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It’s not so complicated: Customer data for startups
Humberto has seen several startups getting off the ground without collecting data at all.
But gut feeling is not scalable.
You don’t need a Customer Data Platform to get started.
But it will definitely help you along the way.
In this episode, you’ll hear about:
- the value and the dangers when dealing with customer data
- why gut feeling is not scalable
- how you can use Customer Data Platforms
- 4 steps that every early stage startup could follow
- the difference between leading and lagging indicators
- Segment, as a customer data platform
- Amplitude or Mixpanel, for product analytics
- Braze and SendGrid, as email tools
- Asana, for Project Management
- Toptal, for hiring freelancers
And all these in less than 17 minutes.
Related: 4 Tips for starting with Customer Data Platforms, a detailed blog post by Humberto
Humberto de Oliveira: Hey, everyone. This is Humberto here. I’m part of the GrowthMentor community. I’m happy to be part of the podcast today. And I come from a software engineering background also worked with statistics, product management. Software solutions consulting, both in pre-sales and post sales. And today I’m going to be talking a little bit about data management and customer data forms as well. So happy to be here.
Spyros Tsoukalas: Humberto, welcome to the GrowthMentor Podcast. I’m excited to learn about customer data. So let’s go straight to the point. Could you tell us something we don’t know about startups and customer data?
Humberto de Oliveira: Absolutely. Let me start by emphasising something that you probably already know that data is a vital part of any business. If you are not already convinced, there are plenty of facts and statistics around how businesses only can become scalable and obtain funding if they collect and understand their own data. Now, I’ll tell you something that some of you may or may not know, which is that the same reports and statistics that you’ll find that most companies do not use data for making decisions. That is absolutely correct. However, it doesn’t tell you the full story. And especially it doesn’t tell you where the problem is. The sad reality is that most startups today, and even big companies do use data. And they’re sometimes very proud of it. But most of them just have a very bad data set up, which inhibits them from making such business decisions out of the data. It’s normally because they’re either not relating business value to every single data point they collect, or that they are collecting just too much data more than they need. And they are unable to make sense of it, or they don’t have enough people to make sense of the data. So in summary, every report requires interpretation and deeper investigation, which is exactly what every business should be able to do as well.
Spyros Tsoukalas: Humberto , thank you very much for the very detailed answer. You reminded me of some aspects of data and how startups use it that I had forgotten. And you reminded me of some mistakes that I have experienced firsthand. So moving on with the topic, like do you see startup doing mistakes when dealing with data, like on top of everything that you already mentioned?
Humberto de Oliveira: Yes, no, absolutely. And I’ve worked at Segment as a Senior Solutions Architect. And I’ve seen several mistakes that startups or big companies are making. As I mentioned, most early stage early stage startups, which is probably the profile that we see here, mostly at GrowthMentor, they either don’t use data to measure success or failure, or they think they do. And for the ones that do use data, some of them read all the statistics about the importance of data for any business. And most of them finally get convinced that relying on gut feeling is too risky. So they go ahead and start collecting everything. So they collect every click that customers do on the website or taps on the mobile app, every page view. And they spend weeks learning how to create dashboards for everything. And as I said before, it gets you overwhelmed in the end to make sense of all of that. And I’m not gonna lie, I’ve seen several startups getting off the ground without collecting data at all. But they always hit a point where gut feeling is not scalable. So most startups say sometimes I don’t need a CDP or a customer data platform should get started with a customer data initiative. And in fact, they’re technically right. So they start tracking events straight into Google Analytics or Mixpanel, or amplitude and completely ignore the fact of having a CDP in between. So those tools are designed for a single end purpose, right? So analytics tools, and these examples that I was giving. Why else customer data platforms are designed to be agnostic to an end purpose. So once you understand that, that’s it helps a lot for you to understand the role of a CDP in between. So everything looks fine for those companies that that connect their websites or mobile apps in to the activator, activation tools or analytics tools. But whenever they need more advanced reporting, or activation, or new activation capabilities, everything starts becoming a mess. For example, if they want to create welcome journey that is triggered by a customer event, or if they want to export the data into an SQL database that is going to feed a Power BI report or Looker or Tableau, then things become really out of control because those tools were not designed to export the data, right, the analytics tools or the activation tools, email marketing or whatever they using. They are not made for that. So in summary, you don’t need a CDP to get started for those that mentioned that But it won’t cost you anything to use one. And it will, it will allow you to scale over time. So I definitely recommend companies that are not using the pitch to get started. And just to be clear, I have no interest in promoting Segment or any other CDP’s. I just do it because I think that it’s really valuable to have one.
Spyros Tsoukalas: Thank you very much for the very detailed answer. I particularly enjoyed that saner phones around the gut feeling is not scalable after a certain point. So given this, these mistakes and stats are facts that you mentioned, like what should early stage startups been doing instead?
Humberto de Oliveira: Ah, absolutely. So I think that there are several things that they could be doing. Apart from, as I mentioned, use a customer data platform. But I’d like to maybe summarise a few of some generous steps that every company could follow, especially early stage startups. So I would start by defining maybe four steps here. Okay, just to keep things things simple. So first, define your two or three critical business goals. I tend to use like four dimensions when I’m consulting with some companies, which are revenue costs, risk and time. So for example, if you want business goal could be increased revenue by 20%, by the end of the quarter, or reduce fixed costs by 10% by the end of the month, or minimise the risk of GDPR or CCPA penalties, and for time, reduce the time that it takes for an new lead to become a customer. So once you start creating those business goals, becomes much easier for you to move into the second step, which is define what are the data points that you need to achieve those objectives. Those could be like, user events write user emitted events, such as site user signed up, or product viewed, or page viewed sometimes, right? And or, but sometimes the data points could be the ratio between visitors and subscribers in a given period, or the percentage of products that were added to the basket, and then were bought within a given period. So these are all kind of the data points that you have to start making sense of, before we can move on to the next part, which is, in some cases, it’s not always that you’re going to need that. But sometimes you may need to define very clearly, what are your business terms. For example, for a SAAS, what exactly defines in active user is, it’s like someone that comes back to the website, every day, every week, someone that refreshes the page, many times what is an active user? For an E-commerce however, maybe you have to think about what defines a top customer? Is it someone that performed the number of purchases within a period of time or someone’s that refer your brand on social media? It really depends. And it’s very important that everyone is aligned on the same page whenever they communicate across those those metrics, using the right business terms. And finally, now you understand your metrics, understanding your goals, understand what is getting tracked or collected in terms of data points, you have to start establishing intuitive hypothesis for improving those metrics, right. And to get there, I’m going to introduce something that is slightly technical, but not too much, which is the difference between leading and lagging indicators. If you don’t know what that is an example of a leading indicator is a product added to the basket for example, or your ecommerce stock factor, these are leading indicators. Leading indicators means that they are going to lead you to understand a lagging indicators, which is an example of ecommerce is a number of purchases, right? So the more you understand what leads to your lie indicators is going to make it easier for you to understand if you’re getting there in a simple way. And those must be correlated. To what extent they are correlated. It depends on the business. Now, the question that you should ask at this final stage is what are my leading indicators? If you say that it’s the number of visitors of your website, you’re probably wrong, because it’s too ambitious, just say that a number of visitors it’s correlated to number of purchases. So how much your leading indicators correlate your lagging indicators important question? And without getting too technical on that again, what is the correlation coefficient, which is how close they are to one another? And the example I gave how much you can you confidently say that a product getting added to your basket leads to a purchase. That’s your quarter like correlation coefficients. And then at the end, what can you do to move your lead indicators, so then it becomes closer and closer to a very convincing way of leading getting to the login ones. So these four steps, as I mentioned before, are iterative. They’re not going to get 100% right from day one. So should just get started. That’s my strong recommendation is here. Just get started with something, and iteratively improve on that. But don’t underestimate the planning phase, it’s very important to dedicate some time to plan. As I said, it’s four steps, they are not exhaustive, but they at least get you on a good head start from what I’ve seen, in my experience.
Spyros Tsoukalas: I’m speechless. So the process is defined is like, simple, stored and actionable. So thank you for structuring this answer in this way. So before we go to our last question, is are there any cases where you think startups shouldn’t be using like, data? Or like the footprint that their customers live?
Humberto de Oliveira: It’s a it’s a good question. I don’t think there is a hard blanket rule for small teams, I think data is generally a good idea. And the more you think mathematically about things, the more you’re gonna avoid that gut feeling that I was talking about before, right. But what I would say, though, is that you should be careful to not let data analytics take too much of your time. So sometimes you get too involved into the planning phase, and don’t execute anything or create too many dashboards or track too many things. Right. So I would say that it’s important for you to strike a balance of dedicating just a little of your time or, or distributed effort of data analytics to your team, to something that makes sense to their domain, right. So we have marketing teams, product teams, customer service technology, so try to distribute the efforts of data analytics, but definitely have a components that makes people think, data driven or data informed. Very important. So then, so the point here is that instead of you spending time configuring a lot of dashboards, just create very simple ones, create maybe some alerts for critical events, or critical data or ratio that is not conforming to your expectation. And for each alert or dashboard that you create, make sure that you have an owner, you have a frequency of verification agreed, for example, how often should we look into this numbers here? Is it daily, hourly, weekly? How is important? How important is it for the owner of the data should be watching that? And frequency of reporting to the wider team or to management, right? So the owner is responsible for watching that metric. But maybe it’s not relevant to be constantly reporting to the team, maybe just once a month is more than enough. So long story short, definitely don’t underestimate the power of data. And I think everyone should use it. But don’t make it too complicated. Don’t boil the ocean and start very small and simple and evolve over that.
Spyros Tsoukalas: Thank you for setting your point of view on that Humberto. So my favourite question now? What tools do you or resources that you love or enjoy using? And you would recommend to our listeners?
Humberto de Oliveira: Yeah that’s a great question. I’m going to suggest a few tools that are related to data analytics, and maybe some more technical tools or project management tools. Because there’s so many expertise around marketing and email marketing tools for from other speakers here that I’m going to leave this for them. But for a customer data platform, I cannot say much about other tools in terms of how great they are. Because I’m really biased towards Segment. I’ve worked for Segment for two years, I think is a great product. I don’t have any stocks just to be completely honest here or anything that connects me to them. But I honestly think that is a great mature product in comparison to what I’ve seen in the competition. Now, for analytics tools, I if you’re very small, and you don’t want to get in too much involved into the into into SQL and you know, programming or anything like that, use something like Amplitude or Mixpanel. I think these are great, great tools and very simple. Very, it’s free to get started from what I’ve used it in other startups. And it can go a long way for free. Now, if I do have to mention something about email marketing, and things like that, I would say depends on how complex your customer journey will be to communicate. But Braze is a great email mail tool, but it also does push notifications, it does journey orchestration, but SendGrid is another one that is owned by Twilio, that might have the best prices. So if you’re looking for something that is a bit cheaper, you may use SendGrid. But it doesn’t have the all the UI features that Braze has. In fact Braze uses SendGrid behind the scenes, in case you don’t know. Now, my last recommendation here when it comes to project management tools. I really like Asana So as soon as a you know, compared to competes with Monday.com, or Jira, I think it’s extremely lightweight solution to for businesses, and it’s super fast to create dashboards and things like that. I use that when I’m consulting with small startups and then when they need something, and then I normally use Asana, I think it’s really, really good. And yeah, but I think those are mostly the main ones that I would say. And if you’re looking, for example, for resources, right, this is not necessarily tools now. But if you’re looking for talent, to hire for your business, I think there’s a great website, it’s it can be a bit expensive, but it’s good for getting some good consultants, it’s Toptal. Toptal is like your website where you can find developers, product managers, and all of that for a competitive price for what the talent is. So I would recommend that one as well.
Spyros Tsoukalas: Humberto, thank you very much for sharing all these with us. I hope you enjoyed this recording and this episode in general as much as I did, and I hope that people will enjoy it even more.
Humberto de Oliveira: As far as it’s been an pleasure to be here and I look forward to meeting all the listeners of the podcast. Thank you so much for invitation.
Spyros Tsoukalas: Thank you very much. Thank you
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