492: Business Intelligence for Startups

[0:00:01]

Steli Efti: Hey everybody, this is Steli Efti.

[0:00:03]

Hiten Shah: And this is Hiten Shah.

[0:00:04]

Steli Efti: And today on The Startup Chat, we’re going to talk about business intelligence for startups. So here’s the deal, Hiten. 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 of data and insights within your company. I think when you’re just starting out in your startup and you’re a handful of people and you’re working day and night and you’re super involved with everything, you generally have, and should have, everybody care about data and look at the numbers. Look at the information and collect and do the research, and constantly and consistently generate insights that help you adjust and pivot until you figure out 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 do we bring this to market? All these things. But as your company grows and as you become 20 people and then 50 and then a 100, and as your customers are now thousands and thousands of customers, and you grow to hundreds of thousands and millions in revenue, the amount of data in all regards of your business, this can be marketing data, this could be sales data, this could be success data, this could be product metrics and data. The amount of information in your business skyrockets. And there comes a point where any time there’s a question around specific metrics, you can have a team go after it and try to figure it out. But it seems like there are more and more companies that will have somebody or a team that’s actually, to a large degree, responsible for doing business intelligence, which means having an overview and an insight 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 holistic view and the mandate to be looking and driving data to generate insights for the business. And this is still a new field. 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 chat with you a little bit about this, because I know you are incredibly experienced and insightful when it comes to data in companies. So first of all, when you think about business intelligence for startups, is that just bullshit? Is that an amazing field that needs a lot more investment? What’s your initial reaction when you hear that?

[0:02:54]

Hiten Shah: Yeah, I think that at some scale, something like business 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 official inside of companies is really what we’re talking about, I think, in great part. And at that point, you have dashboards, and teams are looking at dashboards and are making decisions based on what they see in the dashboards. Ideally, this is happening on a meeting by meeting basis. This isn’t something you just do once a quarter. And so then once you start developing that workflow or that type of way to run the business, you end up needing business intelligence, as they say, which really a lot of times just points to dashboards. But those dashboards are powered by data. That data is when you started. 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 basically a business intelligence team, or buying a product like looker.com or something like that, where you can have dashboards that help 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 the whole company should be looking at data. And in some parts of the organization, they’re using a sales tool if it’s sales. Marketing is using a certain marketing 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. It’s really tricky when you’re trying to put data together across all the departments, especially if some of those departments have some level of scale, like handful to 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 kinds of things. This is a big business in terms of business intelligence. The big question is just, how do you do it just in time or with enough capital or resources that you can put behind it so that you can be successful doing it? There’s so many failed attempts at this inside of organizations. It’s one of the probably areas that fails, that at the same time can have the biggest impact in a business, but also can be one of the most wasteful things a business tries to do.

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Steli Efti: Yeah. It’s one of those areas where a business might be not that data driven, not have a good handle on the dashboards and the analytics and the metrics, and then at some point it becomes a glaring issue. And then it’s like an overreaction is the attempt to solve this. Let’s put together a 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 these individual teams that have the biggest need for a better handle on the metrics and on the analytics and numbers just hire an analyst. So the marketing team might hire a marketing analyst, or the sales team might hire a sales analyst, instead of just building from the get go a business intelligence department or group. These teams will identify that they, themselves, have a big need for it, and then 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 would entertain hiring somebody like that, it’s a very different hire from the culture before. 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 evaluate this person’s performance and how to integrate them into the entire company, it would be very difficult because the people are not difficult but different. Because the type of people that we used to hire as a startup, you start hiring developers, designers, salespeople, marketing people. Those people are much more direct impact and their work product is much more transparently viewable. And then when you start hiring for ops roles, and then even later now for an analyst role, it’s much more outside the sphere of where you operate probably in the first couple of years as you grow. What’s your recommendation there? Is it a good idea even to think about hiring an analyst or building a BI team at some point? Or would you always say the company should just try to have everybody in the company become more data aware and better at it first before hiring externally and bringing somebody in to own that area? What have you seen work best here?

[0:07:52]

Hiten Shah: I tend to try to start by using the tools that might be available to me and using the teams that are helping with that. 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 BI solutions that I see at a lot of startups. Once they hit 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 an analyst, as long as you have some engineering resources and somebody who owns it. I think I’m more concerned about who owns it internally, and less so about hiring an analyst or even data people.

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Steli Efti: Makes sense. What are some of the tools for the dashboards or for just getting a better handle on their metrics for startups in the earlier days? This is maybe advice that a lot of our startups reach out to you and ask for. It’s like, okay, maybe this is between 10 to 100 customers, five to 10 people, and it’s 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? Should we put together a number of tools? Should we just use one external tool? Do you have any recommendations there? Any tools that you think work well in the early days for startups?

[0:09:30]

Hiten Shah: Yeah, I try to get as far as I can with the tools I’m using already. So Looker is a really good example if you’re thinking of going from the standard Google Analytics. And Amplitude if you want something deeper and you have resources to put towards it. So that’s the one way to think about it. And the other way is literally just utilize what you have. I think that’s underrated. Whatever you’re already using, whether it’s whatever sales tool you’re using, using Google Analytics and all that, try to use the reporting functionality and dashboarding there. And sometimes importing that into Google Sheets or Airtable or what have you can be good enough to get you really, really far, before you need to go get all official with the BI and data project and things like that. So I tend to just start with, what do we have already and what can it do for us? And then figure out in that process, what are the gaps before we really go into hiring or having a big initiative around it? I didn’t see too many companies running too fast into this.

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Steli Efti: Awesome. All right. This is it for us for this episode. We’ll hear you very, very soon.

[0:10:56]

Hiten Shah: Later.

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