Kalshi shifts its focus as customer demand changes

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 16:49

   okay that truly applies still okay so how do you plan dynamically right It's the end of December. You've got a board meeting. Alfred Lin's on your board. What do you actually even present to the board? Yeah, it's kind of like hazy a bit. Like, you know, the board used to be like, oh, it's not structured enough. But now I think they're kind of used to it. What is it? It's usually, so look, yeah, it's a good question.

2. 17:12

   I tend to not have too much structure. And one other thing, actually, at Calci, we're not super metrics-y. Okay. In general. I thought you'd be the opposite. No, we're metrics-y, very hardcore, and like risk. Like how much margin are we giving to customers? like things that are like go directly into the product but in terms of decision making We should be a little bit more, and we will probably get to there a little bit more over time, but it's really more like, what are the customers saying? What are the pockets of demand that basically the energy is about? And where can we basically be first or be most aggressive or have a right to win? That's all the conversation where it's at, right? And then there's usually like one or two key challenges that tend to be the single most important challenges in the organizations.

3. 17:55

   like and let me just yeah let me give you the last sort of like uh maybe 18 months so off of the election that all the conversations what are we going to do about election how you're going to cross sell people are they going to stick yep and what they're saying at the time is like like well let's prove that this sort of this network effect engine now that we have we have a massive growth catalyst that it is going to create the chain reaction let's figure out how to like make sure that people are you know adopting other products and like get going and that worked like we really we really create that network network effect where we use that new demand to attract more liquidity which boosted all the other markets and then that helps us get demand at a lower cost and then we basically compounded there then after that it was essentially like okay we we need to prove our

4. 18:32

   broker strategy is working so we had the direct to consumer that was going pretty well but we wanted to make this bet that um becoming an infrastructure layer like all traditional financial markets that we enable a bunch of brokers to basically go and like could we prove that we can do both at once and that one was going a little bit slow so the next six months we're like scaling that we got a bunch of brokers that sort of really started working out then the challenge was actually proving that we're not too dependent on the brokers okay because those were too well they became 80 of our revenue okay so all of a sudden it's like oh amazing the revenue like ripped but like now you're super dependent on a bunch of your big broker partners so what are you gonna do now it's like okay now we have to go back to focus on the direct and like really

5. 19:10

   scale that now that we have an extremely liquid ecosystem because the brokers brought more demand more liquidity the whole thing is flowing now now the brokers are like 10 of our uh volume okay all the way back to 10 yeah so so that and i i want to talk a little bit about this adaptability thing because all of these were i mean we're talking about like going from like elections and like