There are several ways to calculate customer acquisition cost. One of the more traditional is the total sales and marketing expenses for a given period divided by the number of customers acquired during the same period. This calculation should include salaries and standard variable compensation as expenses.
Hayes calculates customer acquisition cost payback as the total marketing and sales costs in the given period divided by the MRR associated with newly acquired customers in the same period multiplied by gross margin as shown below:
The benefits of calculating CAC Payback this way include understanding the additional costs that go into supporting a customer (cost of goods sold) and learning whether the average tenure of a customer meets or exceeds the amount of time it takes to earn back the money spent acquiring the customer.
For example, if you charge customers $100 a month and it costs you $1,200 to acquire a customer, you have a 12-month payback period.
Remember: When calculating CAC, you only include expenses that occur in a "steady" state. For example, severance packages from layoffs should hopefully be a one time thing and not a consistent expense–so they aren't included in the CAC Payback formula.
There are several ways businesses try to reduce CAC, some of which are problematic. These strategies include:
Because payroll is typically the most expensive line item for any company, in theory, we understand why so many companies have used them to increase profit margins (at least temporarily). Instead of focusing on the layoff strategy, let's start with a more nuanced chapter.
Business leaders talk themselves into "forcing efficiency" by reducing headcount in inside sales, sales engineering, marketing, and customer success. However, no department is safe, and RevOps should do several types of analysis before pulling this particular rip cord.
Andrew focused on a few examples within sales:
"The most common ratio people think about when it comes to sales is SDR to AE. But there's also span of control. Look at your manager ratios. How many AEs can a manager support? How many solution consultants or pre-sales representatives per account executive? We used to aim for two and a half or three to one solution consultants per upper-end mid-market or enterprise account executive.
"I think about the way that comp plans work. If you have fewer reps retiring quota, you're giving away a larger slice of the pie for every dollar you bring in."
Andrew pointed out that while changing ratios is a strategy that looks good on paper, it doesn't always end well.
"You need to remember that if you're asking a group of AEs who have never really been full-cycle AEs to go prospect AND run sales cycles at the same time, and you've never really asked them to do that before, then you'd better have a good way to keep them focused on high-quality accounts."
We'll get into this strategy in more detail later in the article. We've seen many companies reduce inside sales headcount (or eliminate the position altogether), and many non-sales people have been surprised by the ramifications. Before you reduce inside sales:
Chances are high that having a few inside sales representatives pays for itself, particularly when pipeline productivity takes a nosedive in month three of every quarter.
Enterprise companies have big budgets and experience greater stability in down markets. They also are the most demanding category of buyers. Think Alexis from Schitt's Creek levels of demanding.
If your product doesn't check all of the security, accessibility, and other boxes demanded by most enterprise companies that sell to a global market, you're going to spend a lot of money getting it there. They'll also make demands about single-sign-on, integrations, support response timelines, and other huge lifts that increase development costs.
Andrew said, "People too often discount the true cost of going upmarket. There are a lot of hidden costs. Sure, you can double your deal size. But if your costs scale just as much, you haven't accomplished much."
Going upmarket sounds excellent, but evaluate your product honestly. Is it ready? Does it fit into enterprise use cases? Or are most of your sales mid-market or smaller, and you're trying to force yourself into a market you need more time to tackle?
Whenever there's a softening in the market, people clamor back to the tried-and-true strategy of selling more products to our existing customer base. Of course, sometimes we don't have more products to sell, but we switch to annual contracts from monthly contracts, aim for multi-year renewals, and get more creative than we normally would to retain unhappy customers.
Raise your hand if this sounds familiar.
Where companies struggle are:
Data seems to point to the answer to the first question being "No." Product-led growth is responsible for upsells a measly 10% of the time. Using in-product usage (or lack thereof) to create calls to action for support, creating regular support calls with the customer, and incentivizing the sales team to mine existing accounts for expansions are all commonly deployed strategies.
Product-led growth is great. But as we've covered in "Expansions," it's not magic or a replacement for a consultative sales approach (which you can read more about in our interview with Stephen Moock). It also only makes sense for some products.
If your product isn't straightforward to use and requires human intervention during implementation (or for your customers to see the total value–and be honest with yourself when evaluating this tricky aspect), cutting your sales and support teams is not a good way to retain or attract new customers.
Another tricky complication with product-led growth is a lack of options for human interaction.
Hayes said, "There's something I see with some of our customers with a PLG motion with a large self-service customer base. There may or may not be a natural mechanism to engage and expand. In some cases, effectively engaging them with sales may be like a cold sales cycle."
Quantive, on the other hand, has built a mechanism for end-users to raise their hand when they want to learn more about a product or feature. Drew said, "We have implemented an SSQL or Self-Serve Qualified Lead. In the last couple of years, we've leaned more heavily into a sales-led motion. We're using SSQLs as almost a flywheel to help drive revenue and expansion. Our conversion rate is probably 10 to 20x on a self-serve qualified lead than on an MQL, if not much higher."
Expanding into a new market or building a new product in record time may seem like a simple theme to do to someone who has never been responsible for anything client-facing in B2B SaaS. The rest of us cringe and then crunch numbers to figure out how best to support such a daunting task.
Pivoting in this market without historical learnings to guide us is risky. We can mitigate some of the risks by getting extremely efficient in operations and then analyzing the data we do have. The first place Hayes recommended ops focus on is evaluating whether or not your CRM has the firmographic data you need. Do you have intent data? Have you been recording past engagements with marketing campaigns, sales, and customer success?
Hayes added, "Have you revisited your scoring, tiering, or anything you're doing for segmentation? When you get these foundational things wrong, it creates friction and distraction for your sales reps. For example, a rep looks at an account and sees that your system lists a thousand employees, and they go look on LinkedIn and they have ten employees-- and suddenly there's no trust in any of the data."
It's also critical to have funnels dialed in. Funnel stages throughout the buyer lifecycle will help operations when it comes to understanding integration issues, process breakage, sales productivity, and where there are areas ripe for optimization.
Regardless of your organization's strategy, the most critical component for success is account executive productivity. If your sales team can't be productive, the plan can't succeed.
Territory planning is complex at best. Even if this isn't your first rodeo and you distributed territories according to population density or target account density, this will only guarantee that some will have success.
The unfortunate part is that it isn't always the salesperson's fault. If they've inherited a "greenfield" or territory with more accounts in a market that hasn't been targeted by marketing yet, they'll have a more challenging time hitting their number.
To ensure account executives have the best possible chance of hitting quota, RevOps needs to figure out a way to equally distribute accounts in the ideal customer profile that are also ready to buy. This methodology is called dynamic book management.
In order to use this methodology, you must implement many of the core concepts we've covered in this article. These include:
Then marketing and sales must work in lock-step to socialize the same message.
Sounds simple, right?
You're right. It's hard. But from what we hear, it's worth it.
Instead of doling out territories that should be equitable, salespeople are only supposed to focus on the correct accounts sending the right buying signals at the right time. This means less time wasted on cold prospecting, which also means that marketing must have their messaging and first-party signals dialed in. To make this work, your data needs to be streamlined (which means integrated, normalized, and qualified).
You also need to start measuring buying signals. You need to have funnel analytics in place to ensure that the sales team is reaching out to the right people at the right time, that everyone is working equally hard, and that you can constantly fine-tune who, how, and when people are elevated to sales.
"From a RevOps perspective, one of the things that's most exciting for me is achieving market equilibrium. You think about your supply of accounts and demand from your reps in terms of quota capacity. What this allows me to do for the first time is to see how the demand and supply curves differ or where they meet.
If we have books of business assigned out to all of our sales reps and they're only engaging with 50% of their accounts, that might tell me that we're giving them too many accounts to work. But before, on a traditional territory model, it was almost impossible to accurately measure this and adjust for it in real-time. We also can spot and correct many bad behaviors that occur, like obsessing over an account that will never actually close."
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