Several weeks ago I announced that we’re closing down Bllush, the startup I founded 4 years ago. The announcement was well received because it talked candidly about a topic we all know is important but usually is overlooked – product market fit (PMF). We almost had it at Bllush. Yet, almost is not enough. Similar to the concept of love, true product-market-fit is obvious when found.
Today I’m giving you a behind-the-scenes look at how product-market-fit actually looks like from the inside. The featured company is young, yet shows all the signs it clearly has true PMF. The metrics shown within this post are rarely shared in public. The CEO has allowed me full access to internal data in order to write this post. Fun!
Meet our startup on PMF-trial: QASE
QASE launched during the start of COVID with a new concept in the world of at-home entertainment. How can we entertain ourselves while the world of bars, clubs, restaurants, theater and social gatherings are limited? Netflix only takes you so far. QASE is a DTC brand that creates and markets “escape-room” style game boxes delivered to your home. You have two hours to solve the game challenge using accessories and clues until you finish and the game is picked up. The games are expertly crafted for a joyful experience. Most customers are group of friends, couples and families.
At first glance, before viewing any data, the startup didn’t seem too interesting and had scale issues. It’s introducing an entirely new category, at a turbulent time, with a hyper-local service. Apparently our simplistic minds can’t fully anticipate what consumers will enjoy. The fact that companies like AirBnB and Uber were passed by many intelligent VCs just proves that. One has to dive into the data to see the real picture.
Riskiest Assumptions & Due-Diligence Checklist
Without seeing any data, I would define the riskiest assumptions as:
- Market Demand = Do consumers actually want to order this new type of product/experience?
- Unit Economics = Can QASE be profitable when acquiring customers?
- COVID-19 & Timing = Would QASE succeed also after the world is back to “normal”?
- Secret Sauce, Moats & Defensibility = How hard would it be for competitors to compete?
- Scale of Hyper-Local Services = Can QASE become a $100M revenue business?
These are the main assumptions QASE needs to prove in-order to prove PMF. In this order. We’ll start at the top and climb our way down the ladder of proof (NFX).
#1 Market Demand
Why is this important? Historically, lack of product demand is the main reason startups fail. This can either be a “nobody cares” or “nice to have” response. If market demand isn’t proven, there is no point in checking out the other points to reach PMF.
I will evaluate the following KPIs to validate market demand for QASE:
- Customer in-game rankings
- NPS Score
- Repeat customers %
- Upsell Customers
Revenue is 100% direct sales from customers ordering the game. It grew from $4,583 in their first month to $77,500 last month. The growth is 33% compounded month-over-month (MoM) for the entire 10-month timeframe the company is active.
What is good MoM Growth? Although this depends on industry and buying cycle, lets take a look at other successful companies:
- YCombinator’s definition of healthy growth: “A good growth rate during YC is 5-7% a week. If you can hit 10% a week you’re doing exceptionally well.” QASE’s 33% monthly growth would come out to approx 7% growth per week.
- Bird / Lime – when looking at other hyper-local, sharing-economy companies, in the first two years of activity, Lime had 16% and Bird 29% MoM Growth. QASE has them both beat for their first operating year.
Customer in-game rankings
Why is this important? While revenue growth is vital, it’s not enough by itself to get a clear picture. At the end of the day, what customers think is paramount. Lets review in-game ratings user left after playing (1-5 star ranking) and NPS scores.
I’ve compiled & graphed the percentage of games with each score (n=1958). Respondents ranking a 4 or 5 star rating were 95% of rankings giving them a mean average of 4.65.
Lets now calculate NPS, a universal golden standard which measures the loyalty of customers to a company. The user is asked how likely is it that they would recommend your service to friends. The scores range from -100 to +100 (best score possible). QASE has a NPS score of 65.
QASE / NPS Breakdown
QASE’s NPS is at 65, which places them in the Great category and very close to Excellent. This score is rare within young startups and is usually held only by the world’s leading leading brands.
Why is this important? If you need to pay to acquire every customer you have, it will be hard to turn a profit and you will forever be dependent on fluctuating advertising costs.
Over the 10 month period the company has been active, more than 30% of their orders have been from repeat customers. This means the average user has ordered 1.3 games (Order Frequency). Although encouraging, I would like to see higher repeat customers in the future as the company adds new games to the collection (customers will not order the same game twice)
Upsell Customers After Finishing Game
QASE implemented an interesting strategy to motivate more repeat customers. At the end of the game, users are offered to buy a voucher for the next game. I was skeptic users would bite.
13% of customers decide to pre-pay for a voucher right after finishing playing. This not only drives repeat customers but also provides QASE with cash upfront to fuel their growth.
#2 Unit Economics
Lets evaluate how QASE finds leads, converts them to customers and the unit economics:
- Customer Acquisition Cost (CAC)
- Gross Margin (%)
- Lifetime Value (LTV)
- CAC/LTV Ratio
Customer Acquisition Cost (CAC)
Why is this important? Companies need to be able to acquire customers in a constant way. CAC is the average cost of acquiring a new customer (All Marketing Spend / Number of Clients)
QASE initially started with organic marketing and later got into paid acquisition. Since 85-90% of the marketing budget is paid ads, CPA is roughly equal to CAC. This means CAC reduced from $85 down to $10 last month. The rapid improvement in CAC in such a short timeframe impressed me a lot, especially since the ad volume also went up.
QASE CAC – How much it costs to bring a customer
Rounding up, we’ll get a CAC of $19 (using last 3 months).
Gross Margin (GM)
Why is this important? Gross margin is the total cost of manufacturing and delivering a product or service to consumers. Unlike Cost of Goods (COG), it includes costs outside of production, such as distribution and marketing (also called contribution margin)
For QASE, every $1 earned in revenue, the cost to acquire the user, supply the game and support that sale is $0.35 (Cost of Sale). This makes our Gross Margin 65%, which signals a healthy company. Even if they make mistakes in their acquisition strategy, they have a lot of room to play around with to maintain profitability. This is very close to SaaS startups who tend to have 75-85% gross margins.
What is a good Gross margin? Successful DTC companies have a gross margin of at least 50%:
- Casper, a DTC e-commerce mattress company (49%)
- Rent The Runway, a DTC e-commerce clothing rental service (50%+)
- StichFix, a DTC e-commerce clothing service (44%)
Lifetime Value (LTV)
Why is this important? LTV calculates how much profit each customer will bring your business in that customer’s lifetime (contribution dollars).
- The formula of LTV is Average Order Value (AOV) x Average Purchase Frequency (APV) x Gross Margin (GM)
- We’ve seen the average user orders 1.3 times per year (APV)
- The average order value is $100 (AOV)
- Gross Margin is 65%
Our lifetime value (LTV) would then be $100 x 1.3 x 65% = $84.50
Why is this important? The ratio of how much it costs to acquire a customer and how much profit each customer brings in is vital. It can quickly tell you if the company can thrive in the world of growth and cash flow.
Lets plot the CAC and LTV by month:
- We’ve seen it costs $19.00 to acquire a customer (CAC)
- This customer will generate $84.50 in revenue over a 12 month period (LTV)
- Hence, we can now calculate the ratio of LTV/CAC as 4.44
- This means every $1 in marketing will generate $4.44 in revenue eventually.
What is a good LTV/CAC Ratio? Here is a rough guideline from the folks at Geckoboard: “A ratio of 1:1 means you lose money the more you sell. A good benchmark for LTV to CAC ratio is 3:1 or better. Generally, 4:1 or higher indicates a great business model. If your ratio is 5:1 or higher, you could be growing faster and are likely under-investing in marketing.”
QASE are doing an amazing job decreasing CAC and increasing LTV. They have a very healthy ratio and can increase spending & marketing with much room for error (that’s the dream).
#3 COVID-19 & Timing
QASE launched in the beginning of COVID-19. It benefited greatly from customers having limited options for entertainment, closure of escape rooms and perhaps lower advertising competition. I would argue that their growth could slow down once alternative entertainment options are re-opened. If so, would we see growth halt completely? Or just slow down by 20%? Would all these loyal customers who connect with the brand start ignoring their marketing messages? There is no doubting these risks, yet it’s hard to predict the likelihood and severity of this outcome.
It’s likely consumer behavior will be slightly altered going forward. People will be more health cautious. Hosting friends at home will be more common. Ordering takeout will become more apparent. The at-home experience would enjoy this new shift in consumer behavior. No amount of research will be able to accurately predict the outcome. Only the future can tell.
#4 Secret Sauce, Moats & Defensibility
Why is this important? Few businesses are dominated by the first-mover. Competition is part of business, and important to see how difficult it would be for new competitors to compete.
I would define QASE’s success as dependant on three inter-connected functions (inspired by Alibaba’s Iron Triangle):
- Games = create awesome games users love
- Logistics = deliver the game to the customer’s home
- Software = support the game experience with tech
At the moment the games they offer are “escape-room” styled challenges. I played both their murder-challenge Grand Hotel and their computer-hacker game with friends. I was positively surprised on how challenging it was (and how much I sucked at them!).
QASE’s Grand Hotel Murder Game (beers not included)
QASE’s Hacker Game (computer is included)
Who makes the games? QASE works with local game makers. The games are created and produced by the makers on their own expense. These games can cost several thousand dollars to produce a single unit. Game developers then enter into a revenue-sharing agreement with QASE and earn from their creations. QASE enjoys high-quality inventory without upfront CapEx.
This game-creator community is a vital part of QASE’s strategy to build the highest quality of at-home game experiences.
- Inventory – Similar to Netflix, QASE will slowly build out their game catalog. A new competitor will find it hard to offer a comprehensive catalog. This offers a built-in network effect in which the customer value grows as the company gets larger.
- Locality – A game creator in New York would now be able to market his game to consumers in Berlin. By connecting the international supply and demand, game enthusiasts can now build sustainable businesses of developing games.
- Expansion – The experiences offered now are “escape-room” style challenges, which is a subset of the experience market. QASE will add additional experiences, such as video game consoles and VR/AR sets to expand.
You can view QASE as a short-term rental company. It has finite games (inventory) and wants to maximise utilization of those games (orders). This makes logistics critical. A customer receives each game for two hours, after which the game is picked up. This requires managing two-way shipping after a brief two hour window.
Hyper-Local: Dispatching a delivery for one customer is doable when it’s just back and forth. This use case is different. QASE needs to either dispatch both a delivery and then a pickup after two hours (super expensive) or have the delivery guy wait around for two hours (also super expensive).
QASE built a unique solution using proprietary R&D. In the diagram below, you can see each delivery truck is dispatched to a certain area where there are n=5 customers. He drops the games off at each customer and then returns to pickup (which takes approx 2 hours). Each delivery can handle multiple customers end-to-end. This is only possible once a high concentration of orders arrives from a single location. Their software builds a delivery model to minimize deliveries in real-time.
Why is this a moat? The traditional economies of scale applies here – As QASE grows, the concentration of customers will go up, minimizing deliveries needed, which reduces costs. Any new competitor would have an uphill battle at keeping their logistics to similar rates.
Interactive, challenge games are hard. That’s the point of them. During an average game, players would need 2-3 tips from a “game master”. Operating a support center with live “game masters” is a solution. But a very expensive one, which would reduce gross margins by 15-20%. and be a pain in the ass to manage.
They went a different route. They invested into R&D. Each game comes with a tablet called QASIE, a digital helper (with a great sense of humor). Having QASIE offer an in-game guide removes the need of a human game master and does the job fantastically. Many of the comments from the reviews are how much the players connected with QASIE the robot. For problems QASIE can not solve, there is a human hotline which costs very minimal resources. This R&D investment is key in their plan to scale.
Another area which R&D comes to the rescue is their BI tools. The company monitors every aspect of the game session, understanding which steps customers need help with and reaching out to customers who might have had a negative experience.
#5 Scale of Hyper-Local Services
Why is this important? In order to attract funding, partners, and employees, a company needs to be able to grow sustainability and be able to reach a billion dollar valuation.
Lets see if QASE can reach $100M revenue. I will model future revenue using the data I have from their original market (Tel-Aviv area). The Year 1 revenue is $250,000 with a monthly growth of 33%. I will assume Year 2 will slow down to 10% MoM growth and further slow down as the local market gets saturated.
Advertising and CAC will vary by market and may increase alongside scale. Due to their high margins of 65%, even if CAC increases by 30-50% they would be fine.
QASE needs to expand internationally to new markets. This can be larger cities with an urban environment at first. Assuming customer demand is similar in other locations, yet the total addressable market (TAM) size is considerably greater, QASE can hit the dream $100M revenue sweetspot within 7 years with 5 locations. The graph below shows the projections assuming they open 2 new locations per year.
We analysed QASE in terms of product-market-fit and if the business can scale:
#1 Market Demand
Revenue: $4,583 (M1) to $77,500 (M10) Revenue Growth: 33% MoM User Ranking: 4.65/5.00 NPS: 65 (Great!) Upsell: 13% pre-pay for next game
#2 Unit Economics
CAC: $18 (last 3 months) Gross Margin: 65% LTV: $86 (last 3 months) LTV/CAC Ratio: 4.44 (Great!)
#3 COVID-19 & Timing
COVID has increased customer demand. Growth may slow down in the future.
#4 Moats & Defensibility
A competitor would need to handle Games, Logistics and Software just as well as QASE. Doable, but not easy.
#5 Scale of Hyper-Local
QASE will need to expand globally which is a complex and not obvious
It’s very rare that an active startup chooses to disclose these KPIs. Thanks again to Itay Hasid and the guys at QASE for being so transparent. The analysis I did are the types of questions investors should ask themselves when evaluating a startup. The fact that 95% of VCs lose money perhaps hints that most of them don’t do as much research as shown here. If you’re an investor reading this, feel free to use my evaluation template for your own due-dillgence. 😉
Hope you had fun reading this post and the analysis of each business unit.
Thanks to my peeps for offering comments on the draft: Sergey Toporov @ LETA Capital, Nitai Dean, Tracey Hayse and Bonita Dean.