Data science solutions can work miracles for businesses. Be it using big data to record every strain of data or applying data analytics techniques to drive lucrative campaigns, data science has had a transformational impact on businesses. Small businesses, primarily, have utilized the power of big data and data analytics for the growth of their business. Let’s look at a hypothesis to understand how big data and data analytics help small businesses race ahead!

A Hypothesis

Let’s consider a hypothesis where the world has only one country with twenty residents. And there is one mega-store that caters to their essential needs, occasional, and others. In such a set-up, the mega-store will have the ultimate advantage because of two things;

• Its monopoly
• All the data collected from multiple customer purchases

Now, if a small business wants to enter, it will face strong resistance from the mega-store. To tackle the resistance, it carries out intensive data research and analytics. It further categorizes the data in multiple sections such as;

• Customer Preferences Graph
• Perceptual Map to find the right kind of product
• SWOT Analysis
• Growth-Share Matrix

After reviewing the analysis results, it realizes that the mega-store does not sell medium segment products. It oscillates between premium or low scale. So, it decides to export or manufacture products for the medium segment, and within nine months, climbs up to be a competitor of the mega-store.

There is no ultimate power-shift, but it keeps oscillating between the two, considering the customers’ needs and preferences.

Not realizing their advantage due to the abundant data they’ve collected over the years, the mega-store runs around frantically to trump the new store.

Later, it digs through all the data and creates an advertising strategy that invites 2x seasonal customer traffic. Both the stores then begin marketing their products and introduce new services to one-up each other.

What do we understand from the case?

The hypothesis consists of various features of small businesses using big data that hold true in today’s time. Let’s look at two concepts that we covered in the case;

Big Data – The Saviour

It is a collection of massive data in a given period and tends to grow exponentially over time. Traditional data aren’t adept at processing or storing such data.

Real-life examples of such data are; Social media data in 24-hours, Stock market data in 6 hours, etc.

It has three parts;

• Structured Data: When you begin storing, accessing, and processing data in a fixed structure, it is known as structured data. Example: Customer Order data at McDonald’s.
• Unstructured Data: When you cannot figure out the structure of data – how it is stored, accessed, or processed – is known as unstructured data. Example: Google search results
• Semi-Structured Data: It is a little bit of both. It has hints of structured data along with unstructured data.
  

From our hypothesis, all the data that the mega-store could collect, over the years, is known as Big data. Also, data collected by the new-store from multiple sources is called Big data.

Data Analysis – The Campaign Planner

Data analysis is the process of cleaning, sorting, and modeling the data in a way that allows quick decision-making. More often than not, our decisions are a result of assessing cumulative actions. A switch from tea to coffee also needs concrete data and analysis. There are a few types of data analysis, but the crux of the process lies in its motive. We conduct data analysis to make better and informed decisions.

From our case, it began with the new store crunching numbers to bring in a medium segment for the customers. Later, the mega-store also began analyzing their data and came up with seasonal deals for its customers.

Using Big Data and Data Analytics To Your Advantage!

In our hypothesis, we saw how the new store was able to harness the power of big data and data analytics to break the mega-store’s monopoly. It is safe to assume that small businesses or start-ups don’t have to fear the entry barrier set in by various stores in today’s data-smart arena. They possess the power to defeat the barrier by leveraging big data and data analytics to their advantage. Here is how they can use it;

Market research

Before entering the market, your first step is to research the market. Find out your close competitors and draw data from sources about the product, value addition, and other necessary components. Once you have all the data, you can begin crunching numbers and draw concrete conclusions that’ll make your entry easier.

Market research platforms like Pew Research Center and Living Facts are the perfect place to gather information about your competitor’s CRM, products, and other details.

Market Segment and Customer Preferences

Big data and data analytics gives you an in-depth view of the market and your niches. After you carry out a thorough analysis, you’ll be able to figure out the right segment for your product. And this will further help you to create a concrete marketing strategy for your product.

Given that exponentially changing consumer preferences, carrying out a constant data analysis, and refreshing the numbers is of utmost importance. You don’t want to lose out on customers as megastore did in our hypothesis.

Google Analytics and Kissmetrics are the ultimate tools to help you with market segmentation, conversion funnels, A/B testing, etc., that can help you gain a strategic advantage.

Roaring Online Presence

Every business understands the role of social media and other online platforms in increasing its sales numbers. Your niches are waiting for you to reach out to them on these platforms and give them something different.

In our hypothesis, the mega-store carried out a strong marketing campaign after crunching the numbers from their big data. After analyzing the data, they came up with seasonal deals for their customers. This way, they pushed more products every season, nudged the customers along the conversion funnel, and made 2x profits.

In real-life too, there is an invisible step in the conversion funnel – Validation. Your customers need to validate your offer before they plunge into buying it. And your social presence only makes it easier for them to do so, thereby pushing them towards your product.

Data is an indispensable part of a business cycle. Just as your customers need information about the products and services, your business needs information about your competitors and customers before deciding. Big data allows you to make an informed, data-driven, and an accurate decision due to abundant data points and analysis.

As a small business or a start-up, you might think that data analysis is not your cup-of-tea, but its accuracy can help you transform your business into a lucrative space within a course of time. But it is also tricky to store such massive data and carry out its analysis. So, data science companies can help you with this and guide you through the decision-making process.