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Are you prepared to answer the 3 questions your CFO will likely ask you?
If you’ve been following along with our Digital Economist blog series, you will have learned a lot about the ins and outs of building a successful digital customer acquisition strategy for your business. Here’s a refresher of the basics.)
From building customer segments, made up of only your most profitable customers to developing persuasive value propositions to architecting segment-specific conversion journeys that drive action — it should be clear by now that digital customer acquisition isn’t something that just comes into fruition overnight. It requires testing, measuring, and constant refining. As market dynamics continue to ebb and flow, so will your digital customer acquisition strategy.
Remember, though, that at the end of the day, the entire purpose of digital customer acquisition is to grow your business. And while everything we’ve discussed thus far is important, how you — and your CFO— will ultimately measure success will come down to the revenue and profit generated by your digital customer acquisition program. In fact, a whopping 94 percent of CFOs have said they would increase digital marketing budgets if there were clear evidence it led to sales. This is proof that approaching digital marketing as a Digital Economist has its perks.
So, to wrap up this first wave of the Digital Economist blog series, we’re going to take a quick look at the important role that unit economics plays in assessing the overall economic impact your acquisition efforts can have on your business.
The goal of any digital customer acquisition program is to devise a plan that will pay off once you’re able to get only your most profitable customers into the top of the funnel. You might even ask yourself, “For every dollar I invest, what am I going to get out of that dollar invested?” Putting unit economics into action will help answer this question. It will uncover exactly what tactics you’ve deployed are working to generate the highest return on investment (across both channels and customer segments), what’s directly affecting CAC (customer acquisition cost), why LTV (lifetime value) might be greater for certain customer segments and channels than others, and, most importantly, how you will ultimately invest your next customer acquisition dollar. Measuring economic outcomes in this way will allow you to test all the work you’ve already done around customer segmentation, value propositions, and conversion journeys.
Here’s why this matters: your CFO will want to know that the budget you’ve allocated to digital customer acquisition is actually working. So, to help you shine in those conversations, let’s take a look at the three questions you’ll most likely be asked — and how you can come to the table prepared to tackle them with confidence.
1. When are you going to spend money?
If you’ve been through any budgeting cycle, you know that money doesn’t just appear out of thin air. The dollars you get for your digital customer acquisition efforts won’t either. For starters, your CFO will ultimately want to know exactly when you plan to spend the money allocated in order to determine when and where to make strategic trade-offs between different investments across the company.
This is where unit economics comes in handy. As marketers, we’re accustomed to reporting the success of our campaigns via vanity metrics like impressions and CTR. However, to help forecast budgets for the future, you’ll need to provide your CFO with line of sight into the sales and revenue pipeline, clearly articulating what value — and profit — can be achieved by continuing to dedicate budget to your digital customer acquisition efforts. Identifying both past and future success via CAC and LTV (which we’ll dive into more detail below) allows you to speak in terms your CFO understands. He or she will want to know — and have quantifiable proof — that your tactics are driving profitable growth. That’s really the key to locking in future budget.
2. Will you make more than you spend?
No CFO will ever expect the fruits of your labor to be in the black immediately. However, at some point, you will need to prove that your digital acquisition plan will eventually make you more money than you spend. To do this, your unit economics need to be buttoned up on two fronts: 1) spend per customer (CAC) and 2) revenue per customer (LTV).
For example, one of our clients is a health-conscious meal kit delivery subscription service. Over the last couple of years, this vertical has become increasingly popular — and with that popularity has come increased competition. This has driven up CAC considerably. To optimize for these highly competitive market dynamics, our strategy out the gate was to keep CAC low in order to learn the LTV of those customers. And based on the cost of a weekly subscription, we knew that newly acquired customers would need to subscribe for at several weeks to break even on that target CAC. Understanding this “break even” delta helped inform the client’s messaging and offer strategy and allowed us to identify, build, and execute campaigns that brought in customers most likely to subscribe for a longer period of time. This gave us the data we needed to fully understand their LTV.
While CAC calculations are great for understanding unit economics at the short-term individual customer level, oftentimes your CFO will also want you to paint a clear picture around what profitability could look like in the long-term. This is especially important knowing that a handful of customers will inevitably churn out over time. This is where calculating LTV comes in handy. Depending on the nature of your business, there are a couple primary ways to go about this:
- Perpetuity Model: This is best suited for businesses with a subscription model (as in the example noted above) where revenue per customer is more or less constant per month. The premise is that a certain percentage of customers will stay while another percentage will unfortunately leave. LTV in this instance is simply “monthly revenue” divided by “monthly churn.” Although this model can help estimate LTV on a forever-basis, it’s a great way to assess what LTV (cumulative revenue) for a set of customers could look like in shorter time frames (12-24 months) as well.
- Cohort Model: This is best suited for businesses where the amounts and timing of transactions are variable (think: e-tail). These businesses will typically use digital marketing tactics, like email, to promote discounts or other offers that incentivize customers to come back for more. The goal here is to understand, from among an average of all those new and repeat customers, what LTV might look like. However, as opposed to the purely future-looking perpetuity model, you need at least 8-12 months of customer purchase data to make an accurate prediction here. To run this calculation, group customers at the start of the any given day or month and then count cumulative transactions for that group of customers over time. Do this for multiple start times — and then layer that data on top of each other to create a curve that shows how, on average, revenue could grow and eventually plateau over time.
Another client of ours works in the insurance, loan, and mortgage business. At one point, we were asked to help them forecast the long-term value of all mortgage leads generated on a monthly basis. Why? Because mortgage leads take an average of 45 days before they actually become revenue for a bank. So, given this long lead-to-purchase lead time, our client wanted to know when they could feasibly expect to make a profit on their marketing efforts. The cohort model proved to be a good solution for addressing this question. By grouping all past customer acquisition efforts by month over the course of 12+ month period of time — and then identifying all future revenue attributed to it on a month-by-month basis — we were able to spot a clear trend that helped us predict, with confidence, how much our client should spend moving forward (per month) in order to achieve their specified growth goals, all without overloading their team.
3. When will you get make that money back?
Finally, in an effort to manage cash flow and, more importantly, temper investor expectations, your CFO will likely want to know when your digital customer acquisition efforts will finally turn a profit. This is where all the LTV measurements from above will become a true game changer.
With standard quarterly (or monthly) financial reporting, costs and revenues are reported purely on an accrual basis. The problem here is that by only looking at revenues vs. spend in-quarter, for example, you fail to paint the entire LTV picture. Within a given quarter, your CAC spend may have outpaced revenues, which can be extrapolated in this very narrow time frame as contributing to a loss in profits. Looking at the bigger picture, however, might tell you a different story: that cumulative revenue actually surpasses CAC spend over time. Therefore, you’ve successfully managed to turn a profit on your digital customer acquisition efforts (just not necessarily if you look at the numbers within the confines of a single quarter).
Here’s why this distinction is so important. By boiling your digital customer acquisition efforts down to unit economics around LTV, you can add value to traditional financial reporting that helps business leaders make a direct connection between performance marketing to future business growth and profitability in an entirely new light — and earning you a seat at the proverbial revenue table.
Are you ready to become a Digital Economist?
This now officially brings a close to the first wave of our Digital Economist blog series. Throughout the series, we’ve given you an in-depth look at the four key pillars of a successful digital customer acquisition program to help you understand the importance of approaching digital marketing through the lens of a Digital Economist. Now, it’s your turn to put everything you’ve learned into action. Are you up for the challenge?
To learn more, be sure to download our whitepaper, “The Rise of the Digital Economist.”
- Digital Economist