Why Using the Wrong Metrics is Hurting Your Business Part 1
Using the right metrics to measure your marketing efforts is essential to really know what you are getting for your dollar. Edward Nevraumont, Chief Marketing Officer at A Place for Mom, offers up Part 1 in a series of articles he hopes will help senior living executives spend their marketing dollars more efficiently.
If I told you that you could give me a $1 bill and I would turn around and give you a $5 bill, that would be a pretty good deal. Your next question should be, “How many times can I give you a $1 bill?” While negotiating to get $6 instead would be even better, there is far more benefit to be achieved by just scaling the good thing you have going.
Good marketing works the same way.
You want to find marketing ‘channels’ where you can spend money that will drive customers into your sales funnel. And you want to make sure the value you get from those customers is more than the cost you spend on that marketing channel.
It is all easier said than done.
What Are Some Potential Challenges?
Let’s list off some of the questions you might be asking yourself:
- How do I know which channel a customer has come from?
- What if a customer has interacted with more than one marketing channel? How do I know which is responsible for bringing me the customer?
- What if a channel doesn’t bring me any customers, but it increases my sales conversion of the customers my other channels bring me?
- How do I even know what a customer is worth?
These questions and more I hope to answer over the coming weeks. In each post in this series I hope to give you a little more structure to help you think through these challenges. To start with, we’ll discuss how you value a new resident.
What Is the Value Created Each Month of Stay?
While paying $1 for $5 is a great deal, paying $1 for $0.50 is pretty terrible. Before we start figuring out the true cost of marketing, we need to determine what the true value is of a move-in, in other words, what is your $5 bill worth?
To begin, you can look at your gross monthly revenue from the move-in. This should be easy: It’s just the total charge of room and care for the particular resident. But the monthly ‘value’ of the move-in is a little more complicated. You need to subtract out all the incremental costs of having that resident in your community. What do I mean by incremental?
Here are some examples of what is NOT incremental:
- The cost of the real estate
- The cost of the back-office staff
- The cost of the grounds keeping
- Base level of utilities
- Any corporate costs
It should be equally easy to figure out what is definitely incremental. For example:
- The cost of the food the new resident eats
- The cost of any disposable medical supplies the resident uses
- The cost of any outsourced care or additional housekeeping services that are borne by the community
- Additional utility costs (i.e., for additional water used)
Then, there are a lot of costs that may or may not be incremental. Examples:
- The cost of care. (Will you need to increase the hours of caregivers, or will you be able to help the resident within existing caregiver hours by increasing utilization?)
- The cost of kitchen staff. (You may be able to feed one more resident with the existing team, but if you increased the building capacity by 40 residents, you will need more labor.)
Figuring out what exactly is incremental and what is ‘fixed’ is not easy, and it is sometimes easier to just use simple approximations. In most cases the incremental costs of caring for an additional resident are somewhere between 20-60% of their monthly rent and care charges. For the rest of this post I will use 50% to keep things simple, but you should try and calculate the relevant numbers for your specific communities at their current utilization capacity.
So, now you know your monthly value created is approximately your (monthly charge)/2. But you are not done. The next, harder, question is ‚Äúhow many months will the resident stay in my community?‚Äù In the Senior Living industry, this concept is referred to as Average Length of Stay, or ‚ÄúALOS.” For readers who are new to the industry, ALOS may be a bit perplexing, so I will explain in more detail below. If you are comfortable with the concept of ALOS, feel free to skip to ‚ÄúWhat is the Value per Move-In.”
How Many Months Will a Resident Stay In My Community?
Unfortunately, you will not know the answer to that question until the resident moves out. The common way to do this is to take all the move-outs within a given time period and then look at how long they stayed – and then take an average. It definitely gets you an answer, but it has some serious limitations.
The biggest issue is it ignores all your long-time residents ‚Äì and the newer your community the more it ignores. Imagine if your community is a year old. You run this analysis and it will tell you your average length of stay is less than a year (the math requires it will always be less than a year). It ignores all the people who moved in a year ago and haven‚Äôt left yet (this method does the same thing with new marketing channels ‚Äì or even channels that are growing! If you have twice as many leads this year over last year from a marketing channel, then you will have a much higher ‘less than one year move-out rate‚Äô than if the marketing channel was flat).
Thankfully there are better ways (if a little more complicated). The right way to do it is by creating what are called ‘cohort-based churn curves’. That is just a fancy way of saying “how long have previous residents stayed with us before moving on?”
The simplest way to do this is by taking a specific month about four years ago:
- Count how many residents moved into your community in that month.
- Then count how many moved out in the same month, the next month, the next month, and so on, up to the present day.
- You should end up with a chart that tells you your ‘churn rate’ or the estimate of the percentage of residents moving-out over time.
The problem with this chart is that the total count is so low it’s hard to make future predictions – since there might only be a handful of residents who move-in in a given month. So we need a better way.
The key is to combine or ‘aggregate’ the data. Instead of looking at one month, we can look at many months at the same time. The trick here is to still look at time separately for each group. If we took all of the move-ins from 2009 and then looked at how many were left in January 2010, we would be over-counting ‘one month’ churn – since many of those residents moved in long before December 2009 (like January 2009 for example). Look at every single one for the months in 2009 and then add them up separately.
In fact there is no such thing as ‘length of stay’ there is only ‘length of stay so far’. The best metrics to use are time-based churn numbers. For example, 5% of residents move-out by 3 months. 25% of residents move-out by 12-months. 60% of residents move-out after 24 months, etc. If you build a curve that connects all those data points you might even be able to estimate into time periods when you don’t have data.
In any case, the more data you collect this way the more accurate your move-out curves will be. The drawback is that as you combine this information, it gets ‘stale’. If you want to estimate the percent of residents that will move-out after one month, you are better to use data from the last couple of months than try to estimate it with what happened back in January 2009. Another way is to look at other communities similar to yours. That gives you more data, with the drawback of making it less relevant (one community may be better run than another and have a lower expected churn rate). Everything is a trade-off and it’s often about looking at the data a dozen different ways and using your judgment to figure out what the ‘real’ answer is.
Once you have a time period you are comfortable with you can take an average to estimate how long an average resident will stay in your community after they move-in. (Later I will talk about how you can change this number based on the marketing channel to better estimate a channels value, but for now, let’s assume all channels are the same).
To figure out your average just use this math:
[(Month 1 x Residents left) + (Month 2 x Residents left) + (Month 3 x Residents left) + etc.] / Residents moved-in
That gets you your average lifetime stay length for a new resident. It actually under-states the length since we are ignoring the value that comes from residents staying longer than four years, but it’s a fine start.
What is the Value per Move-In?
If you skipped the last section, welcome back. Now that we know the length of stay and the value created per month of stay, calculating the value per move-in is just a function of multiplying the two results. That is your ‘value per resident move-in’, or to tie it back to the beginning, that is your $5 bill.
Economically speaking, any time you can get an additional resident to move-in for a lower cost than that, you should do it.
You likely have tons of questions and challenges now:
- How do I tie my spend to a specific resident moving in?
- How do I know if I would have got that resident to move in anyway, without spending that money?
- But if I spend $4.90 to get $5 and do it over and over to fill my building, how will I pay for my fixed costs?
I will cover all these questions (and more!) over the coming weeks. But before I do, let me reiterate the importance of this “value of an additional move-in.” Without knowing how much an activity is worth, it is very difficult to figure out if you should be doing more or less of it.
If you know that the bill I am handing you is worth $5, you will be more than ready to hand over $1 over and over again (and do it quickly before your competition does). However, if you are unsure what that bill is worth, you will be very hesitant to hand over the $1 bill you already have. Maybe you will anyway because you were told you had a specific marketing budget to use, but that’s a very bad reason to spend money.
What Does This Look Like for An Example Community?
Say Senior Living Inc’s monthly charges are $3,000. Their monthly incremental costs are $1,000, so their monthly value created is $2,000. They look at their move-out curves and it looks like the average resident stays about 20 months before moving out. That means the total value created with a move-in is $2,000/month x 20 months = $40,000!
Looking at it that way, it’s a lot of money. This is why one of the best metrics of success for a community is keeping all of their rooms in use. If this community has 100 beds, the difference between being consistently at 90% full and 100% full would be $2,000 x 12 x 10 = $2.4 million per year! That’s a lot of room to spend more on marketing to fill up the community.
But it only works if you can guarantee more marketing spend actually fills up more beds.
More on that in my next column.