How Data Science Can Help You Grow Your Business Faster

By Kimberly Fries | Apr 12, 2018
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Big data and data science are terms no longer restricted to just the techies’ vocabularies. In this ever-increasing digital world, these technological advances are critical for businesses to succeed and grow. Big data is estimated to generate a 60% increase in retailers’ operating margins on a global scale. European government administrators could save over $149 billion in operational efficiency improvements by leveraging big data.

The potential transformational use cases of this technology extend into multiple industries. If you are a business owner of any sized company, knowing how to use data science will keep you competitive and growing.

What is data science?

Data is nothing more than information that is “out there,” all over the web. And the scientific use of that data means that it is gathered in huge amounts and then churned and categorized, based on the specific information that a user wants.

Data scientists are the people who gather huge “lakes” of information and then use their expertise and algorithms they have developed to extract specific information that a user wants.

“Users of big data have typically been large enterprises who can afford to hire data scientists to churn the information,” said Kevin Murcko, CEO of CoinMetro. “But now, thanks to democratization of tech and the rise of blockchain, there are tools that can be used by small and medium-sized companies to both gather big data and to use it to make good business decisions – decisions that will help them be competitive and grow.”

Here’s an example to illustrate the point further. Suppose you were a bank that wants to develop loan products that will be really attractive to borrowers– products that will beat out your competition. You will use data science to gather information about all of the types of loans that consumers have sought over the past year, what demographic groups have sought what types of loans, what times of the year are specific loans sought, and what have been the most popular types of loan features. You can use all of this information to develop loan products and market them to specific groups, thus growing the lending sector of your enterprise.

How big data fuels business growth

Today, up to 65% of business owners already admit that leveraging big data makes their organizations more competitive. Spending on big data is projected to reach $114 billion in 2018. Here’s the exact big data value that companies are going after:

1. Improved business decision making. You can measure and track the response of consumers to products/services you currently offer and those that you are considering in the future. Consumer patterns of behavior can be analyzed using real facts, not gut feelings.

2. Analyzing market trends. As stated above, you can capture information about consumption trends and modify products/services accordingly.

3. Save yourself from needless spending. If big data shows that products or services you are considering will not be popular, you can scrap development plans and, instead, use trends to refine and improve what you currently offer. Or, you can meet those trends by developing what you know will be “hot.”

4. You can test ideas. If you have ideas for new products/services, you can “test” them before you move forward on production. Big data and AI will tell you if they will be in demand in the future, by analyzing current trends and predicting future ones.

5. You can more carefully define your target market. Customer data is important. There may be entire demographics out there whose consumption behaviors and patterns are a “fit” for the products/services you offer. And yet you have not targeted or marketed to them. For example, did you know that Generation Z, that which follow millennials, is even more focused on company sustainability and diversity? If you can show that your products/services or activities foster environmental responsibility and/or that you promote diversity in your business, there is a new target market out there that you can capitalize on.

Learning and leveraging big data

If you have not begun to use big data, and accompanying artificial intelligence (AI) and machine learning (ML), there is much to learn about the tools and processes you can use, as a small to medium-sized business owner. Consider attending a workshop or conference on data science to get a better understanding of how you can use this new technology to grow.

But not all events are created equally, so make sure to define your specific needs and that the conference you’re attending is actionable and meets those exact needs. For instance, the AI and Data Science for Executives workshop is specifically tailored for busy business executives, is facilitated by an expert and participation is limited to 12 attendants, so every participant gets personal attention.

Data science is the most current “tool” for businesses that want to meet consumer demand. The beauty of it is that it is not based on what we may “feel” about consumers and what they want or need. It is based upon actual patterns of behaviors and trends that the facts reveal. These facts are what should drive all business decisions, because they save money and time, but more importantly, allow a business to reach new and existing audiences with products or services they will actually purchase.

Related: Data Analytics Will be the DNA of New Economy

Big data and data science are terms no longer restricted to just the techies’ vocabularies. In this ever-increasing digital world, these technological advances are critical for businesses to succeed and grow. Big data is estimated to generate a 60% increase in retailers’ operating margins on a global scale. European government administrators could save over $149 billion in operational efficiency improvements by leveraging big data.

The potential transformational use cases of this technology extend into multiple industries. If you are a business owner of any sized company, knowing how to use data science will keep you competitive and growing.

What is data science?

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