As it is known big data initiatives have become a standard part of doing business but that doesn’t mean big data is easy. It is generally acknowledged that startup founders are struggling to get meaningful ROI from their data analytics programs. After all, startups need to make the right decisions: create the right features, target the right buyers, and recruit the right staff so analyzing all this data can become a bit overwhelming at times.
Making informed choices needs accurate data, the challenge is that startups barely have adequate data, let alone good data and the ones that have a bigger pool of users do not know how to organize the information they are receiving all the time. In this article, we will discuss a few challenges that startups face when it comes to big data and suggestions on how to solve them.
Also, each startup is different, so the volume of data that appears challenging for a small early stage startup might not seem that way for a scaleup. But as we all know, every startup might have issues with analyzing data at some point whether we are talking about early stage or not because as your company grows so does your data that needs to be managed. Responsibilities regarding the management of data because it is unstructured doesn’t give insights or isn’t time efficient can appear at every stage of a startup.
Why do we need to understand data as startup founders?
Whether you’re looking to develop the next delivery application, electric vehicle, or project management software, data shows you that there’s an issue that needs to be addressed before you start designing the idea.
When you have a product, making smart choices is the secret to the success of a startup. Restricted resources mean that you can only create a limited number of functions for your product. If you’re unsuccessful, you won’t survive long. Time and resources are minimal, and they can’t be lost. You need to easily define your core customers, discover others, and monetize them. The more captured, stored, and analyzed data, the better the decisions, and the less time and resources are spent.
Data is about growing the chances of the startup to succeed in the future and not fail, it is about setting the right direction, the right target, and the right metrics.
One of the challenges startups face is the lack of data that can be present in different stages and can create some confusion when it comes to what you should do next.
As an early stage startup, you analyzed the market, discussed with prospective customers and validated that there was a challenge for your startup to tackle. Now you want to use this chance to shape an early stage startup. You’re a tiny team: maybe just co-founders, maybe a few workers, if you’ve earned any seed capital. You may have users, maybe even some paying customers and you’re getting some early traction, but something doesn’t seem right. You don’t have the whole information that you need.
Or you can already have the product but you want to expand to different markets in other countries and you analyzed the market as well, now you have a big team, you had a few discussions with potential users but then again some information is missing and questions start to appear.
● What features should be developed next?
● What users are our best use cases?
● What am I missing from this analysis?
● How can I gain more information about this topic?
● Why are the users doing that?
In this part, you can discuss these data issues with mentors or investors that you might have. Search online statistics, check what has worked before and what hasn’t. But the most important thing that you can do is ask your users what the issues are. Startups such as Airbnb, Stripe, or Fitbit are just a few examples of how important it is to know what your data is talking about and what your user needs. To produce great products, you need to have a clear understanding of your consumers and their use cases. And if you have encountered the issue yourself, you cannot presume that your experience fits that of your future customers. Everything needs to be validated whether it is just a new feature for the application or the product itself.
For a scaleup, the challenges might vary since the data has grown significantly but they can appear there. The data might be unstructured, might not reside in a database, presumptions can still be made. The same solutions apply to them as well.
Another challenge for startups is the limited resources they might have for data management and infrastructure. You may not have enough resources or if you have enough resources you do not know how to organize them because at the same time you know that there are features that need to be created, debt to be repaid, and other bugs to fix,
As a result, data processing and technology frequently comes as a hard thing to do and there are many tools that you know you can use to gather it, you just didn’t take enough time to understand which one fits best for this type of situation.
Moreover, if you are an early stage startup you analyzing data might sometimes be the last thing on your priority list, leaving it at the end to be done. But analyzing the data you have from an early stage will help you more when you upscale the product and when you need to confront some issues that can’t be canceled.
When you come across this challenge you can start documenting what you are implementing and if you are already doing that you can start documenting better, maybe using another tool that gives you more insight if you see that the one you are already using is not helping you. Another thing you can do is to take into consideration the use cases that you have and come to them for validation and some conclusions that you can’t reach on your own.
Other challenges that startups might go through include:
– Recruiting and retaining big data talent, people who know how to analyze the data that you have and use the specific tools.
– Getting insights in a short time doesn’t happen every time due to different unplanned aspects even though you might need the data in a few days not weeks or even months.
– Monetizing the insight you get from the data, not a lot of startups understand all the time how to monetize the data.
Luckily enough there are a lot of tools that you can use as a startup, some of them are free and some of them request a payment. It is up to you to decide which one to use and how you want to analyze the data that you have. But a thing that is important to remember is that the data you have can help your startup grow and achieve more. Data that is not used well can give you a lot of problems that you do not want to have. That is why when you encounter challenges such as the ones above talk to your users, talk to other business partners, and figure out what to do next to have the best outcome possible.