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Harder to stop a moving train: Inside FOSSIL's high velocity testing program | Marcela Gutierrez
25 Plays8 days ago
Stopping someone who already has a finished experiment is a lot harder than saying no to an idea on a whiteboard. Marcela Gutierrez figured that out, and it changed everything about how Fossil Group runs its experimentation program.
Marcela Gutierrez leads digital analytics, experimentation, and consumer behavior at FOSSIL Group, where she has spent 13 years across the US and Switzerland. She is the kind of analyst who thinks just as hard about how data gets communicated as she does about what the data says.
In this episode, Marcela shares how FOSSIL shifted who builds experiments and why that single change unlocked speed across the entire team. She also breaks down how her analysts think about metrics, storytelling, and why human judgment matters more in experimentation programs as AI takes on more of the build.
Key takeaways
- Building a test before asking for approval changes the conversation. Coming to a sprint review with something nearly finished is harder to stop than rejecting a rough idea, and FOSSIL uses this dynamic to run more experiments with less friction.
- A primary KPI needs a secondary one. Marcela's team pairs each main metric with what she calls its "BFF" metric, so results tell a coherent story rather than just a flattering one.
- Analysts are not data processors. The most valuable work they do is understanding organizational context, cleaning data before it goes in, and translating insights for the right audience at the right level of detail.
Recommended
Transcript
The Impact of Presenting Ideas
00:00:00
Speaker
it's harder to stop the progress of somebody that already has work done. right so when and When somebody comes to you with an almost fully developed idea ready to be implemented, it brings a different outcome to the team because they're like, okay, let's run it. Or actually, can we change can we tweak this a little bit? Can you make this font a little something? Or could we And all of this is still welcome. right We want the test to be executed to perfection like it would. We want the voices still to have a say in all of that. But it's alleviated debt so that they can spend their time working on on really cool projects that we know are going to be effective for our brands versus working on all these, I'll call them little, but not really, on all these ideas that we're trying to, with speed, try to see can we come up with any good ideas that are going to be changing the business for the positive for us.
00:00:53
Speaker
Welcome
Introduction to 'Unite Voices' and Guest
00:00:54
Speaker
to Unite Voices, hosted by Katie Green. Real stories from the people behind today's most innovative experimentation programs. No fluff, just wins, failures, and the lessons in between.
00:01:08
Speaker
Marcella, welcome to Unite Voices, hosted by me, Katie Green, who I'm so happy we got to meet in person already at Unite Vancouver. i feel like we're already buddies coming onto this podcast, so thank you so much for being a part of our show. I want to give you a chance to introduce yourself. You had such a good presentation at Unite Summit Vancouver, and i would love for the people to know who you are before I dig into all the dirty details of how you're running your testing program.
00:01:35
Speaker
Thank you, Katie.
Marcella's Career and Role at Fossil Group
00:01:36
Speaker
um It's an honor to be a guest in your podcast. I had the pleasure of meeting you and I feel like in Vancouver you became instant friends with everybody. You just have such an aura and a good um quality to you to make people feel at ease and Marcella Gutierrez, have a great conversation so i'm very much looking forward to being a part of this and just for everybody at quick intro my name is marcella gutierrez Marcella Gutierrez, born and raised in Honduras in Central America, but I lived much of my life in in the US am I lived a little bit in the Philippines, and now I live in Switzerland i've been here almost 80 years now. in
00:02:14
Speaker
And I've been with Fossil, with Fossil Group for 13 years. So my career with Fossil spanned both in the US and in Switzerland. And
Translating Analytics for Diverse Audiences
00:02:25
Speaker
my my role here is to be over digital analytics, experimentation and yeah consumer behavior, really understand who our consumer is for Fossil. So i'm happy to be here.
00:02:37
Speaker
This is great. I didn't realize you lived in the Philippines for some time. We're going have to talk about that a separate time. My dad is from Manila. so Oh, that's where I lived. Oh, great. Okay. We're going to have to go over this. like i There's some really good Filipino food in Portland, Oregon, so we're going have to talk about this and- That'll be a whole separate pod. That'll be my food pod when I start that. No, this is great. I want to dive deeper into your role at Fossil because I saw on your LinkedIn something that really stood out to me, which is you are an analytics translator. And I think a lot of people listening to this pod who work with us and work in experimentation, they may not be analytics engineers, but they are responsible
00:03:19
Speaker
for translating analytics, data, success. I'd love to hear a little bit more about what that means in the context of a global brand like Fossil. Yeah, for sure. I mean, I think if you are if you play in a technical role or even if you have expertise in anything,
00:03:35
Speaker
you need to become good at communicating and you need to become good at translating to whatever audience you are speaking with. So my same message when I talk about a whatever project it may be talking about will be delivered in different language if I'm speaking to analysts versus if I'm speaking to a marketer versus if I'm speaking to a salesperson versus if I am speaking to a board of directors, right? And it's just this idea of that with analytics, with experimentation, with blank, your in your things can get very technical and you can come across as very intelligent and impressive by using complicated language, or you can come across as just easy to understand. And that's
00:04:21
Speaker
That's how I challenge myself. That's a skill set that I try to work on to make sure that my team and I are very good about this and in translating, in taking complicated topics and making them easy to understand, easy to digest and easy to know what can I do with this? What is my next step? And funny enough, I was just looking this up because it's even in our team mantra, like for my direct team. we have a little mantra that we put together a few years back. And and our little mantra is always deliver the truth in a beautiful way.
00:04:58
Speaker
And what this means is you know, we are the analytics team. So we are a neutral team and we will always deliver the truth. Like people come to us with questions. They want, they have something in their mind that they want to explore a problem, an opportunity or something. So it's our job to look into and into this and deliver truth, look at facts. But we are also, when when I say deliver in a beautiful way, this encompasses several things. It encompasses being respectful of the other person's point of view, knowing if they're biased in some way or another, because if we're gonna deliver bad news, we will we will always do it. We will always deliver the truth, right?
AI and PBX in Experimentation at Fossil
00:05:34
Speaker
But we wanna do it in such a respectful way that can be that can be easily grabbed by them and understood or versus celebrated if you're delivering a positive news and in a beautiful way, meaning also in visually appealing, like that your information can be captured and understood easily on a slide, not with 10,000 different words, with formulas, with things that are just gonna make somebody go to sleep, but really do it in a way that is, it's easy to digest and easy to to action on. so
00:06:06
Speaker
I love that. i think I think a lot of people are going to take that away from this episode is how do i deliver maybe not even hard things, but like like you said, complicated. it can be really complicated in experimentation. I think you have a very unique skill. I love that you said you're still working on it. I think that shows the ego of an experimenter, right, where you're constantly striving for better. You're looking to improve. You're kind of classic to a T on that. that constant improvement behavior identity. So I think something you did at Unite Summit Vancouver is you told the story of how you're leveraging PBX and ai to speed up velocity for your testing. And I'd love for you to dig into that a little bit more. You did such a good job explaining that. I think there's so many elements we can get into, but let's start with the overview of how are you using PBX? How are you leveraging AI to
00:06:56
Speaker
increase velocity, increase learnings, and democratize how you're sharing that information. Yeah, for sure. I mean, we at Fossil um do a lot of experimentation, right? And in our process, we've been doing experimentation now for several years. We do it across our different brands of portfolios and across regions. And so PBX has really, when I tell you this, it's it's transformed our experimentation program. Meaning if we look at our experimentation program and where where it was four years back and where it is today, it's changed and a lot of it has had to do with PBX. Why? Because with PBX, we've been able to tackle an area that used to be a bottleneck for us. For us, the the idea of experimentation, you know you're looking into ideation and you're looking into execution and analyzing the results and presenting them and all of this.
00:07:51
Speaker
Ideation has never been a struggle for us. We come from a group that is very outspoken. People here, they love to share ideas and we we love it. We welcome it. We want everybody to give a good idea of things to be tested. And then we go about it and and measure the idea and such. But to us, it was always up an issue of finding dev capacity and capacity in the different in the different teams, but especially with our devs, to be able to create the test that we wanted to. and get it ready in order for it to go to production. oh
00:08:23
Speaker
With PBX, what we've been able to do is analysts and members of my team were able to lighten the load on the developers because we can take a lot of the ideas that we have in the pipeline and do them ourselves. And what I mean by this is when we come to a sprint review, when we come to to get together with a bigger team and talk about the ideas that we want to run and execute, it's a different story when you come prepared and come.
00:08:51
Speaker
I have an idea ready for QA. Can we test this? Versus, hey, I have this idea that's an easy one to do. Should we work on it? It's it's harder to stop the progress of somebody that already has work done, right? So when and when somebody comes to you with an almost fully developed idea ready to be implemented, It brings a different outcome to the team because they're like, okay, let's run it. Or actually, can we change can we tweak this a little bit? Can you make this font a little something? Or could we QA? and and and all of this is still welcome. right We want the test to be executed to perfection like it would. We want the voices still to have a say in all of that. but it's alleviated debt so that they can spend their time working on on really cool projects that we know are going to be effective for our brands versus working on all these, I'll call them little, but not really, on all these ideas that we're trying to, with speed, try to see can we come up with any good ideas that are going to be changing the business for the positive for us.
00:09:57
Speaker
I love
Impact of Small Changes in Testing
00:09:58
Speaker
that little clip so much. I'm going to cut that out and use that a hundred times I'm telling you. No, that's wonderful. the i The momentum, right? It's it's a lot harder to start to stop a moving train. And i think that Exactly. Yeah. And so a lot of people are excited about that with PBX.
00:10:18
Speaker
The question I usually get is, okay, but are they just little ideas? Is it just a thing that like your example of, oh, this is like a little test that was probably going to win. Should we even waste our time building it? Versus I built this thing. Let's just go ahead and try it. We know it's probably solid.
00:10:36
Speaker
Can you tell us a little bit more about the diversity of complicated tests that you're building? What is the level of effort that you're putting into PBX and what what outcomes are you getting in terms of complexity of tests?
00:10:50
Speaker
Yeah, great question. So I'll go in different levels of of of effort. The simple ideas, the little ones, the little ones that even dev would say are little, these can be done. These are the bread and butter of PBX. They can be done almost with one prompt, okay, easy to do, easy to execute. Now, the ideas, so this, this is, for example, what I mean by these easy ideas are like hiding an element or moving existing features around.
00:11:17
Speaker
This is so easy with PBX. Now, the ones that I would consider medium, medium ideas, medium medium level of effort, right? It includes different pages or it includes a different flow or it includes creating something new or something like this.
00:11:34
Speaker
or it has different elements that, for example, adding an add to cart button on ah on a recommendation zone. This is a little bit of ah of a bigger task than just changing the color of a button, right? And with PBX, what we've noticed is it's it's been able to tackle Many medium ideas and some medium ideas it can do up to like 80% and then we can have the dev team come in and just do that last little bit to help us um to help us finish it. So it still decreases the work of the developer. And for the harder ideas, I mean, what what I consider a harder idea is it involves different systems. PBX is not going to touch these different systems, right? So if it if it involves my my product, my product and management system, if it involves our um
00:12:28
Speaker
content in and that lives in somewhere else. Okay, this is not going to be touched by PBX. This remains a hard idea. in When we think about it and in that terminology, we'll still need interventions from the different teams, but it does alleviate a lot of these medium to to easy ideas that even some easy ideas have been in our pipeline for a year because they might be easy, but they might be considered, yeah, they're they're not going to do much. And so we don't do them. But because they're ready and ready to serve, we've been able to slip them through the cracks. Hey, we got this idea ready and our property is ready. Does anybody have any objection to running this test?
00:13:11
Speaker
No. OK, let's run it. And we've run a lot these way. What I've seen in my career in Crow, i this is also another great example of what you're saying, is the little tests can have just as big of an impact on your bottom line as your bigger tests, especially because they compound on each other, right? So when you're changing a button color, reordering, changing the headline, da-da-da-da-da-da-da, over time, you end up with a huge change to the page, right? It may take more time. slash it doesn't plug into those complicated tech stack problems. right
00:13:41
Speaker
We see that all the time where somebody's like, oh, I'm you know creating something that new and it connects to our CMS and it connects to Shopify. right This is a a complicated test. But these little ones can have just as much impact as as the larger tests and PBX allows you to run faster on those little ideas.
00:14:01
Speaker
And the medium ones. i I appreciate that you brought that in there. PBX is getting better every day too. So it'll be the blink of an eye before we wrote like before it's handling all of your really complicated tests, which is great. And then your dev team can focus on all of the implementation. But I'm curious if you have found that to be true for your program, the little tests. compounding that impact and having a really big impact on your bottom line, right? I think that it's really easy to say, okay, let's run fast, run fast, run fast.
00:14:32
Speaker
I want
Measuring Test Impact with ROI and Opportunity Cost
00:14:33
Speaker
to make sure it's not a hamster wheel, right? I'm saying I, the proverbial. And, you know, tell me a little bit about the impact to your bottom line and how you're measuring that as a result of the velocity increase you're seeing with PBX.
00:14:46
Speaker
Yeah. So, To your point, these can accumulate over time, right? Because when we run several tests, then we have the task of looking back, of looking back and noticing trends. And this becomes the that concept of winning and losing tests, right? And the learnings that you get are still grand even if you lose. And I think of so many examples where we had a losing test, and by this I only mean the hypothesis that we had in place,
00:15:14
Speaker
it it um didn't match what actually happened but we learned so much up from it and in those cases i we still have meetings today where somebody will bring up a test that happened three five years ago that was a failure because we don't want to make that same mistake again like we learned something about the consumer And ultimately, that's what we're trying to do with all these tests. We're really trying to understand our consumer, what is their preference. And when we do all what we consider these little tests, ultimately, we're learning the behavior of it, of the consumer.
00:15:49
Speaker
And they'll aggregate for us to do better, better decisions, better features, better U.S. in the future, um we tend to put an ROI for each for each test in estimating what it would be if we were to implement this test or the opportunity cost if that if that test was a failure.
00:16:12
Speaker
And because we didn't launch it without testing, how much money did we save so we put this little number, but it's more of an internal check for us in just to kind of.
00:16:23
Speaker
show
AI's Expanding Role in Experimentation
00:16:24
Speaker
effort the the efforts that we're putting into our experimentation program yeah that risk assessment is is a huge part of understanding the impact of what could have been launched but lost and i think that a really healthy program has both of those measurements so i love that you brought that up because people are going to listening to this and maybe they're like just focused i mean i've worked with teams that are okay we really just focus on roi we're not really focused on opportunity costs we're not really focused on risk risk evaluation but it really does start to paint a picture of what your users want and speaking of what your users want i'm i'm curious how else you're using ai so pbx has grown astronomically since it was originally launched And but as it was originally launched as PBX build right helping you do exactly what you're saying, which is taking these little tests and every single day it's getting better at building that. Now we have PBX ID eight which is coming up with ideas and prioritizing them on pages. And now we have PBX MCP so you can there's no longer a separation between experimentation and feature flagging. These are all one big tool under PBX. And this is like a very recent launch, but I'm curious, are there any other AI tools in specific that you're using for ideation? i think the, what are our, because that all comes back to what your user wants and what you're learning. Are you using AI to analyze insights? Are you then putting that back into a custom GPT, for example, to help you generate ideas? Is there any other place you're implementing AI to speed up velocity at any other stage in the experimentation workflow?
00:18:02
Speaker
So for experimentation, not quite yet. No. I mean, we have many cases and I could share many of how we're using AI and how how we even test AI features, AI solutions, AI vendors and and things like that. but Within the ideation, I saw Drake's demo and I saw in the in the Vancouver Unite, and I'm actually super interested in this product in this product. So we're actually in the process of trying to get access to it, trying to add it to our contract, because I think this would be a big game changer for us. Based on the demo, again, I don't have hands-on experience with this, but based on the demo, the thing that I liked about it the most is the tieback to
00:18:47
Speaker
the the science behind it the what is it, the behavioral economics of it. like why are they recommend Why is it recommending this? so In other words, I think in in one of the examples that Drake showed, it was like in your PLP, in your product listing page, you should have instead of three product instead of a grid of three products in per row, have four. and Because the choice giving them more choice will allow you to buth blah, blah, blah. and Just this fact of having this these concepts explained is is such a powerful thing. And if I remember correctly, it also even gave an ah ROI or an expectation of how how much of an impact it would have on your site. So I am really interested in testing this out. We haven't yet, but excited because hopefully, maybe in the in the next few weeks here, we get access to it.
00:19:40
Speaker
Yeah, I ask because so many people listening to this are, they're getting the, how do I implement AI? I don't even know where to start. They don't even have PBX, right? So this is just great context to have. I love that you're about to be building that in. I actually did a really good a webinar, a little shameless self-plug here, but I did a really good webinar with Drake and it went a lot into the nitty gritty details of okay, how are these tests created? Where are they coming from? Why are they prioritized like this?
00:20:07
Speaker
Tell me about the consumer
Evolution of Experimentation Metrics
00:20:08
Speaker
psychology behind the x y and Z. And he did an excellent job. So it was kind of like the part two of that demo where he explained a lot more of the backend and the build of PBX ID8. So if you're ever interested, anybody listening or yourself in listening to that, I have a few clips that I've shared on LinkedIn and i have a write-up of my takeaways on my LinkedIn as an article. So totally feel free to check.
00:20:31
Speaker
Perfect. Yeah, I saw it come through and I was excited to to see it. Yeah, thank you. i love working with Drake. ah But and this is all great. I think that AI is really changing the landscape. extremely quickly for experimentation. I mean, for every industry, right? Like we're seeing this everywhere. i think it all comes down to what your core truth is. Your little, I'm calling it a pillar of truth for you is how do you understand your users? You did a really cool talk at the United Summit Vancouver that we've mentioned, and you mentioned a lot about KPIs, primary and secondary. um i'm I'm curious if you have a take on what some of your best practices are when you're talking about metrics. and what are some common mistakes you might see when people are, they're getting they're getting really fast, right? We have an idea, we have it 90, 100% built in PBX. Now we come to the metrics part, which can feel like another bottleneck. So I'm curious what experience you have navigating that part of what is the future bottleneck that will be unlocked by PBX.
00:21:35
Speaker
I mean, really our experimentation program has changed so much. over the years. And I challenge my team this all the time, right? Like we know as much as we know today and hopefully tomorrow we'll know more. And the moment we know more, we pivot and we are very transparent with the business the moment we do. And looking into these these metrics is one of them.
00:21:55
Speaker
When we started out the program many years ago, we were session based. And one time I remember seeing this woman speak about how you were hurting your experimentation program if you're doing it session based and not user based. And
Significance of Primary and Secondary KPIs
00:22:09
Speaker
because by a test being effective, you would get a returning consumer. But because you were not looking at it correctly, the math wouldn't add up and it would be detrimental to your past.
00:22:20
Speaker
We changed it. We changed it immediately. We tested it out and saw that. um her points were so valid to so many of our tests that we made a change for for for this. And the the metrics that we use, so this idea of when we have tests, we set the hypothesis from the very beginning.
00:22:38
Speaker
And our metrics aren't always conversion rate. If it's further down in the funnel, if it's in the checkout, for sure, we'll be looking at conversion rate. But when we test, and because we're running multiple tests at the same time, we tackle what's the immediate next step.
00:22:54
Speaker
So if I am changing the way my filters are are are being shown, my main KPI is interactions with the filter. My secondary KPI is do they view more product?
00:23:08
Speaker
If I'm testing something in a marketing campaign, I'm my primary metric might be, are they clicking through do they come to the website my secondary metric might be bounce rate, I want to make sure they're not just bouncing right. So it's idea of this idea of having your main KPI and it's BFF like we need to make sure that when you do a test, you are corroborate like a set word corroborating.
00:23:36
Speaker
that you are corrupt, corrupt. Now I can't remember that word. Okay. That you are making sure that that story makes sense, that it's truthful, right? So you don't want a test to just, I want to bring in traffic. No, I want to bring in qualified traffic. So my sessions, my users go up, but my bounce rate doesn't skyrocket, or they're still showing whatever behavior you're going for, whether it be the time on page, the view, the pages they see, interactions with your filters that they're not just interacting, but then that but then they bounce or something regarding your search or if you take the price away.
00:24:12
Speaker
Okay, you're going to get more clicks sure, but did they actually continue down the funnel or did you just frustrate them right so it's that idea of checking the immediate next two steps.
00:24:23
Speaker
And having these combined metrics together to always make sure that you're you're showing the right story that what that what you're testing makes sense, so that idea of you have your step one.
00:24:35
Speaker
Your step two and your
Understanding Consumer Behavior through Experimentation
00:24:36
Speaker
step three let's pretend we change something in the filters so interact like aim. you're changing or something in your filters is your step one. Your step two is interacting with your filters. If they interacted with it, that's good, right? That's what we were going for. Step three, did they did they view product? If they did, so the division of that step three divided by your step one, this is also important because if you inflated your step two and you just look at step three divided by step two,
00:25:04
Speaker
then you might be negating the fact, right? You might be hurting your formula. But if you divide step three by step one, then you get a story. Did you actually get a lift overall? Or were you just inflating that that first step?
00:25:18
Speaker
I really like that i ah visual, right, that you're you're painting here. i think a lot of people are going resonate with that. As a practitioner myself, when I'm looking at a test, I'm thinking my primary KPI is the closest to the change. And then from there, though, you bring up this excellent point, which is context. And I think going back to AI, it's such a focus of what we're doing at Chameleon.
00:25:44
Speaker
The AI doesn't understand what's important to your leaders, right? Not at the stage it exists today. and And maybe it's easy enough to create it in there and tell it what's important. But at the same time, there's an emotional intelligence that AI doesn't have in terms of you saying, okay,
00:26:01
Speaker
let's Let's go with a PLP example. I want to see how many people are viewing products. Okay, are they viewing more products? Are they clicking more products? Are they actually adding to cart? Or is their IOB increasing? There's the different ways you can get to a meaningful story arc with the metrics you're using. And sometimes that meaningfulness, I don't know the right word there, but that meaning is
Human Role in Analyzing Experimental Insights
00:26:26
Speaker
originally generated from a leader's POV, one of your team members, but KPI, OKR, whatever it is, right? Insert generic acronym here. I'm curious where else you see the human creativity not being lost in the loop because we talk about AI so much. It can automate. You've done an incredible job illustrating how PBX has increased your velocity for build.
00:26:52
Speaker
Where are the humans still having the most impact in your experimentation program, you think, today? In everything. Yeah, that's the best answer, right? Isn't everything?
00:27:03
Speaker
Yeah, I mean, AI is a tool. And I remember going to um an AI conference a year ago, actually. And it it was a great conference of AI across industry. And I remember this one gentleman putting his hands up and saying, you know, right now I could fire 80% analysts.
00:27:25
Speaker
And I just couldn't believe this fact because either one, he's not quite in tune with what his analysts are doing. Number two, they're doing too much of a manual task. And in that case, yeah, being used incorrectly. Because when I see my team of analysts,
00:27:42
Speaker
What they work on is not manual stuff. And what we need analysts for are for this idea of understanding concepts, of understanding what's important to the different teams. What is going on with this promotion? What is going on with the inventory over here? What did this team, what is top of mind for them? Because sure, maybe it's going to get, maybe it's better at identifying trends, at taking a big data set and identifying things here. This is great.
00:28:13
Speaker
but to understand what other factors that we did not put in or to clean up the data before we feed it in. right like All of this takes human intervention. so Our teams are pivotal in in every step of the way in creating it and feeding it in in making it resonate in the storytelling, because at the end of the day, if you have something wonderful, but you cannot connect to the audience and ah going back to that translation piece, you can have all the beautiful insights.
00:28:47
Speaker
But if you cannot make a marketer, if you cannot make a salesperson, if you cannot make whatever audience understand it and act on it, it's nothing. It's just
Enhancing Communication Skills
00:28:56
Speaker
words on a paper or numbers on an Excel sheet, right?
00:29:00
Speaker
You did an incredible job tying it back to the very first thing we talked about. It's like you're a professional podcast guest. I love that. Yeah, it I think that there is that politics is what I want to call it, that AI isn't going to be able to manage in its current state, um that people are so important in making sure gets done. um Wonderful. this is all We have so many...
00:29:26
Speaker
Good nuggets for people to listen to here and learn from your program. I know people are probably going to be finding you on LinkedIn and sending you a message and saying, oh my gosh, i loved your episode. Of course, I'm assuming there's so many people listening to this episode. um But my last question for you is kind of the same question I ask everybody, which is...
00:29:48
Speaker
Let's say somebody, a lead, a analyst, a designer, whoever is, you can pick the persona, but they're listening to this show watching it on YouTube, listening on Spotify, whatever it is.
00:29:59
Speaker
And they're curious, what am I going to do tomorrow to start to get closer to speeding up velocity and translating complex ideas in a better way, which are the things that you do so well. What are some tangible next steps you could provide someone leaving the show?
00:30:18
Speaker
To work on your communication, to practice it, right? Like in in the team, we we've at times done presentation training. And what this meant is like we presented to each other and we said, Katie, you have to present PBX, present it to other, present it to somebody like Drake.
00:30:36
Speaker
or to call into somebody involved in the industry. Your wording used is gonna be very different. And so you had to pitch this for two minutes. Now presented to a 10 year old, what words would you use? And you have to make it entertaining for them, you know, or presented to um to somebody who, yeah, to your grandpa presented and now take two minutes to present PBX to your grandpa. And so it it's this idea of practicing and to listen to others, what what when do you think, or in other words, taking a look at other people that you believe are good presenters, what's the commonality among them? What do they do? How do they get their message across and learn from that? Because the best experts can take a complicated topic
00:31:30
Speaker
and make it simple. When you're a young analyst, it's like that idea of when you when we were kids in math school and they gave us a math problem and the teacher was like, I need to see all the work, you know, and you remember you would write down all the work and then finally the answer.
00:31:45
Speaker
And now it comes about that in our day to day life, we didn't need to cut out all the work. When you're a young analyst, you want to show, oh, yeah, OK, you gave me this problem and then I went down this rabbit hole and then I had these many issues and then I put this this thing, but then I put this other thing and then I put this other thing. And here's the answer.
00:32:05
Speaker
But the more experience you get, you come out and you just simplify it and you make it look very easy, even though it costs you a week of time to come up with this answer. But you you present you you don't need your audience to know that, right? you You can get your audience to just understand. They don't need to remember. It's it's even something as like something we work on with my team is like, do they really need the decimal point?
00:32:29
Speaker
For some cases, yes, I want 0.1 decimal point. This is important. But in most cases, the 40% is enough. I don't need to know 40.2. They're not going to remember 40.2. They'll remember 40%. In other cases, it's important. 0.76 is important for whatever. But it's always tying back to the concept, like understanding your communication, the message you're trying to get across, and just getting good.
00:33:00
Speaker
at communicating. This is just the the best self-skill in life that we can do right now is to to keep practicing and and and getting better at and at our messaging.
00:33:13
Speaker
That's wonderful. Thank you so much. And I think that it's something I'll always strive for myself. Being the host of a podcast is a horrible and extremely effective way of getting better at communicating because I'm just like,
00:33:27
Speaker
constantly listening to myself. So I
Conclusion and Future Collaborations
00:33:30
Speaker
think that to build on that, the thing that I found was the most helpful in building my communication skills is recording my QBRs, recording my ideation sessions.
00:33:42
Speaker
It's, it sucks. Don't get me wrong.
00:33:48
Speaker
That is just a soft skill that humans uniquely have. And i really appreciate you lending your time to talk to us about your experimentation program and I know people are going finding you for more information. I'm so excited to see you in London and maybe Paris for Unite Summits later this year. And yeah, thank you again for your time. I can't wait for the world to see this episode.
00:34:11
Speaker
Thank you. Thank you so much, Katie. was wonderful. See you soon. See you.