Investment Dissection: Homebase.ai
[Note: My posts on this blog vary in length. The last one was long. So is this one. The next few will be shorter.]
I recently made an investment in Homebase.ai, a “smart apartment” platform. In this post I’ll walk through how I thought through that decision. I’m doing this for two reasons. First, I think it’s good practice to keep a ‘decision journal’ that one can review and learn from. Second, I’m hoping that others can point out things I missed or where I could be wrong. For confidentiality reasons there are many data points that I can’t share. But that’s okay because I want the focus here to be on the process.
Here are roughly the steps I went through, along with how my thinking on how the opportunity evolved over time.
Step 01: Intro
I heard about the opportunity from a friend who had invested at an earlier stage. The company was now raising money at a significant increase in valuation (roughly a 5x increase in ~18 mo) and had seemingly good traction. There were also two other similar companies that had recently gone public via a SPAC: Latch at a ~$1.5 billion valuation and Smart Rent at $2.2 billion. Homebase was much smaller and earlier stage.
My Thought Process
(First, an aside: when evaluating investments I think of them in terms of probability distributions. The shape of that probability distribution adjusts as I get more information. As I talk through my thought process here, I’ll reference this payoff distribution frequently. OK, let’s get back to it.)
At this time the SPAC market was still quite hot. While my general view was that the SPAC market was overheated and valuations were getting inflated, I have learned to both develop my own independent opinion of a company’s worth and to understand that – when actually seeking liquidity – the price of an asset is what the highest bidder is willing to pay. I was also aware that while the hot SPAC market could disappear at any time – it hadn’t yet.
Moreover, while this company was still early stage, the fact that two competitors had recently gone public told me a few things. First, at a minimum there were clear, public comps available. This would allow me see how Homebase compared from a metric-to-valuation perspective. Second, given the general SPAC frenzy, I thought that this might make it easier for Homebase to go public via a SPAC in the future since the approach had been ‘proven’. Third, I figured that even if Homebase didn’t go public that way, there were now at least two competitors in the field with a lot of cash that could potentially acquire them down the line. Finally, I thought that the fact the fact that two companies in this space had gone public might indicate that there was something fundamentally successful about the business-model / timing interaction (i.e. it was a sign of a fundamentally good business model at the right time in the market and not just some rockstar team or fluke of luck). Given how hot the SPAC market was, however, it was also possible that this was just another company being sold on hype (I’m looking at you, WeWork).
For all the reasons above, this deal immediately caught my attention enough that I decided to investigate further. Given that the company was already beyond a typical “seed” or “pre-seed” valuation, in my view a ‘spray and pray’ 1/N approach wasn’t appropriate. Therefore, I knew that to even invest at all I needed to feel comfortable that there was a real business there at a reasonable valuation. However, I also thought that the SPAC route might provide a potential far right tail on the distribution, which might effect how much I would invest. I’ll talk more about this later.
So I started digging.
Step 02: High Level Market and Competitor Analysis
What I Did
Though I wouldn’t always do this step first, because of the two recent SPACs, there was a treasure trove of relevant data that I could find just by looking at the public documents that each competitor had provided to investors during the process (which were available on their websites), but it was also relatively easy to find other people’s analysis of those companies. I could then triangulate at least some of those data points with other sources just to make sure the numbers seemed reasonable.
I first started with the general market and my knowledge about it. Homebase’s general market was the “rental home / apartment space” since they are (mostly) selling to contractors building new buildings and landlords. I knew that real estate generally was the largest asset class in the world so that part was fine, and intuitively I felt comfortable that the size of the rental market was pretty large. A quick search told me that there are about 47M rental homes in the US and 93M apartments in Europe. Without nitpicking, that seemed ‘big enough’ to me. Now I didn’t yet have a feel for what ‘end’ of the market (i.e. luxury, mid-market, low-income, etc.) Homebase was really targeting so I didn’t do a deeper analysis yet on that, but I did make a note to come back to that later. I also knew that real estate was likely undergoing a significant transition, which had only been accelerated by COVID: more remote work, at least a temporary flight from large cities, and likely a more permanent reduction in demand for much commercial space. That said, people still needed a place to live, so in aggregate residential real estate would likely continue to be needed. I also knew that, at least prior to the pandemic, Millennials were renting longer and many said they preferred renting over owning. (I didn’t evaluate whether or not that had shifted due to the pandemic, which I probably should have). However, I did think quantitative easing coupled with the pandemic was likely to continue to push property prices higher (at least temporarily), which would make it more difficult for folks to afford to buy even if they wanted to.
I also believed in the general trend of digitization of the home/apartment. Products like the Nest smart thermostat, Amazon Echo, Google Home, etc. continue to grow in penetration, and it seemed reasonable to me that landlords were a next segment.
In short, the general trends seemed favorable.
Next I took at look at the financials. While I can’t talk about Homebase’s financials because they are confidential, I can talk about Latch’s. Take a look at just a few (these are from their SPAC presentation and so were accurate as of that date):
- 154% Net Dollar Retention
- 100% Gross Dollar Retention
- 6.8x LTV/CAC
- 6.3 year average SaaS contract term
If you compare those metrics to other public SaaS companies, those are near the top of the list. Importantly to me, Smart Rent had similar metrics so this said something about the general sector/model and not just about one company.
My Thought Process
There were a couple of things I took away from the above exercise. The first was that, given unit economics, unless I was missing something (which I was very aware I could be), the fundamentals of the business seemed pretty good. The second was that, while there were some network effects at play, this didn’t feel like a “winner take all” market, though because of the high switching costs (is a competitor’s electronic lock going to be so much better that you’re going to want to switch out all the locks in your building again?), I figured there would be a bit of a “land grab” dynamic, where part of the game was simply getting to scale quickly and “grabbing” as much territory as you could. In this scenario I figured the most likely outcome is an oligopoly situation.
From my research above I figured that the market was large enough that Homebase still had a chance to become one of the large players. This extended the right tail. However, I also figured that even in the situation where they become only a “medium size” player, that positioned them reasonably well to be fought over by any other bigger players with large balance sheets. Not a bad place to be. This shifted the ‘mass’ of the distribution right. The main risk then (from this perspective, anyway) was that they would grow so slowly that they wouldn’t be able to capture a footprint large enough to be valuable.
Step 03: Zoom in on the Company
What I Did
The first thing I did was speak to the team. While what I look for in teams is beyond the scope of this post, generally speaking what I’m looking for falls into two buckets: individual level things (e.g. intelligence, drive, self-awareness of a particular kind, relevant experience, etc.) and team level dynamics (is the team truly aligned on the mission, strategy, risks, their respective roles, etc.).
I again won’t go into a lot of detail here for confidentiality reasons, but I did speak to folks on the team and tried to understand their backgrounds, roles, and outlook. The reality – by their own admission – was that the management bench wasn’t that deep and, at least on paper, wouldn’t be what you’d consider a ‘dream team’ compared to their competitors. It was also true that (some) of their metrics were not quite as far along as their competitors had been at the same age. Finally, they were dependent on one particular relationship that was tremendously powerful for them but also could be problematic if that relationship went bad.
On the flip side, there were many positives. First, the reason some of the metrics were not quite as far along had to do with some specific strategy choices they made early on which would cause them to move a bit slower at the beginning but then – if you believe their thesis – would allow them to scale more quickly from then on. To me, this thesis was the crux of the differentiation and so the question became “do I believe it?” More on this later. Lastly, partially because of this strategy choice (among others), Homebase had gotten nearly as far as competitors had in the same amount of time, but with substantially less capital required.
My Thought Process
Now here’s where I might start to get a little controversial. See, I didn’t necessarily take the lack of an existing rockstar management team as a negative. In fact, this actually only reinforced the fact that this was likely a good business to be in. Why?
Warren Buffet has a famous say that goes something like this: “When a management with a reputation for brilliance tackles a business with a reputation for bad economics, it is the reputation of the business that remains intact.” I think this is a wise statement. But then I would also argue that a version of the contrapositive is also true: if you see a business with good economics with only a “good” (as opposed to great) management team, it’s probably an indication that the underlying business is a good one to be in. Think of it like a movie star. If someone is a movie star, they are usually talented, good looking, or both. In aggregate, looks + talent needs to cross some threshold. The less good looking they are, the more talented you can probably infer they are (or the son/daughter of the producer). In my view this actually decreased the weight given to the left tail of the outcome distribution.
Beyond this fact, the team readily admitted their weaknesses. Self-awareness and humility (at least of a certain kind) can be very helpful to a team if it means they will do what is necessary to supplement or replace that team to shore up gaps. This slightly shifted the probability mass to the right.
The obvious other part of this is understanding the relative valuation of Homebase vs other competitors (and other deals generally). Based upon the metrics and comps, the valuation cap and discount on the SAFE appeared to value Homebase at a reasonable discount given its earlier stage and less mature management team.
Step 03: Contraindications & Deeper Dive
What I Did
By this point in the process I was leaning towards making an investment so I flipped to the risk side. I asked myself a few questions:
- (1) Assume things didn’t work out well – what are the most likely reasons why?
- What evidence do I have today to suggest how (un)likely these are to occur?
- How aware is the team of these these things and what plans to they have to reduce their probability, impact, or both?
- (2) What are the core assumptions that must hold true for this to be a major success?
- Do I believe they’re true?
- Do others I consider credible in the relevant area believe they are true? If not, what is their rationale and do I agree with that?
- (3) What evidence, if I found it, would cause me to change my mind?
- Does that evidence exist?
- How can I find it?
Using this as my guide, I came up with a specific list of questions for the team and asked them to provide answers and relevant information where possible.
Going through all of this in complete detail would make this post even longer than it’s already going to be, so I won’t do that here. For now I’ll focus on one of the core assumptions I spoke about previously, which had to do with a particular part of their strategy that was different from their competitors. For this particular point, I tried to drill in to understand why they thought their approach was better. I saw the logic and merits of their approach. But I could also see the risks and downsides. Ultimately, I felt I couldn’t determine which approach was better. More on this later.
My Thought Process
My goal in this process is two-fold: first, to maximize the amount of information (in the information theoretic sense) that I get while keeping the burden on the management team in check. Second, by hearing (or reading, which I personally prefer) their responses, I get a deeper insight into how the management team thinks about these issues and how deeply they’ve thought about their business.
I didn’t get all the answers I asked for, but I did get many of them. I would say that the answers I got in return were about what I expected: there were several of the questions that the team couldn’t answer well, simply because they were difficult questions and the future is uncertain. A few of their answers allayed my fears in certain areas, and a few were not as well thought through as I would have liked.
The overall picture their responses painted was mixed: on the one hand it reinforced the lack of depth on the management bench and the amount of thinking they had put into certain aspects of their business. On the other hand, part of the reason they likely hadn’t put much time into thinking through these things was that the business was growing so rapidly that they were understaffed. Net, I would say this exercise shifted my perceived probability distribution to the left slightly.
Step 05: Act Like a Customer
If you’re talking to the management team of a company, it’s probably likely that you’re going to get a relatively favorable view of the organization. Not only are their incentives aligned, but many executives are executives in part because they are good sales people. Thus, when it makes sense, I like to put myself in the position of a buyer.
What I Did
If I actually was thinking about buying Homebase’s products and services, what would I do? I’d browse the website, I’d search the web for reviews, I’d contact and talk to their salespeople…and then I’d do the same for their competitors. So that’s what I did. I found that all three companies were responsive. Latch was the most polished and professional experience of the three and Homebase the least, but Homebase made up for that with some ‘Midwestern hospitality’ (they are based in Kansas City), and the salesperson I talked to was very genuine and friendly. One thing I didn’t do, but should have, was ask each group more directly about the other to get their take; I think that would have been very helpful. I also did the mandatory Googling around to find reviews of the companies, their products, and their app. (Note that my wife and I do own real estate investments so we could evaluate as actual potential customers, I would do something similar even if I weren’t in a position to be a customer.)
In terms of Homebase’s product offering and pricing, there were actually some limitations I was saddened to hear about (namely, they just couldn’t unlock your door if you got locked out), but those limitations were imposed for legal and security reasons, which affected all competitors. The smart lock offering didn’t seem compelling enough to us alone at the moment, but when combined with their wifi solution it seemed interesting. Unfortunately, their wifi solution is much more applicable to larger buildings and/or new construction. Thus, while not a good fit for us at the moment, it was clear to me under which situations it would make sense for us to purchase, and that situation seemed reasonably likely to occur in the medium term.
My Thought Process
From this exercise, it was clear that both Latch and SmartRent were more mature, polished businesses and that Homebase was still acting more like a scrappy, lean startup. It also became clear that there was a time-tracking app that was also called Homebase, which confused some reviewers. On the flip side, my actual experience with Homebase sales and customer service was prompt, friendly, proactive, and helpful. I thought they could do more to further simplify their product and service offering, but as a customer I would easily have considered buying from them.
Some of the limitations on the product and services surprised me, which did shift my distribution to the left, but did so for all competitors not just Homebase. However, it did help me understand further that their solution was really more appropriate for larger buildings, which made me revisit the distribution channels that each competitor was building to make sure that they accounted for this reality. Latch, for example, had gone public partnering with Tishman Speyer, a very large, high-end real estate developer and owner. This was a perfect match for what Latch was trying to do. Homebase had developed a few key distribution partnerships as well; while they might also be good, the uncertainty (to me) was higher than with the Latch / Tishman partnership. To me, this both spread out the mass of the Homebase distribution a bit and shifted it slightly to the left.
Based upon the information provided, however, I now felt I had enough information to move into position sizing. Let’s turn to that now.
Step 04: Position Sizing
The thing about money – at least for the purposes of this discussion – is that it’s a continuous quantity. Therefore, I think a much better question than whether or not to invest is how much to invest. If the amount you invest is zero, that’s fine too. But zero is a quantity just like any other.
Now in many situations it may not make sense to invest $10. Perhaps there’s a minimum investment. You have limited time and attention so you may decide to limit yourself to a fixed number of investments you can track. My point is only that, in general terms, the amount you invest should be a reflection on the confidence you have in the bet, how much it’s worth if you’re right, and how much money you have to be betting with in the first place.
Investing is both a quantitative and qualitative process. Doing the initial assessment of the unit economics, market and company growth rates, and relative valuation were quantitative. Assessing the general market dynamics, consumer psychology, competitive landscape, risk and opportunities were most qualitative. When thinking about position sizing, we move back to the quantitative side. What I like to do here is based upon the information I’ve collected so far, come up with a ‘gut level’ estimate of the right amount of money to invest. In this case let’s call that $X. I then like to use quantitiative methods to calculate an answer and see how far apart they are. If they’re pretty close, I feel good. If they’re way apart, it means I need to reevaluate my assumptions (or my math). I had come up with an initial $X, so now it was time to dive into the numbers.
To assess the amount to invest, I use a modified version of the Kelly Formula. I’ll write a separate post on that at some point, but for those of you who aren’t familiar with it, given the appropriate inputs, it tells you what percentage of your portfolio you should invest in a given bet if you want to maximize your geometric rate of return over time. While a full explanation is beyond the scope of this post, what’s important for now is that it requires you to make estimates of two key parameters:
- The probability of success
- If you win, how much you’d get for every dollar you invested
Let’s start with the probability of success. Using the odds form of Bayes’ Rule and making a judgement based upon everything I had learned up until now, I made the following estimate:
So I assume a 25% chance of success. Not great odds, but for a startup that’s not bad.
Next I needed to estimate how much I would receive if the company was successful. Using some data on the distribution of returns for similarly staged companies (which I’m sorry I don’t have the link for any more) and defining ‘success’ as any company that returned greater than 5 times my money), I took the expected value of the remaining part of the distribution. This left me with roughly 14x invested capital. In other words, assuming I only looked at companies that had made their investors at least 5 times their money, if I had invested in all of those, I would have made about 14x the money I invested.
Plugging that into to my modified version of Kelly’s Formula:
According to this formula, I should take 6.5% of whatever money I have to invest and invest it in Homebase. Now there are a few caveats here. The first is the ‘whatever money I have to invest’ part. I typically think of this instead as “whatever money I’ve allocated to invest in risky, early stage companies. As you can see from my general investment portfolio, this is actually relatively small.
[The second point is more technical for those who are already familiar with Kelly: though many practitioners use half-Kelly as a general rule, in a 1997 paper Thorpe himself described how to adjust the Kelly approach when multiple opportunities are offered. Beyond this diversification adjustment, there is also the degree of confidence you have in your assessment of the probabilities and payoff involved. You also have a time value of money when investing for an extended period. Finally, when investing in an illiquid asset you lose liquidity and hence optionality. Given this, in my view a 50-66% reduction in the amount allocated seems reasonable. More to come on this in a future post.]
Step 05: Adjust as New Information Comes In
One should always be open to changing their mind as new information comes in. The beauty of Bayes’ Rule is that it formalizes this approach.
In the previous step I had estimated the probability of success (which I defined as a return of 5x my money or greater) to be 25%. However, recall from the very beginning of this post that the shape of the right side of the probability distribution was influenced by the chance that Homebase might be able to go public via SPAC. Since first starting to investigate the company, however, the SPAC market had since cooled off due to some comments from the SEC. In my mind, this definitely reduced the probability of a ‘quick, big win’ scenario. In my estimation, I thought that given the company failed, the probability that this had happened was about 25% higher than if the company had ended up being successful. Therefore, I adjusted in the following way (note that the posterior probability from round 1 becomes the prior in round 2 – this is how Bayesian updating works):
As can be seen, the net effect of this was that my estimate of the probability of success dropped by 4%.
The other thing I did to collect additional information was to ask other people I respect their opinions and concerns. While many folks were very bullish, a few folks were skeptical and provided their reasoning. In general most of the differences were due to higher or lower weighting on different factors, but at least one person did provide me with a perspective that I hadn’t considered before. Net, I adjusted as follows:
This further dropped the probability of success to 17%. Let’s stick that number back into my modified Kelly formula:
The recommended allocation has dropped to 3.7%. This may seem small, but if applied to each position in a portfolio, that means the entire portfolio is only 27 positions; many people would still call that a fairly concentrated portfolio.
How did this compare to my initial “gut level” investment amount? It was lower by a reasonable-but-not-crazy margin, which told me it was probably just protecting me from some of my risk-seeking tendencies.
Step 06: Position Shaping
This step isn’t always possible (or appropriate) in the way I’m going to talk about here, but I wanted to include it because it illustrates how I think about investing more broadly.
Your investments are really just an expression of your beliefs about the world. As I mentioned earlier, your position sizing is part of this expression. In many cases then, I find it helpful to first express my general belief about the world in words and then figure out how to express that in terms of positions.
While a full synthesis of my beliefs at this point would make this post even longer, for my purposes here, there were a few key points:
- I fundamentally believed in the continued growth of the smart apartment market
- I also believed that all these players – Latch, SmartRent, and Homebase – had tapped into a model with fundamentally good characteristics, strong unit economics, high switching costs, and land-grab/oligopoly dynamics, some network effects, and recurring, SaaS-type revenues.
- Each had slightly different strategies, however, on how they thought best to create and capture value. None of them were obviously wrong to me and – despite my efforts – I couldn’t get a lot of conviction about which strategy was the best.
- From a valuation standpoint Homebase was the most attractively valued but I could also understand why. And, unlike the public companies, an investment there was illiquid.
Given this, I did what made the most sense to me: I bought all three. This helped mitigate the risk that I would pick the wrong one, but allowed me to make a bet on the sector. Homebase was still the largest position for several reasons (valuation, deal terms, and acquisition potential), but in aggregate I collectively bet on the space with a weighting towards a particular investment.
So there you have it. While long, it hopefully gave you some idea about how I approach investments. Questions and constructive criticism welcome.