Ever thought about what would have been our world without data science? Many and many things would have been different. Understanding customers has been only possible in person; experience would have been the only critical factor to take new risks without knowing or predicting the ultimate outcomes.
Thanks to AI and machine learning, they stand today: tracking and analyzing data can never be this easy without them. With a few clicks, one can generate very accurate data using various filters to differentiate the odds.
But the small businesses are always in the spotlight, from being the best in the locals to opening their branch in the big cities and continuing their legacy for which they are best known. Without the right set of data, they also suffer, bear a huge loss and even diminish.
Without the right team and tools, sustaining in the highly competitive business world is highly sturdy. If you own a small business, you have to become more cautious and think about leveraging data science into your small business and scale it.
Having said that, here are five expert tips to power up data science use in your small business. Let’s dive in.
5 (Expert) Tips To Power-up Your Data Science Uses In Your Small Business
Every business has its strategies, no matter how big or small they are: and that makes them stand unique in the market. With effective branding, advertisement, and customer experience, along with the quality of products they deliver, they establish their position in the market. That’s how one brand differs from the other.
The Data Science Strategies That You Need To Scale-up Your Small Business Are:
Hire A Data Scientist With 2 – 3 Years Of Experience (In Your Relevant Industry)
When you are a business, many employees work under you. Treat them so well that you let your employees become the voice of your brand to attract new and existing customers. Let’s say you run a SaaS startup; hire a data scientist who has a good 2-3 years of experience as a data scientist and has already been working in the SaaS industry.
Then he always has a good understanding of data that your companies require; just let him know your objectives and goals, and he can help you in better ways. He can find and analyze new trends, get the customers’ preferences, and do many things. However, hiring can be costly when you have the best professional in your team. But if you feel you don’t have that much budget, upskill one of your employees, or work with a consultant who can guide you in the right direction.
Using Right Set Of Data To Make Better Decisions
The right set of data matters a lot if you want your data to be accurate. And this dataset shall be packed with concrete evidence and statistics that you need for your business. For this purpose, data wrangling is necessary to differentiate the odd ones.
Therefore the best ways to look into data are:
- Collecting survey reports to identify products, services, and features.
- Conducting user surveys to find out how well they relate to your product.
- When launching new products to understand how a product might perform in the market
- Determining business threats and new opportunities
Right Tools And Softwares That Makes Your Work Super-Easy
Gathering data and analyzing them is a humongous task. It can kill all your productivity manually and even give you a headache when your work is not over on time. And when you do manually, there are high chances your results won’t come accurate, and you might miss a slice of data for the same reason.
Python and its libraries are an excellent tool for data science that can do a lot of work in minimum time. But having one data visualization tool either from Tableau or Power BI will help you understand unstructured data and make complex decisions easy-going.
Thus, you master MYSQL, Excel, Python, R, Tableau, Microsoft Azure, Apache Spark, Big Data, and Hadoop to get most of your work done.
You’ll have many existing customers speaking about your business who love what you sell and come back to you for their next purchase. But what about new customers, how can you target them better, what they like most, and so many questions.
From identifying where most of your customers come from, how they interact with your products, how your products can give a permanent solution to one of the problems. And best customer service wins you many new customers through word of mouth.
The best way to get insight is by running ads for local and nearby places and diving into a google analytics dashboard that gives you a complete understanding of how your customers interact with the ads they see. Their location, area of interest, and much more. And you can get it from the marketing team, combine it with your data science, and produce a robust report.
Discover New Trends And Opportunities To Scale-up Your Business
To be at the top of the business, you need to follow the ongoing trend and look for the opportunities that your competitors lag. When you fill those gaps, you build trust in your customers’ minds.
As a data scientist, your primary work is to do research, come up with concrete ideas, and plan effectively. Suppose you want to sustain and be at the top of the business. When you do thorough research using advanced tools, you find better opportunities. Try them out to discover how they work for your company (necessarily a dry run at least) to collect your customers’ feedback.
If it works, then great. If not, you can look for even better ideas. business is all about taking risks, but calculated ones (so it won’t affect you much.)
Taking new and calculated risks is a new approach to grow your business fast. But when you don’t research and invest, you face a significant loss, and it’s tough to recover. And if you run a small business, it’s not like your business can never go big.
You can make it big, but the right strategies, mindset, and team will help you achieve the same. This blog taught about five best practices to power up your data science use in your small business. Let’s know your thoughts and how you would implement data science in your small business, and which one you find most helpful.