Tomer Cohen: evaluation

Transcript context

…team, there was no unified feed team, there was no feed PM to an extent, I asked to do this role, nobody cared about it. I really believed in it. I have strong conviction about what I could do there. And I asked to do this role and we assembled the team around it and one of the main things we've done was to really set the new purpose for it, which was this is not a springboard for other products, this is not a traffic jumpstart for, it's not an app self feed, it's really about people that matter talking about things that I care about professionally. It's about knowledge exchange. It's about how can I get the right views to the right experts in a way that actually helps them build a reputation and build their business. And then we started from there backwards. So it was basically setting that ground for that mountain peak that was nowhere to be imagined at the beginning and making our way backwards. The first thing we did was really making AI first. So the AI team back then was completely centralized. It was not part of any product team and we brought it together with one unified AI first team. And the belief I had was ultimately the engine of the car was AI and that was almost like de-prioritized or delegated to a team that was not unified in objectives. So bring that in. And then I spent most of my time on objectives and algorithm features and data training, which led me into my passion about training product people to be a first product people. And that was a big transformation there, really shifting and we had incredible AI team, but they were completely, actually, it was a confused operation. They were building something for a whole different purpose and we were trying to aim to that mountain peak and they were putting in a different direction. No bad intent, that's what they were told to do. So bringing it together into this SWAT team was the first thing that actually was extremely powerful, but then became the hard work. You have a product that works in a certain way and you almost want to change its DNA altogether. And it was very hard because whenever we were trying to run experiments that were mass in scale, I told you everybody was relying on the feed for their traffic. It just scared the whole system because numbers were shifting up and down and teams were freaking out about meeting their goals. And then I realized that was just spending my time in escalations instead of actually building a great product. So what I did was I carved out two million members and I said, "Those are my members. I'm going to focus on building that mountain peak. I'm going to build for them." Full liberty and doing whatever, it doesn't hurt numbers, giving the scale and really focus on building a great experience for them. And it wasn't overnight and it wasn't over a week, but over the course of months we've seen dramatic behavior change for those members, almost like secluded, like a country of people that were seeing a different experience of LinkedIn. And once we saw that you actually had strong evidence that wow, if I bring this in, we don't need to spend time talking about how this pie gets slotted between different teams. experience of LinkedIn. And once we saw that you actually had strong evidence that wow, if I bring this in, we don't need to spend time talking about how this pie gets slotted between different teams. We can actually grow the pie. The experience just manifests itself in a whole different way and that was a big change internally. It wasn't overnight, but it was really powerful in getting everybody around to see, wow, we have this cohort that is doing extremely well, which was a randomized cohort and then how we can bring it out. I've also done some crazy things. We've done some negative tests to prove some stuff out, test for the sake of learning. When you run something that you can show that if it's just a promotional feed and you played it out organically over time, engage with the tier rates. We ran some really important ad tests as well, but we're really shown separate, almost like we carved out the different product and we showed that this could work and then we brought it out to the main experience for everybody else. And then that was, I would say the inner workings of minus one to one. Then the scanning part really became when we started to focus on professional opportunities. So when people actually share, how do they get the right views into the experience? We don't compete for volume, we're not in the same category of Meta in terms of the skill there, but we will compete all day long for the right people seeing your content. In fact, I think in many ways that's the most powerful part of LinkedIn. How do we make sure that it's professionally productive and safe conversations? How do we trade off bad engagement all day long? In fact, when we started shifting the AI objective from click through into more downstream conversations, spammers actually took notice as well. So they were jumping over the LinkedIn bandwagon, so we had to spend a lot of time removing bad activity from LinkedIn, but that's been the evolution of this process. That is amazing. There's so much I want to dig into here. Okay, so this two million user carve out that you did, basically everyone was just like, what the hell are you doing to our metrics and goals? You're causing all this trouble for the business. Why is this team hurting our metrics? So that was basically a group that those two million users are the only ones that saw this new updated feed and were they removed from everyone else's metrics so they weren't fluctuated as much or was it just?…

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