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🎯 How Airbnb 2x'd revenue in 1 week
No code. One counterintuitive insight.
Read time: 3 minutes 14 seconds
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Honestly its a surreal privilege.
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How Airbnb 2x'd revenue in 1 week
Chess Move
The what: A TLDR explanation of the strategy
In the summer of 2009, Airbnb was stuck at $200 per week in revenue.
They had been there for 8 months.
When examining their lowest-performing listings, they noticed a pattern:
“The similarity is that the photos sucked. People were using their camera phones or using their images from classified sites. It actually wasn't a surprise that people weren't booking rooms because you couldn't even really see what it is that you were paying for.”
Poor visuals amplified uncertainty about quality and safety, making Airbnb's novel concept (staying with strangers) feel even riskier.
So Brian Chesky and Joe Gebbia flew from Mountain View to New York and personally photographed 24 hosts' apartments.
Within one week, revenue doubled to $400.
The insight sparked what became Airbnb's Professional Photography Program - Airbnb would send freelance photographers to hosts, for free, to take beautiful photos of their property.
Initially a scrappy “concierge MVP,” with founders and early team members manually matching photographers to hosts, it quickly evolved into a global platform.
By 2012, over 2,000 freelance photographers had shot 35,000 listings across 5,000 cities.
When they ran the numbers, listings with professional photos earned:
2.5× more bookings
$1,025 extra per month
The program solved their fundamental marketplace trust problem: guests couldn't assess property quality before booking an experiential product they couldn't return.
💡 | Strategy Playbook: A picture tells 1,000 words. |
Breakdown
The how: The strategic playbook boiled down to 3x key takeaways
1. Stop coding and start knocking
Startup mantras about scalability had trapped Airbnb in eight months of stagnation.
"We had this Silicon Valley mentality that you had to solve problems in a scalable way because that's the beauty of code. It wasn't until Paul Graham gave us permission to do things that don't scale that everything changed.”
The manual approach of spending in-person time with hosts revealed the real problem. Chesky discovered host taking pixellated photos using 5MP cameras, or saying things like "I can't figure out how to get photos onto my computer."
This was before high-quality cameras in every smartphone, or AirDrop / G Drive to transfer files. Hosts needed an eye for architectural photography, a quality digital camera, the right cables, the right adaptors, and a diploma in Windows Live Photo Gallery to have even a slim chance of a beautiful listing.
Often the friction wasn't laziness → It was a genuine capability gap.
By going door-to-door, founders gathered qualitative data they couldn’t get from an analytics dashboard.
One host famously presented a binder with dozens of product suggestions during a photo shoot.
"The roadmap often exists in the minds of the users you're designing things for."
This phase established one of the company’s foundational principles: "do everything by hand until it’s painful, then build systems."
2. Solving the adverse selection problem
The photography program attacked a fundamental issue with marketplace trust: information asymmetry.
Economist George Akerlof's seminal "lemons problem" paper explains why markets with hidden quality information fail:
(Quick ECON201 lesson: If sellers know more about product quality (like a used car with hidden defects, a "lemon") than buyers in a market, then buyers can only offer an average price, driving out high-quality "peach" sellers, leading to a market dominated by low-quality goods and potential collapse.)
Guests booking on Airbnb were buying something:
Experiential (i.e. non-returnable)
From strangers
With no way to verify quality beforehand
Professional photography solved multiple problems simultaneously.
First, it showcased properties accurately, helping guests make informed decisions.
Second, it served as verification - every photographer visit confirmed the address and space were real, and Airbnb badged the listings with “verified photos” labels.
Third, it dramatically improved conversion by making listings trustworthy and appealing.
The arbitrage math: photography cost Airbnb far less than the latent marketplace value it unlocked through increased bookings.
(Without even factoring higher host retention, increased brand trust, and competitive differentiation.)
3. Scaling the unscalable
‘Founders + borrowed cameras’ eventually grew into 2,000 freelance photographers shooting 13,000 listings.
The original workflow was pure manual labour. An intern emailed photographers and hosts to coordinate shoots, reviewed photos in Dropbox, provided visual feedback, and manually uploaded images to listings.
The process took hours per property.
Over time, Airbnb had automated several bottlenecks:
A system notifier made photography offers to hosts in specific markets
An assignment algorithm matched photographers to shoots
Operations coordinators handled quality control
Shoots followed style guides for consistency
Photographers were vetted for architectural expertise
The program ran "like a small business within Airbnb" with 8 in-house staff managing the global contractor network.
"We start with the perfect experience and then work backward."
The perfect experience was trustworthy, beautiful listings.
Code alone couldn't deliver that - but humans could, and over time, code could scale the humans.
Rabbit Hole
The where: 3x high-signal resources to learn more
[4 minute read]
This iconic essay has the craziest Airbnb origin details you've never heard:
A binder full of maxed-out credit cards
The investor who left mid-meeting (didn't even finish his smoothie)
How they were literally giving the company "one last shot" when they joined YC
The exact week-by-week revenue when their growth exploded
PG reveals what made the Airbnbs different from every other YC batch.
(It wasn't just the novel idea).
[5 minute read]
This 68-slide deck contains the full evolution from "Concierge MVP" to an automated global network of freelance photographers.
Workflow diagrams, growth charts, and operational metrics never published elsewhere.
The 2 hypotheses Airbnb bet the program on:
"Professionally photographed listings get 2-3X more bookings than the market average"
"Hosts are wildly enthusiastic to receive the offer.”
[26 minute read]
“If he wants to sell that horse, do I really want to buy it?”
The fundamental trust gap present in every market transaction.
Less so when buying bananas from a supermarket. But very much so when buying a second-hand vintage guitar.
But every transaction sits somewhere on this continuum.
This paper was the most insightful thing I read when researching today’s breakdown. I think you’ll enjoy it too (only 13 pages!)
What did you think of today's edition? |
P.S. If you found this interesting, have a read of this other breakdown we did about how Airbnb funnelled users from Craigslist:
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