A look at how Airbnb is solving the confusion around pricing for their hosts, and you can too.
If you were in Mordor or Westeros until now, read this before going ahead. If not, you probably know how big Airbnb is and how particular they are about providing their hosts and guests with the best of experiences throughout their respective journeys. Something which every business aspires to do.
Airbnb has a vast number of hosts who have listings ranging from a room in Manhattan to a castle in Scotland, a beach house in Goa to a tree house in Hawaii. Add to this the complexity of seasonality, popularity, other nearby listings and booking history and it becomes a nightmare for the hosts to get to the right price!
This is important for all businesses today. In Fact, Airbnb has actually spent a lot of time to develop a custom solution for themselves.
You can’t expect someone renting out a single room in their house to check how much their neighbour is charging. They will never wonder how different seasons or nearby events affect the going rate of the room. And, hosts being Airbnb’s bread-and-butter, needed a solution for this.
Airbnb had a lot of bookings data on their platform. So they looked inside this treasure chest of data and came out with Aerosolve. Using Aerosolve, they now suggest a price (inside the app) at which the host should list their spare room, their apartment, their castle or their tree-house to get the best out of their listing. This just takes all of the complexity away from the hosts. They don’t have to worry about all the factors that affect the demand for their spare room and Airbnb takes it all away.
To come up with the optimal price — what the guest would be willing to pay, Airbnb has been leveraging machine learning to understand all the market changes and the micro-trends. All of this happens automatically, so the hosts don’t have to do a thing! Airbnb takes care of all of the following factors before making a suggestion.
- If the place is going to go empty for a night. (perishable inventory)
- If more people are looking for a place in your area. (product popularity)
- If the location is currently in-season or not. (seasonality)
- If the place has extra amenities. (extra features)
- If the place has been booked heavily in the past. (booking history)
- Most importantly, if the nearby hotels have increased/decreased their prices. (competition pricing)
“We have been operating on the belief that enabling humans to partner with a machine in a symbiotic way exceeds the capabilities of humans or machines alone.” — Airbnb
You (if you are selling anything online or offline) also have a huge number of products in your catalogue. You also have to deal with similar complexities like inventory, competition, margins, seasonality etc. Getting the price right for each of them can be a huge advantage for your business.
You and your business can benefit from what Airbnb did for their hosts. There is a lot of data that you are already collecting. Yes, the sales spreadsheets, the invoices, the bills and transaction receipts — they all count. Once you have them, you can start to figure out trends like sale patterns during weekends, or complimentary nature of a product with another.
You can also look at the prices at which your competition is selling their products. This will help you adapt to changing market conditions.
Like Airbnb, if you leverage the power of machines to remove complexities away from the humans involved in the decision making process, you could end up with a system that’s effective and frictionless. The best part, once you set up all of this, this functions automatically and you can stay on top of your pricing. This is something we do here at Greendeck. We help you manage your pricing and promotions with the data-science technology that was once limited to Amazons and Walmarts of the world.
In Airbnb’s case, their solution depends on calculating correlations and figuring out location polygons to get to the right price. This works perfectly for them, but every business is different and that is why pricing is a complex problem to solve. I believe that you can get there by being open about the problems you face while pricing and fixing it one at a time.
IF- You feel that your pricing strategies need a revamp -OR- If You have reasonable doubt that you are leaving money on the table by sub-optimal prices -THEN- you can do what Airbnb did.
That is; start thinking how you can use the data you already have to make better pricing decisions.
The answer is already with you. You just have to find it!