My post on Wednesday about Passengers as an RLV market got me thinking about the old Futron Space Tourism study from 2002.
Background on the Futron 2002 Space Tourism Market Study
If you’re relatively new to the space scene, this was a market study the Futron corporation did right around the time the first Space Tourists started flying to the ISS (Mark Shuttleworth and Dennis Tito). In this study they met with several hundred affluent people and asked them a series of questions about their interest in flying to space (suborbital and orbital), both before and after they had talked about the postive features and downsides/risks of space tourism. They asked questions to try and gauge how sensitive people’s interest was to the price point of the service. They asked questions about things that might increase or decrease people’s willingness to buy a ticket (things like flying on a Russian rocket on the negative side and having a short 1 month training cycle on the plus side).
They also asked sanity checking questions about how much people spent on vacations and large discretionary purchases. They used this last bit of information to try and estimate what fraction of a person’s wealth they really would be likely to spend on a single purchase (they found that very few of the affluent people surveyed spent more than 1.5% of their wealth on any given discretionary purchase). They used this 1.5% number as a conservative upper bound on the percentage of their wealth someone would spend on a space tourism flight. They would use that to estimate the minimum amount of wealth someone would need to actually be willing to pay for a flight. They’d take the number of people with that wealth level or higher as the base pool of potential customers. They’d then reduce it based on several other factors (fitness, willingness of survey members to buy at that given price, etc) to whittle it down to likely customers. They then used that with an adoption curve to try and estimate the adoption rate for orbital and suborbital tourism. In both cases, they made assumptions about the price of the service over time, and did a single projection of the market.
Gary Hudson’s t/Space later reanalyzed the data to see what the effect of different price levels would be on demand. They used both the 1.5% of wealth and 5% of wealth limits to see the size of market at ticket price points of $5M, 2.5M, and 1M, with the assumption that the launch took place in the US and the training took only one month (instead of six months in Russia). Gary found that the addressable market and flight revenues were likely to increase substantially as prices dropped to these levels.
Update Based on 2013 High Net-Worth Individual Data
Out of curiosity, I decided to look-up the latest estimates of numbers of High Net-Worth Individuals (HNWIs) by various wealth tiers, to recrunch the numbers. I had to get data from two wealth surveys, one the 2013 World Wealth Report from Capgemini that only had three tiers ($1-5M, $5-30M, and $30M+), and another World Ultra Wealth Report 2013 from WealthX and UBS, which broke down Ultra High Net-Worth Individuals (UHNWIs) into several tiers between $30M and $1B. One important discrepancy you’ll notice is that the first report only showed ~110k UHNWIs and the latter showed nearly twice that, ~200k UHNWIs, both for the same time frame, so you should expect the transition between the two to be a bit rough. Also, the World Ultra Wealth Report didn’t break billionaires into any subtiers, which had the odd effect of placing more people in the $1B+ tier than in the $750-999M tier. Also in each case, the tier divisions seemed somewhat arbitrary. I’d love to get a single set of raw data from one source that all individuals with >$1M in assets, but alas.
Anyhow, let’s get to some tables and charts.
First up is the table with the numbers from both of the reports put into one convenient location…
Next, is chart that uses the data from that table and shows the average wealth level of each individual tier on the X axis, and the number of individuals on the Y axis, with both axes on a logarithmic scale .
The two major blips you see in the curve are at the third data point where we transition from one report to the other, and in the final data point where all billionaires are lumped into one single group. But the data actually lines up reasonably well with a power-law curve fit.
One third chart uses the same data, but this time shows for each given tier level the number of individuals with at least that level of net worth.
While this looks like a great fit, and while it’s within <10% error at half the data points, the worst errors are at the >$5M level (+33%), the >$200M (-27%), and the >$1B level (+34%). That’s far from perfect, but is a far better fit than any other the other trendline options in Excel, and using that trendline equation we can estimate the global demand pool at various ticket prices and percentages of their wealth people would willing to spend.
One last chart is to extrapolate the percentage of HNWIs willing to buy at a given ticket price. This is probably the shakiest extrapolation, but is necessary to cover the full range of interest. I didn’t plot this log-log this time, and as you can see the trendline isn’t perfect, so data below $1M and above $25M needs to be taken with an appropriate sized grain of NaCl.
Estimated Addressable Orbital Tourism Market Size Analysis
So, now that I have those curve fits and that data, I can rerun the analysis Gary Hudson’s group ran using up-to-date data, and a more granular distribution of ticket prices, up to and including today’s current ~$50M ticket price level for Soyuz seats. I also used three values for the maximum fraction of someone’s net worth they’d spend on a ticket–the Futron value of 1.5%, the 5% number t/Space included, and a 10% number that’s more indicative of what several actual space tourists have been willing to shell out. I used the same multipliers t/Space did for fitness probability, and for flying out of the US with ~1 month training in the US instead of 6 months in Russia.
Here’s the results for the case where customers are willing to spend 10% of their net worth on space travel:
Here’s similar charts based on a max ticket price of 5% of a given HNWI’s net worth:
And again with ticket prices at the 1.5% of HNWI’s net worth used by the Futron study:
And in case you want to poke around my spreadsheet, here’s a copy: SpaceTourismCalcs.xlsx.
Takeaways and Caveats
Here’s the main takeaways I had from this exercise:
- Space Tourism demand looks like it’s likely one of the few existing space markets with a high degree of elasticity. Reducing ticket prices should increase the addressable market enough to actually lead to more addressable revenue–so there should be a strong incentive to drive down costs and thus prices.
- I was actually surprised by this–I figured that at the prices we were talking about, the demand elasticity would actually be very low, and that you’d have to get prices down quite a bit to get into “virtuous spiral territory”.
- The elasticity at all three levels of “max percentage of net worth per ticket” is strong, with a 7-8x revenue increase dropping from the targeted Commercial Crew ticket prices of $20M/seat to the $1M/seat level.
- You wouldn’t even need to get down to the $1M/seat range to get demand levels high enough to support a healthy industry of small RLVs.
- If you assume 60hr research weeks for 2 weeks at a stay, a researcher could beat the already lowballed NASA ISS estimate of $55k/hr costs even if seat prices were $5M/seat. This is a totally different and complementary market to tourism, but I thought I’d throw that number in there.
- Even though almost all space tourists so far have spent >5-10% of their net worth on their flight to ISS, even if future tourists would only be willing to spend 1.5% of their net worth, these elasticity results look real, and the addressable market sizes look interesting.
Before we wrap up, here are some important caveats:
- There were discrepancies between the two wealth datasets, and the trendlines I used probably smoothed out a lot of real-world bumpiness.
- The Futron “likelyhood to buy at a given price point” data I used here was only for orbital flight–for other destinations like suborbital or lunar you’d need different probabilities.
- I wasn’t doing this post to suggest I think that space tourism is the only interesting market, the best market, or even a good market. I just wanted to run the numbers using newer data to see what could be learned. It suggests to me that people-related markets (tourism, potentially research, etc) likely are going to be very elastic compared to say satellite launch.
- This is based on a survey over a decade old. A lot has happened since then for better or for worse. For instance, space tourism has progressed a lot slower than originally expected. On the orbital side, part of this is due to the spotty availability of Soyuz seats–the Russians have filled just about every space tourist seat they’ve offered, even while jacking the price up by 2x what Futron had analyzed. On the suborbital side, it has taken everyone a lot longer to execute (and in XCOR’s case raise the money to have a shot at executing) than expected. There was also the fatal SS2 test accident last year. All of those could shift people’s opinions around. As could the number of wealthy people seriously talking about space tourism, Mars emmigration, etc.
- I wouldn’t put any weight in these numbers on a quantitative basis–there are probably useful qualitative lessons to be learned, but I don’t want to see anyone using this data as though it has even one significant figure…
- Also, the market sizes I showed were total addressable market sizes (ie the total number of people who could afford it, are healthy enough, and are likely to buy if the flight happens in the US with ~1 month training), not yearly market sizes.
- I think I mentioned this 2-3 times already, but someone should really pay a Futron type entity to redo this study in another year or two or three, maybe once suborbital tourism flights have started up.