Unsure if your marketplace is supply or demand constrained? ⚖️
Here are 8 examples of models and heuristic to inspire your thinking.
Thread 👇 (1/12)
Here are 8 examples of models and heuristic to inspire your thinking.
Thread 👇 (1/12)
1/ Thumbtack: “We went through a process to find a metric what was most predictive of consumer satisfaction (NPS in out case), and found that ‘Hire Rate’ was directly correlated with the NPS score they ended up giving later. So we focused on Hire Rate...”
2/ Thumbtack (cont.): “...We found that customers were happy when they got at least three results when searching for a Pro, and that we were healthy when 60% of the search results included 3 or more quotes. Below that meant we were supply constrained.” @sanderdaniels
3/ DoorDash: “When we launch markets our focus is to get to a small, defined number of deliveries per day (for example, 100 deliveries per day), within a relatively defined space. When markets hit that level, they ‘graduate’ as a market.” @micahmoreau
4/ OpenTable: “We were able to graph out restaurant penetration, and overlay diner growth and % of reservations we could deliver per restaurant. Our ability to accurately forecast growth was tied to this correlation of restaurant penetration to reservation volume.” @XenakisMike
5/ Uber: “We eventually decided that our goal should be that less than a certain percentage of trips should be surged in a market (~20% - 30%). The idea is that any market that was over that percentage was under-supplied, and vice versa.” @andrewchen
6/ Airbnb: “To determine if we were supply or demand constrained in a market, initially we used occupancy rate — if it was above a certain % we were supply constrained. Then, we moved to a model where we looked at occupancy rate vs. bookings rate...”
7/ Airbnb (cont.): “...and when there was a downward inflection point we knew what occupancy rate that market was supply constrained at. Most recently, we used model that tells you for each market - do you get more incremental revenue from an additional unit of supply or demand.”
8/ Zillow: “To figure out where we’re constrained, we’d watch stats like quotes/loan request, loan requests/user, competitiveness of rates, and contact rates/market/area. If we were low in a given area, we’d work hard to build supply in those areas or turn down demand.” @natemoch
9/ Instacart: “One metric we use is called Availability. When Availability is high, it means customers can order for immediate delivery. We worked hard to make sure availability is high so that customers are able to order and get value from our service immediately.” @Max
10/ GrubHub: “We created a model that looked at restaurant coverage in a market to tell us which markets were supply constrained: (1) What % of restaurants in a market are on GrubHub vs. not, and (2) the number of orders per GrubHub restaurant...”
11/ GrubHub (cont.): “...If orders per restaurant in that area were in the higher percentiles, we focused on supply in those markets.” @onecaseman
12/ More insights 👇👇👇 lennyrachitsky.com/p/how-to-know-…
