This is part three of our series on startup metrics and why financial advisors need to care. In part one, I discussed why financial service professionals, including insurance agents, wealth managers, and financial planners, should be savvy to their cost of acquiring a customer across their channels. In part two, we delved a little deeper into two of the most important metrics – customer lifetime value and churn. I highly recommend you read both. They’re on the longer side, but will arm you with what you need to know going into this article.
So, we’ve now discussed quite a bit on metrics. As I have mentioned in the previous two blogs, this series was inspired by an advisor who had fired a few clients and reaped higher profits for his trouble. It was all about becoming a quantitative advisor and not following your gut. To whit, my last few posts have been a little bit heavier on the metrics and math side. Unfortunately, this one will be no different. But there’s light at the end of the tunnel here, I promise. This will be the last metrics piece I write for a while. I have also included a template spreadsheet that tries to combine the major metrics for your tracking purposes. It will help calculate the important metrics for you, you just need to download it and fill in the blue cells with appropriate numbers. However, if you get lost, stuck, or confused, please reach out to me (firstname.lastname@example.org) and I’ll be glad to discuss.
Today, we are going to go through a case study demonstrating how to put all the metrics together. In this case study, we will discuss LTV further. Specifically, we will talk about the proper way to calculate LTV, as opposed to the simple way I introduced in the previous entry. We will then talk about two golden metrics – LTV:CAC and sales payback months. Both of these metrics allow you to get a real sense for how your book is doing and how channel strategies are producing. All combined, this case study will hopefully be demonstrative of how to approach your own book of business.
The Case Study: A Growing Employee Benefits Insurance Advisor
Recently, I helped a friend out with his channel strategy. He owns a group benefits book and had been growing slowly (but surely) over the last few years. Much of this was through referrals and cold calling, but he had also started investing a substantial amount of money into online marketing five years ago. His goal was to find a way to bring more inbound clients to him – employers who would find him online and call him with true intent to purchase. He had, at that point, collected about five years worth of data over five big annual $10,000+ digital campaigns. However, he had never really sat down and crunched his numbers. He was also a bit concerned with how cash strapped he often felt. These campaigns were the most expensive line item of running his business, and they tended to leave him pinching pennies afterwards. He knew they had produced some clients for him, but he wasn’t sure if the value of these clients was enough to keep spending money in such a way. Intuitively, he believed that this marketing provided enough clients to keep growing well, but he wanted to double check.
This is where I came in, spreadsheets in hand (well, on screen at least). I made him a deal – I would analyze his channel strategy IF he let me write about it. He agreed, as long as it was anonymous. And thus, this case study was born!
The Tale of the Tape
Before we start, let’s quickly talk about his business. He was selling group benefits insurance to employers. On average, he was generating premiums of approximately $31,765. His overall annual income had come out to $84,219 over 34 clients, or an average annual revenue of $2477 per client. This meant that his average commission was around 7.8% for each client per year.
Over the online channel, he had generated 11 new clients over the last five years and six new clients over the last three years. His online marketing cost averaged out to just over $12,000 / year over the last three years. Off the bat, I knew this was going to be messy.
Calculating the Contribution Margin and LTV
Now, his data was a touch messy, but not incomprehensible. I dug through his revenue streams over the last few years and decided to start off by figuring out his client lifetime value (LTV). Now, if you recall the previous blog, I stated that simple LTV was calculated as so:
This formula is a great way to eyeball LTV. With just the average annual revenue of your clients and the annual churn percentage, you can very quickly get a rough idea of how much your clients are worth. However, the simple LTV formula isn’t exactly right. Why? Because a proper LTV should take into account the contribution margin a client generates, not just their net revenue. If I give you $2 for a coffee, the net revenue is $2. But the contribution margin takes into account that you spent $0.50 on coffee beans and $0.15 on a cup:
In the case of a coffee, your contribution margin would be $2 – $0.65 = $1.35 per cup. The same logic applies to clients. If a client generates $1000 in revenue for you, but you send them a $200 bottle of wine every Christmas, your contribution margin on the client is $800. If you spend a further $200 worth of your time with them yearly, the contribution margin drops to $600. This is what a client is actually generating in cash flow.
A more correct version of LTV takes these variable costs into account. Note that these costs are NOT related to acquiring the customer – the CAC exists BEFORE you incur any variable costs. Instead, when talking about variable costs, we are focused on the costs you incur to keep the client as an income stream afterwards. This is the cost of servicing the client every year. Thankfully, for most advisors, this is a fairly easy calculation. There are no expensive bills of materials or material costs that need to be worried about. Instead, advisors just need to consider how much time and money they put into servicing their clients annually. This likely breaks down into the number of hours they spend with a client per year and the amount of dollars they spend on their clients as part of their client success strategy. A good LTV, therefore, looks as follows:
Our advisor, unfortunately, didn’t have great logs on his time spent with clients, but he had a general sense that he was spending maybe six hours per client per quarter. We decided to assign an hourly rate of $30 / hour for his time. Therefore, annually, he was spending a further $720 (24 hours x $30 / hour) per year on clients in labor costs. I asked him about any other material costs (e.g., that bottle of wine mentioned above), but he wasn’t sending out any gifts (!!) to his clients. Therefore, I calculated out his contribution margin as follows:
Average Annual Contribution Margin = $2477 – $720 = $1757
So, I had the numerator for calculating complex LTV set. Next up, I needed to get through his churn records. Going back 12 months, I saw that he had started the year with 35 clients, had added four new ones, and had lost five. I compared it to his previous years, and noted that this was about average. I decided to calculate churn based on that. If you recall, the equation for churn is as follows:
By starting with 32 and losing five, we calculated a churn of 15.6%. Notice that I did not take into account the four newly added clients – they matter for his overall growth rate, but are irrelevant for calculating churn. Just as importantly, I did not look at the churn of only his online clients. This is because there were only ten of them. As mentioned in the previous article, this is a very small sample size to make predictions of churn on. I gut checked to make sure he wasn’t picking up really loyal clients through his online channel, and found that he had lost 6 / 10 over the last five years, which would put him just a touch under 10% annual churn. The ratio wasn’t far enough off, however, for me to suspect that these clients were behaving differently from the rest. I was likely just seeing variance in small numbers.
So now I had both my contribution margin and my churn – it was time to calculate LTV:
With $1757 in contribution margin and 15.6% churn gave him an LTV of approximately $11,245. This actually came as quite a surprise to my friend. He had assumed that his clients were worth a lot more, especially if he was investing this much to acquire them. But the numbers were pretty clear – his churn was not pretty and the value of his clients collapsed accordingly.
Okay, great. So knowing that, I needed to figure out his CAC next. If you recall from last week, CAC is calculated as:
This one was easy to establish, as he was using Google Adwords primarily for acquiring his clients and we could easily see the results. Checking out his spend on marketing, he had spent $12,328 on average per year. This had led to ten new client accounts over five years, or two new ones per year. On a per client basis, therefore, his marketing costs came out to about $6,164.
Likewise, for labor costs, we estimated it would take 10 hours per client to take them from prospect to close. Once more, I valued his time at $30 / hour. So that came out to an additional $300 in costs. This meant that, overall, he had spent $6464 per client on acquisition.
So, he was spending $6,464 and was earning about $11,245. So, what did this mean?
LTV:CAC Should Be Greater Than Three
To answer this question properly, we need to understand the golden metric – LTV:CAC.
For our advisor, who was creating $11,245 in lifetime cash flow at the cost of $6464, we have a ratio of 1.78x ($11,245/$6464). Now the LTV:CAC ratio tells us is how much cash flow you generate, over the lifetime of a client, for every dollar you spend in acquiring that customer. In other words, for every $1 our advisor spent on acquiring a client, he was generating $1.78 over the long run in contribution margin. So was this good?
Nope. Not good.
In fact, any ratio less than 3x is generally considered poor. Let me repeat that. An LTV:CAC ratio of less than 3x is considered not great.
Now, as a savvy reader, you will argue with this. You will point out that if you’re spending $1 to generate $1.78 in the long run, this is a great formula for growth. I mean, if you had a machine that turned $1 into $1.78 whenever you pumped dollar bills into it, you’d be pretty thrilled, right? I know I would. And it certainly is better than the converse – a machine that converts $1 into $0.50. Through my time in tech, I’ve seen plenty of those as well (I once did consulting work for a startup that was generating $0.32 for every dollar in marketing it spent; I offered the CEO that if he just gave me the money instead, I would return $0.75 per dollar instead – he was unamused).
But this is unfortunately wrong. Fundamentally, it mistakes contribution margin for profit. Remember, contribution margin is revenue minus variable costs. What it lacks, however, are your fixed costs. Costs such as rent, administrative overhead, office equipment, staff – these are all fixed costs. To quote Investopedia:
“A fixed cost is a cost that does not change with an increase or decrease in the amount of goods or services produced or sold. Fixed costs are expenses that have to be paid by a company, independent of any business activity.”
For a client to be profitable, then, they need to not only have a strictly positive contribution margin (generated more than $1 for every $1 spent on attracting them), they also need to have enough of an extra kicker to help cover a portion of your fixed costs. In other words, a ratio of LTV:CAC at 1.78x means that the client is generating a positive contribution margin, but that they are not earning you enough to help deal with the fixed costs. These will never be very profitable clients in the long run. At best, they may be at break even for profit. At worse, they distract you from more valuable clients who would earn you significantly more, while not adding much of anything to your bottom line. In other words, my friend’s online marketing was not an investment. It would never really payback in a truly profitable way. Instead, he was dumping cash into a system that was going to maybe break-even in the long run, all while costing an arm and a leg upfront. Just as importantly, he was wasting cash that could have been better spent on delighting his current clientele and reducing the churn.
Financial Advisors Should Know Their Sales Payback Months
Now, I just mentioned the upfront cost. This is actually a very important part of the equation. Think of two scenarios. In one scenario, you acquire a slightly profitable customer for $6434, she returns the cash to you within a year, and you reuse it to acquire another one. Assuming you’re not constrained by time spent servicing her as a client, you can grow fairly rapidly. Every year, you could reinvest. Now, compare that to a situation where the client takes ten years before you can reinvest. Now your growth rate through reinvestment is one customer every ten years.
Your sales payback months looks at how long it takes before a client pays back their upfront cost and you can reinvest. It is a great metric. It helps you understand when a client has recouped the cost you spent to acquire them in the first place. Consider the three scenarios in the following graph:
For all three scenarios, we used a CAC of $6464. The difference for each scenario was the contribution margin. The orange line represented a contribution margin of $1000 / year. In this scenario, after 60 months, you still would not hit break-even. Scenario three showed a contribution margin of $3000. Here, it took just over two years to recover the initially spent money. This too wasn’t ideal, but was better.
Scenario two was what our advisor was dealing with, with a $1757 contribution margin. For every client he brought on through online marketing, he needed roughly 3.67 years before they paid back their acquisition cost. That is a very long time. It means that even if all goes well, it would take him 3.67 years before he would be able to reinvest the dollars spent into his business. That is, if he picked up a client in early 2012, only now would he have recovered enough money from the client to spend on picking up another client (late 2016). Unless our advisor was absolutely flush (he wasn’t), this would constrain his growth immensely.
So what should a savvy financial services professional be aiming for? Well, a sales payback under a year is ideal. Anything under 18 months is reasonable. But beyond that point and it’s time to start changing your channel strategy up. Thankfully, calculating your sales payback for a single client is fairly easy:
Now, there’s a problem with using this equation alone and that problem is churn. Remember how I said churn was murder before? It remains true here. See, our advisor, with a 15.6% churn rate, had a ⅙ chance of losing a client every year. If he lost a client before the 3.67 years it took to recoup his investment, he would never break-even on a client. So, what do we do? Well, we add in churn. Take a look at the following chart:
In all four scenarios, we have a CAC of $6464 and a CM of $1757. The different lines here represent different levels of churn. At a churn of 0%, it will take 3.67 years to recoup the investment. At a churn of 15.6%, it will take over five years. Pretty spectacular, right? Unfortunately, there’s no simple equation to compute this. However, check out the tab called “Sales Payback Chart” and feel free to play around with the variables to create charts that are demonstrative for you (I’ve protected cells that are not in blue).
Conclusion & Cheat Sheet
Okay, we’ve covered a lot in the last three blog topics. So a quick breakdown:
CAC – What it costs upfront to acquire a client
Contribution Margin – What the customer is worth annually in revenue minus variable costs
Annual Churn – Likelihood a client leaves in any given year
LTV – Lifetime value of a client
LTV:CAC – Golden metric! Should be greater than 3.
Sales Payback Months – How long will it take to recoup your upfront investment costs. Target less than 12 months.
You have the spreadsheet! Download it and start filling it out to fit your own numbers. If you’re not sure what those numbers are – now is the time to start figuring them out. I honestly cannot emphasize this enough – financial advisors who get smart on their metrics will win in the long run. Otherwise, you’re basing serious strategic decisions on gut feel and hoping for the best. Let me know how it goes in the comments, and feel free to reach out if you need any help (email@example.com). Also, please subscribe!