How to Accelerate Everything

Yashad Kulkarni38min

Speaker 1

00:05

Folks, it's a pleasure to be here today to talk about growth on this panel called How to accelerate everything. It said that you measure what you value. And for startups, nothing is more valuable than growth. Growth is the key ingredient to raising capital, hiring great people moving up in the Silicon Valley world, that obviously creating some of the greatest companies on the planet. I'm extraordinarily excited today to have the distinguished growth panel, which you just heard, introduced by a colleague, Alex Wilhelm. And we're going to start with one of the most challenging topics that has come up in 2021, which is around attribution. This week, Apple released iOS 15. And last year released iOS 14. And those the iOS updates introduced several new do not track features into the Apple iOS ecosystem. Those features also make attribution extraordinarily hard for startups. And attribution is a core for a lot of growth. And so I want to start Jennifer baby with you just to get us going. Um, how do you think about attribution today, in the context of Allegiant health?

Speaker 2

01:07

Yeah, it's it's a great question. I think about it a lot. First of all, Danny, and I think for us, so for a little context, elation, health is a b2b business, and we're working with other physician practices, but trying to partner from a sense, business to business. And so the way I think about it is, a lot of our attribution ties back ultimately to sales or acquisition if new physicians coming on to use the elation platform. And so for us, there's a lot that happens, obviously, prior to the sale, and we do a lot of work to map from when a user is anonymous, and coming to just maybe first learn about elation on one of our first party properties like our website, to when that person actually converts. And for us, when we actually see that person convert to a known user, is when we really start to get a lot of strength in our tracking. So that's when we can start to understand how that person became known to us. So if they responded to a search ad, or a Facebook ad or flee to he came in organically, and then can measure all the way through to our cycle or deal cycle if they take a meeting, multiple meetings, and ultimately, if they decide to move forward with using elation. So it's it's a journey we track. And a lot of it really just depends on the program and the tactic. But a lot of it starts with like anonymous users becoming known users.

Speaker 1

02:34

And churchy have a point is sort of the same concept applies to you. Are you focused on sort of, you know, the starting touch points for customers ending touchpoints, multi touch? How do you think about attribution?

Speaker 3

02:47

Yeah, definitely. I think one of the main things I've learned from experiences with attribution is that it's really important to start basic and simple. And then try to evolve from there. Right. And it definitely been in companies where we've made that mistake before. And the example I like to give with that is that, you know, if you think about attribution, like, say, a vehicle, right, it's, it's really enticing to try to build that Ferrari of attribution systems. But a lot of times when you're just starting out, all you really need is a skateboard, right? It's something that's simple, and they get the gets the job done. And we've sort of made that mistake at some previous companies I've been at. You know, one example from a few years ago at ctq, was we tried to build a medium mix model, before, we had something much more basic in place. And we invested a lot of time and effort into that with our data science team, but was actually, you know, after all of that it was actually never used and never adopted. And I think there were a couple reasons for that, you know, the first was that, at the end of the day, the ultimate goal of attribution is to measure incrementality, right, or how much incremental revenue is being generated by your marketing efforts. And, of course, a complex, you know, media mix model, multi touch attribution model is intended to do that. But it's hard to do it right. It takes a lot of effort and takes a lot of time. And for us, we had built one that actually didn't serve that need a better your mentality as much as possible. And the other learning from that was that, you know, as much as it's important to build the right technology, it's also really important to bring a lot of the people and processes and culture along with it. Right. So as we were building it, I think we didn't do as good of a job of ensuring that all the different business stakeholders really understood it. And as a result, it's hard to trusted, right? Especially if it's telling you that, you know, different channels or strategies are less effective than you think. And so, from that particular example, we sort of went back to the drawing board started much simpler, and then from there over time, evolved it and built into something a lot more effective.

Speaker 1

04:56

And, Nick, you work with a lot of different startups. Do you have sort of a template that you apply to everyone, when it comes to attribution and thinking about attribution or, you know, does does the engine that you're building change radically depending on the kind of company you're working with?

Speaker 4

05:10

Sure, yeah. So for context, we, we focus a lot on b2c or CPG, direct to consumer brands, more focused on on on the customers versus going b2b. And, you know, kind of what Shoji mentioned, a lot of it is starting simple and building on top of that, for the brands that we work with, which have, you know, a ton of different channels running, whether it's outside of just paid social, they're going into TV and podcasts and influencer and all these different channels, we've actually found that the best way, especially with iOS 14, and 15, which we're very not happy about, especially with those emails being hidden, the best way to do it is actually look at attribution from an incrementality testing standpoint. So understanding with holdouts how incrementally, you know, essentially, how incrementally good is a channel for us. And what that also does is outside of just giving us the data of what the platform says, you know, for example, a click or a seat were really less CPA or you know, how far they got down and to that funnel event, whatever that cost is, the incrementality. attribution platforms can actually help us to verify that and really understand, oh, you know, is the platform telling us something that makes them look good? Or is it telling us a real holistic number.

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