492: Business Intelligence for Startups
The Startup Chat with Steli and Hiten
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Full episode transcript -

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everybody. This is Stella TFT,

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and this is heating shop.

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And today, in the style of Chip, we're gonna talk about business intelligence for start ups. You like talking about more than your sales and market. We just want a bullshit chat about business and life, and hopefully, while we're doing them for my long value to be the best for people trying to get shit way, don't want to give you feedback. That's bullshit. You want you to do your best. So here's the deal hidden. Here's a trend that I've seen over the last few years and also something that's been on my mind. It's the big topic off data and insights within your company. I think when you're just starting out in your startup and you're a handful of people on your working day night and you're like Super Bowl with everything you generally have and should have everybody care about data and look at the numbers and look at the information and collect. Do the research and constantly and consistently generate insights that help you adjust and pivot until you figure out out of the big building blocks of your business. Try to figure out what is it that we're building? Who is it that we're building it for?

What differentiates us? How to bring this to market all these things. But as your company gross and as you become, you know, 20 people, then 50 and then 100 is your customers are now thousands and 1000 customers, and you grow to hundreds of thousands of millions in revenue. The amount of data in all regards of your business. This could be marketing data. This could be sales data. This could be, you know, success data. This could be product metrics and data. The amount of information in your business skyrockets. And,

you know, there comes a point where any time there's a question around specific metrics, you can have a team kind of go after it and try to figure it out. But it seems like there's a there more, more companies that will have, you know, somebody or a team that's actually to a large degree responsible for doing business intelligence, which means having an overview in an inside into most of the big business metrics and trying to generate insights or view opportunities or risks ahead of everybody else because they have a kind of a holistic view and the mandate to be looking and driving data to generate insights for the business. And this is kind of a still and you feel there's a lot of bullshit involved. There's a lot of lack of clarity on. Is this needed? When is this needed? Who should be doing this? How should it be done? So I wanted to check with you a little bit about this because I know you are incredibly experiencing insightful when it comes to of data in company. So first of all,

when you think about, you know, business intelligence for startups, is that just bullshit? Is that in an amazing field that needs a lot more investment? What's kind of your initial reaction when you

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hear that? Yeah. I think that at some scale, something like with this intelligence starts making sense inside of a company. A lot of it has to do with the company culture. How data informed the company wants to be or is. I think this is a very fascinating topic, because at the end of the day, you're always doing business intelligence as long as you're looking at some metrics When it starts. Getting a fischel inside of companies is really what we're talking about. I think in great part and at that point, like you have dashboard and teams are looking at dashboards and are making decisions based on what they see in the dashboards. Ideally, this is happening on ah, meeting by meeting basis. This isn't something you just do once 1/4. And so then once you start developing that sort of workflow or that type of that type of way to run the business,

you end up needing, like sort of business intelligence, as they say, which really a lot of times points to dashboard. But those dashboards air powered by data. That data is when you start like that data, making sure it's accurate, making sure it's the right data, making sure that the teams have what they need across the whole company. That's when you start building out, like basically a business intelligence team or the buying a product like looker dot com or something like that, where you can sort of have dashboards that hope the whole company see what's happening, see what's going on in the company and make better decisions. So on a high level. It's really just this idea that, like the whole company,

should be looking at data. And in some some parts organization, they're using a sales tool. Fit sales marketing is using a certain monkeying tool. They already have these dashboards and these tools. The thing that gets really interesting is when you're trying to put it all together, gets really tricky when you're gonna put data together. Across all the departments, especially some of those department have some level of scale, like no handful toe dozens of people. Business intelligence starts becoming a thing, and companies want to wrangle their data and make sure they can build holistic dashboards. These kind of things, I mean, this is like a is the big business in terms of business intelligence. The big question is just like, How do you do it just in time or with enough sort of capital or resource is that you can put behind it so that you could be successful doing it. There's so many failed attempts of this inside organizations like one of the probably areas that sales that at the same time it can have the biggest impact in a business that also could be one of the most wasteful things

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of business tries to do. Yeah, it's one of those areas where the business might be, you know, not that data driven, not have a good handle on the dash boats on the analytics on the metrics. And then they at some point it becomes kind of a glaring issue. And then it's like an overreaction is the attempt to solve this. Let's put together business Intelligence Department, and you want to hire a bunch of people come in and fix this holistically when Maybe that's too big of a first step. One thing that I've seen been done a lot is that sometimes companies will start having like these individual teams that have the biggest need form or kind of a better handle on the metrics and on the analytics and numbers. I'm just high an analyst, right? So the marketing team might hire a marketing analyst on the sales team, might hire sales analyst instead of just building a kind of from the get go a business intelligence department, a group, and these teams will identify that they themselves have a big need for them to bring in somebody like an analyst person to do that.

But it's always a tricky role because most startups, by the time that they wouldn't entertain hiring somebody like that. It's a very different higher from the culture before it's like, I'll tell you for me I've never hired an analyst. And so even evaluating a person like that and knowing how do we value this person's performance and how to integrate them into the entire company would be very difficult, because the kind of people are difficult different because the type of people that we used to hire as a star of you start hiring developers, designers, salespeople, marketing people, those people you know, a much more direct impact. And their work product is much more transparently viewable. Then, when you start hiring for ops rules and then even later now for like an analyst role becomes, It's much more outside this year of where you operate, probably in the first couple of years as you grow.

What's your recommendation? There she? Is it a good idea even to think about, like hiring an analyst of building a business? The I team, It's on point, Or would you always say the company should trust. Try to have everybody in the company become more data aware and better it at first before hiring, extremely. Bring somebody into own that area. What kind of you? What have you seen? Work best

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here. I tend to try to start by using using the tools that might be available to me and using the the teams that are helping without. So, for example, if I'm using amplitude for analytics, I might talk to their team more and see what else they can do for us along these lines. I do think the team at Looker has probably one of the more modern B I solutions that I see a lot of startups. Once I hit like 25 50 100 people, they start using looker between those two. I think there's a lot of help you can get without having to hire analyst. As long as you have some engineering resource is and somebody who owns it, I think I'm more concerned about who owns it internally and less so about hiring a Nana list or sir, even data people already like that

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makes sense. What are some of the the tools for the dashboards or forgetting, like just getting more better handle on their metrics for startups in the earlier days. This is maybe advice that a lot of startups reach out to you and ask for It's like, Okay, maybe this is between 10 to 100 customers of 5 to 10 people and kind of still early days. But there's a bunch of data already coming in, and a startup is trying to figure out what should we use to keep track of all our business metrics and company metrics. Should we build something internally, like, should we put together a number of tools? We just use one external tool. You have any recommendations there Any tools that you think work well in the

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early days for start ups? Yeah, I try to get as far as I can with the tools I'm using. Ready. So, like, looker is a really good example. Uh, if you're, you know, thinking of going from the standard Google analytics and you know, amplitude and you want something kind of deeper and you have resource is to put towards it. So that's one way to think about it. Another way is like, literally just utilized what you have. I think, like that's underrated like like whatever you're already using,

whether it's whatever sales till you're using using Google. And let's try to use the reporting functionality and dash putting their and sometimes importing that in tow, Google sheets or air table or what have you could be good enough to get you really, really far before you need to like Oh, go get all official with the be hyper with like a P I the V I data project and things like that. So I tend to try and I tend to just start with like, what do we what do we have? A ready and what can you do for us and then figure out enough process? What are the gaps before we really go into hiring or having a big initiative? Er of it? I didn't see to me cos running too fast into this.

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I'm also right. This is it for us for this episode, will you?

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