We all are witnessing how the startup culture is evolving with a massive number of new ventures coming out.
However, not every startup hits the jackpot. Some startups struggle and fail, and one of the significant reasons behind this is not knowing what the market wants.
Simply put, they fail because their product or service is completely out of the market.
Apart from that, at times, the market isn’t that mature; meaning, even if you have a well-developed product, it might not be relevant for the current preferences.
Amid all these successful and failed startups’ scenario, one thing that is entering the space is Data Science.
If you notice, in the last couple of years, data science has become extremely popular among startups. These new ventures are pouring loads of money and hiring data science professionals.
And I am sure, you all already know that it is even called “the sexiest job of the 21st century”.
However, there’s a dilemma of startups — whether to turn to data science or do away?
And in this blog, I am going to address the same. I will try to look at the important aspects of data science for startups and try to put down my perspective on this.
Why Data Science is Booming So Much?
Before I tell you whether a startup needs data science, let me first talk about the demand for data science and this whole shebang.
There are a whole bunch of reason why companies are doubling down on data. But the one that sits on the top is “the amount of data that is being generated every day by companies is just MASSIVE”.
It is believed that more than 2.5 quintillion bytes of data is created every day. And the number is just increasing.
(For your information, there are 18 zeroes in a quintillion.)
But how can a company benefit from data?
Many companies didn’t know what to do with this pile of data. They were unaware of all the possible use cases. But now, they know and are going all out to make the best out of it.
Data helps you measure and know more about your business. Further, you can directly translate that data into knowledge and get benefited with improved decision making and performance.
Let’s take the example of online shopping.
You have an online clothing store named Zzzara (fancy name, right!). Now, every time people shop from your store, you can track not only what they bought, but also what else they checked before and after their purchase.
That’s not all.
You can also track whether they came to you after getting influenced by an ad or promotion or review. Basically, you can track almost everything to know about their intent and preferences.
Once you understand your buyers, you can use advertisements to target them with the content they want to check. And in turn, increase your sales.
The Rise of Data Scientists
And just like any other domain, the demand for skilled professionals for this technology is also touching the skies.
Even though we have figured out what to do with data, the number of professionals to handle this data is significantly less. Therefore, the expertise of data scientists is a hot commodity at present, filing a unique business need.
Moreover, when we say data science, it’s not just one role. Data science consists of disciplines like statistics, data analysis, machine learning, computer programs etc. Meaning, there are a plethora of career opportunities for data science enthusiasts.
Therefore, to hire the best, companies are paying a fortune, making it one of the high-paying jobs in the world.
Do Startups Need Data Science to Succeed?
There’s no solid answer to this question.
It’s just that startups must make the most informed decision regarding this.
If you’re an early-stage startup and don’t have much on the capital front, then I would suggest not to think of data science. Because it is expensive and difficult to retain.
If you decide to hire a data science professional, then you must be ready to pay a lot. It’s not just his/her salary, but there are tools involved that are expensive too. And I don’t think it’s wise enough to invest so much at the beginning.
No doubt, it will deliver results. But what’s the point of such results if you fail to scale your startup.
Don’t forget, money-related issues are also one of the common reasons why startups fail.
BUT, if you are significantly funded or have the capacity to invest, then data science can definitely infuse your business with information and take it to greater heights.
With data, you can nail the personalization aspect.
With the right skills and right set of tools, you can extract data, build pipelines, visualize findings, predict the future, create products based on that, and then test and validate them to improve.
Simply put, it’s all about a data-driven approach. You are not shooting arrows in the dark. You are looking at each and every piece of information in detail to build a product that actually makes sense to the world.
I know this article has gone a little towards the bright side of data science. But I think that’s because of the perks of data science.
Yes, it is expensive and not every company can afford to turn to this tech. But again, one can also not deny that it is a revolutionary technology that can make or break a company.
If you’re a business owner or someone from the startup ecosystem, it’s completely upon you whether you want to invest in it.