Okay. Thanks everyone for joining us today. Today, we're talking about unlocking growth through opportunity sizing. I am Emily from MoonPay. We are on the data team.I run the data team, which can consist of data engineering, data science as well as ML, and we are in a company that does crypto ramps. That means that we help basically people onboard onto the crypto economy. It is essentially the PayPal of crypto, as we like to call it, to make it easier for those who are not in crypto to get what we, what we do in on a day to day basis. I want to introduce Panri. I think, would would you like to say a couple words about yourself?

Yeah. Thank you, Anri. Hi, everyone. I'm Panri. I'm a staff data scientist, as the data team here at MoonPay. I've been here for a bit more than a year, and I have worked, across many product areas at MoonPay already. What I do on a day to day basis basis is help, our product team to improve their product by conducting, analysis, experiments. And most recently, we're building a lot of AI tools, help humans have a easier life. Previously, I worked at Deliveroo and booking.com, and I came from, actually, a finance background.

Thanks, Barry. Before I get started, I want to make this a little more interactive. So can people put in the chat, what kind of company you work for? Is it the startup, if it's a big corporation, etc? I want to just get a feel for who has encountered, the problems that we're going to be talking about today and as well the solution, of course. Government? Okay. Legal tech? Corporation? Great. Any others? No. Okay. Leasing company? Cool. Presuming this private. Game dev software. Great. Four k. Automated leasing. Okay. Great. Logistics. Awesome. Okay. So quite, a large group of diverse companies and diverse roles, diverse purposes, etcetera. The great thing about what we're going to present to you today is that this is applicable to pretty much anything.

It can actually be applicable to to life in a lot of ways as well. I think everyone has probably experienced in the companies that we work on or, again, in life, you know, needing to make decisions about how to prioritize, how to make sure that you and your team or even you individually are working on the things that are the most high value and the most impactful.

I think a lot of us, have been in jobs in which you have felt perhaps a little bit disillusioned, by the lack of impact that you're having and slash or the role of what you're doing in a larger picture. So Pammi is gonna walk us through the opportunity sizing framework today. Feel free to put any questions in the chat if you have any along the way. Without further ado, thank you so much. Pamir, go ahead.

Yeah. Thank you. Let me share the slide deck we prepared. Right. So I'm going to walk walk you through, first, what is actually ops resizing. And Emily already mentioned a little bit why we should do it, not only in our job, but also in our lives. I'm also going to emphasize on that as well. And then I'm going to introduce, like, when and actually how to use it. And in the end, I will introduce some, three basic, methodology that's gonna help you to actually do this optimization. And in the end, I'm also going to talk about some limitations about this framework and some actionable takeaways for you to, bring it to your business or your, company or even your life. And in the end, we'll also leave some time for you to ask any, questions you might have have. Cool. So what is optimizing?

In one sentence, it's basically to estimate the impact of doing something. For example, if we expand our product to a new market, we will make x amount of more money per year. Or if we want to optimize, our product flow, which will improve our new customer conversion, and we will make x amount of more money per year. And another one is if we optimize our usage of a certain software, we can probably save y amount of dollar per year. And then why do you want to estimate, the impact of doing something? It's because we want to make sure that we're investing our efforts, our money, our human resource on the most impactful initiatives.

First, it helps to standardize the process and, the road map or planning session by evaluating potential opportunities across the company using the same frame framework. It helps to avoid subjective decision making with some, data and math. And, also, it's help, as I mentioned before, avoid misallocating resources. Because as a company, we have limited people, limited cash. We want to invest, as we wanna invest as much as more in high impact in initiative, and we don't also want to overlook them. On to the next. This is a not so good example of how a road map or initiative list might look like. So you will see, we want to improve feature x because some important person asked for it, or fixes this bug just because this been there for a while, or we want to expand to this new market.

Otherwise, we, sorry. We want to expand to Mars. Otherwise, we lose all alien customers. Or we want to build this new platform just because a competitor, just launched it. This list, you can see there are some rational behinds ideas, but you are not clear on, okay, what is the impact, and how we should prioritize this. And here is, in the ideal scenario, how a prioritization or a roadmap list should look like backed by opportunity sizing. So here, you can clearly see for each initiative what is the rationale and what is the math, behind the opportunity sizing, and what is the actual priority, based on the sizing, results. So taking the first, expanding our new feature to Mars as example, we know our alien customers are high value customers, which can generate 50 k dollar net revenue per per customer per year. And expanding our product to Mars will acquire up to approximately 100, customers.

And simply by multiplying by, this, net revenue per customer as the number of new customer, we can easily guess okay. This can potentially bring us 5,000,000 per year. And, the next one, fix bug why, because it's a broken flow in our checkout page and it's costing 10¢, of failed transactions. And we are losing 3,000,000 money on this, and we believe fixing it will solve 90% of the problem, which means the potential upside of our revenue is 3,000,000 multiplied by 9¢, which is nearly 3 $22,700,000.0. And I will skip the rest two, but, you can see for each initiative, you have a clear rationale. You have a clear methodology or data backing your impact sizing, and you can also see why we are ranking, this initiative over other initiative. So when and how you can use this?

Whenever you have a long list of ideas but limited time and resource, for example, during the quarterly road mapping or planning or during the AI time sensitive hackathon, Or if you are not sure if something is worth building or show your cuss show your stakeholders why you are prioritizing or deprioritizing their big ideas, without bias.

Or demonstrate your team on why they're working on certain projects and what kind of impact it could have. And then on how to use it, I'm going to introduce some basic methodology in the next section. And, also, if you came from a nontechnical background and want to cite some very complicated, scenarios, reach out to your data team for reviews and further help. Cool. So there are three common, methods. Before we start with that, I want to note that make sure that you are measuring your initiative, by your company, OKR or NorthStar Metrics. I think I saw a question raised by someone. Is it always has to be in money terms or cash terms?

It doesn't, but you want to align your option sizing results, with your company OKR. So, for example, if a new gaming start up, care mostly about, new number of new users, you should be measuring your initiative by what how many, incremental new users your initiative could bring to the company, rather than, revenue. And for some mature company, you might care about more about gross profits. So make sure that's, you understand your company OKR before starting, actually doing the sizing. Cool. Then three methodologies. First one, directional t shirt sizing. So by the name is, a very simple, low rigor, low accuracy, methodology. It and is mainly used for existing initiatives and is based on rough estimates and is mainly used during the early ideation or sanity checking, stage. And second one, bottom up sizing, is also for existing initiatives but has higher rigor because we are using a lot of, internal data points, for example, comparable data, product data points, and, more, conversative or, extensive assumptions.

And it's usually used to size initiative during a later stage. For example, you really want to guess this into your road map. And so the last one, top down, is usually for new new initiatives and based on a mix of internal and external information. It also has higher rigor, and it's, usually also happen during the later stage, when you want to really get something to a road map. And, also, due to the fact that you're using a mix of internal and external data points, it has, like, uncertain accuracy. And, for example, if you want to, like, enter a new market, build a brand new product, it's hard to be, like, very certain about the estimated impacts. Now I'm going to walk you through the examples. So first one, directional T shirt sizing. And the example is, we have a idea now.

We want to optimize our customer onboarding verification flow in The UK by switching to a new k v I KIC vendor. So for context, because we are a crypto WAMS company, we have to verify our customers' identity before they can buy crypto in The UK. And, you know, the customer has to provide a lot of documents, which is high friction, but we want to make that experience as smooth as possible to so we onboard more customers. So we have a few assumptions and data points. By the way, all the numbers and scenarios are made up. It's not real. Our current KIC pass rate is around 30%, and the benchmark provided by this new potential vendor is 40%. And we have a number of KIC customers in the last year is 10 k, and the average net revenue from customer who passed KIC is around $30.

So the estimated impacts of switching to a new vendor essentially will be the uplift on the KIC pass rate multiplied by number of KIC users and then multiplied by their net revenue, which, in the end, is around 30 k per year. On to the next. Bottom up, is, a bit more complicated and also more accurate. The example here is, we want to improve our checkout's, click through rates, by providing translation into, on the checkout page. So we have a few assumptions and internal data points. For example, we know our average number of non English speakers visiting our checkout page daily is around 10, and our average English speaker checkout conversion rate is 50%, but our non English speaker checkout conversion rate is 40¢. We have assumption that, the conversion rates for non English speakers will be similar to English speakers if we add translation.

And we also have a average transaction success rate, which is after the user converter on the checkout page is 90¢. And we know that our average net profits per transaction is $3. So the estimated impact is our daily non English speaker volume multiplied by the expected uplift checkout page conversion and multiplied by transactions access rate and then the profits per transaction and days in the year. And in the end, you get, nearly, 1,000,000 incremental net revenue. And last one, the top down sizing. The example is we want to expand our crypto business to a new market, Costa Rica. And we have gathered a few external data points, which is, we know the population in Costa Rica is 5,000,000, and external research shows that nearly 10% of the population trades crypto.

And we did internal research, which suggests that our pricing is lower and our competitors, so we expect to acquire 20% of their users in a month with very ugly, aggressive marketing. And, also, based on internal data, we know that's our average net revenue per customer per year from our existing customers in in North America is around $3. And we know that our marketing will cost us, 3,000,000 in the first year to expand. So the estimated impact for year one would be the 5,000,000 population multiplied by 10% of the crypto users, multiplied by 20% of the users we can take, multiplied by their average net revenue per customer, minus the investments on marketing, which will be, breakeven for year one.

But after year one, because we will be spending less on marketing, we expect to generate positive cash flow. Those are the most common methods, and, I have also walked you through the examples. So feel free to try them out and apply in some basic scenarios in your work or life. And now I'm going to talk about some limitations about opportunity sizing. So first, because there are a lot of assumptions, and even external data points and something we're not certain about. So we will never be 100, 100% accurate and even 50%. And, also, not everything is sizable. Sometimes, also, it takes very long, to do a very comprehensive analysis. But I want to know that, option sizing isn't really too much about making a very precise and accurate forecast. It's a estimate. It's usually done very quickly.

So it can so it's destined to be off by some margin. But the purpose is really about creating this separation. So it's easier to make decisions, compare your initiatives across the company, across the team. So ideally, you can just focus on the great ideas. And if you have extra bandwidth, take a take a gamble on some average projects. And so we also suggest to apply some, like, different assumptions. For example, use bare neutral bull scenarios, in your calculation so you can easily adapt, in case of a market condition change. And, the actionable next steps. So if you haven't heard of or applied any optimizing methodology in your company yet, I would suggest to start with understanding and set your company OKR because, that's the key metric that you're being measuring against. And also understands the, like, where where your company is currently at.

For example, like, in the maturity and size, and then adjust the framework accordingly according to your company situation and promote it across the business so everyone can adopt it, actually use it. So, it will be much easier when you, like, prioritizing the initiatives across the company. And last, because you brought this good idea, be ready for, incoming request for from your stakeholders. That's all from me today. Hope you enjoyed it. And now I will, look at the, chats to see if there's any outstanding, questions.

Could you put the T shirt sizing example back onto the screen so so that someone can take a Nirmen can take a screenshot? Yeah. Great. Yeah. So it's been reset, and as I've been chatting to all of you on the chat about, this is very much a modular approach to getting a lot of things done. So again for prioritization for yourself, as Palmer mentioned, but also, especially because we're a woman in tech, I know that, you know, a lot of women, myself included, you know, we've been in situations in which you have this great idea and you're really just not getting traction on how, to get buy in and how to, kind of rally people around this great thing that you want to do.

And this really allows you to, one, sense check your own ideas and, two, to really help people understand this is this is big, this is impactful, and this is something that we should really enable people to focus on and to, organize, you know, the either your organization or your structure, your own team or yourself again to make sure that it can get done, because, yeah, this is, provably, provably valuable to various parties including, including the company and ideally, you know, society etc.