is proportional to their value) on the specific customers that are more likely to be the most profitable. When compared to campaigns without value-based bidding, the ROAS on campaigns stemming from value-based bidding is significantly higher.
As you can expect, when using Google Ads for value-based bidding, Google gains a better understanding of your customer’s value, and in turn manages the bidding in a differentiated stratified approach, with higher bids on higher “bands” of customer values, and lower bids for lower value customers. This creates a much more efficient strategy - using the same given budget, to provide much better efficiency (ROI and ROAS).
Value-based bidding has been around for a while, and has only recently become mainstream due to:
When you use value-based bidding, you are prioritizing and enforcing more lucrative conversions, and deploying your marketing capital in the most efficient way.
At this point, you might be wondering what’s wrong with treating all customers the same. More is more, right? To be honest, without value-based bidding, it boils down to the fact that you are over-investing on lower-quality customers, while under-investing on those that are inclined to be more profitable. When segmentation takes place based on customer value, the returns become maximized, as seen below.
Now let’s go over the most valuable element of value-based bidding with an example:
Let’s assume your company has three typical customer types, each of which manifests different values to your company. These values can be due to LTV, plan price or probability to convert.
Instead of paying the same amount for Customer 1 as Customer 3, even though Customer 3 is worth four times more, you can bid differently for each of those customers, in accordance to their potential value, while also prioritizing users that will manifest higher value.
The use cases for DTC subscription brands to start using value bidding include different price levels to differentiate products, different plans (monthly/yearly) and of course, if your subscription brand offers eCommerce top-ups.
Now let’s talk about how you can get started with value-based bidding, so you can make the most of your marketing budget to target higher value customers.
At this point, value-based bidding is for most every brand, and here are the three steps to get started:
Start by sharing conversion values according to the box/product size and plan. For instance, if a user paid for the highest-priced box and chose a yearly plan, they are probably worth much more than a user that purchased the basic box and chose a monthly plan.
Now if you want to take this to the next level—your team can also leverage your company’s zero-party data, to better evaluate your users' loyalty and LTV.
Based on our experience working with D2C customers, the answers to simple questions implemented in onboarding questionnaires can be very strong indicators of future value. Especially when the questions are something like: “How many times a week/month do you plan to use our product?” or “What do you use our product for?” We recommend you analyze and identify the answers to such questions, as those strong indicators for high LTV.
The second step is to assign different values to conversions, based on your real-time and historical data.
I’ll explain how it’s done.
Let’s say you want to calculate the value of a user who purchased your basic monthly subscription.
To start you'll need to know and calculate the average loyalty of users who purchased a monthly subscription. Is it three months? Perhaps six months? Or maybe 18 months?
Next multiply that by the monthly revenue. You can also include average additional revenue from e-commerce top-ups to the basic box.
The final result is the conversion value, as you can see in the graphic below.
Of course the accuracy and effect of the value can be enhanced by leveraging LTV models that predict users future value.
There are different ways to assign different values:
The final step on Google Ads is to set the campaign up as a tCPA for a short period, then switch to tROAS. The tCPA phase is only needed the first time you set such a campaign, not in subsequent campaigns.
You start this by reporting your conversion value to Google Ads on an ongoing basis, four weeks before opting in. This is done by creating a new conversion on Google Ads, and applying value to the conversion. This includes choosing whether the value is constant or dynamic.
After four weeks, you can launch a new campaign(s) on tCPA, optimizing toward this set of conversions. It’s recommended to keep the campaign as tCPA for about four weeks, or three sales cycles. Why four weeks? Well, mainly because of the learning curve. You need to give Google’s algorithm some time to process the data.
After the waiting period is over, and Google’s algorithms have collected enough data to predict user behavior, you can switch to tROAS.
There are some pretty common pitfalls that prove to be costly for DTCs. Here are some of the top ones that we really recommend you steer clear from:
Now if you’re really ready to spice things up, you might want to consider adding Predictive Bidding into the mix. After all, the ability for DTCs to send a value based on LTV is major! If your DTC business engages with customers with different values based on variables such as subscription level, upsales/cross sales, churn and more—there’s clearly a lot of volatility at play here, and predictive bidding helps bring order and direction to your campaigns.
This branch of predictive marketing takes value-based bidding to a whole new level. Let’s start at the very beginning. What is Predictive Bidding in the first place?
Predictive Bidding, in the context of growth marketing, refers to the usage of predictive models that can analyze your brands zero- and first-party data, to accurately determine each user's future LTV in real time. By extension, your team can use this to accurately gauge each user's LTV and loyalty, based on defined behaviors, and make decisions for days/months/years from now back on that day. That’s futurespection.
For marketing teams, Predictive Bidding can be considered the holy grail in the value modeling approach. Here are some of the main reasons why:
The usage of Predictive Bidding will drive the best value for your campaign budget in a sustainable manner, locking in long-term profitability.
By now, I’m sure you realize why there is no time like the present to make the switch to value-based bidding, to maximize your conversion value. And if you choose to capitalize on LTV optimization on top of that through predictive modeling—the sky's the limit because that sets your campaigns up to succeed from the onset. It is well-known that additional conversions could happen when a new customer exhibits signals they will become a high-LTV customer.
If there is one takeaway I suggest you walk away from the post with, it would be that you really should consider value-based bidding before your next ad campaign. This can help you achieve the big goals you’ve set for your business, and get on the path to long-term sustainable success.
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