Business Intelligence generated from Big Data is no longer just a concern for large enterprises. Small businesses need to understand and manipulate Big Data to succeed.
Author Frank Moss defines Big Data as the explosion of structured and unstructured data about everyone and everything. The spectacular success of social networks like Facebook and Twitter and the growing machine-to-machine connections have given birth to what is commonly referred to as the Internet of Things, where computers, GPS devices, smartphones, and embedded microprocessors and sensors are generating data every minute of the day. Every time you send a tweet, post a blog comment, use a credit card, or update your social network profile, you leave behind a footprint of digital data, which is not only accessible but can be used to determine consumer behavior.
Big Data can especially be rewarding for entrepreneurs and small business owners who are looking for ways to accelerate growth based on consumer insight. This market intelligence, which has been used by large corporations for decades, is now available to small companies at a fraction of the cost of what it was just a few years ago. Big Data is big business, and learning how to leverage it will give your small business a competitive edge.
Various uses for Big Data in small business
The explosion of Internet services, from apps that monitor the amount of time you spend watching television to how hot your coffee is, has seen a proliferation of unstructured data. Unless you figure out how this data can be put to use, you are not leveraging the full potential of Big Data.
One area where Big Data can prove critical to small business success is in price setting for products and services. The price of a product or a service could differ drastically depending on the product or service and when it's sold. For example, how do you set a price for your product or service during the holiday season? Should you offer deep discounts at the start of the season to capture the deal seekers, while raising the price at the very end of the season to capture the procrastinators, or should you set a standard price that everybody would be pretty comfortable with? These are Big Data decisions that should only be made if you have substantial data from customer behavior trends in your line of business.
Big Data can also be used to identify consumer patterns and help develop strategic marketing plans. Understanding a consumer's direct impact on your business will largely transform your ability to engage with them effectively. This information can be used to identify how people become customers at each stage in the purchasing process and ultimately help you determine which channels have the most influence on sales.
Another use for Big Data is determining whether you should spend more time and resources on acquiring new customers or retaining existing ones. This simple insight can help you realign your marketing efforts and quickly increase your revenue by spending more marketing dollars on the group likely to give you more in returns.
Two real-life examples of Big Data in action
The first example was featured in an Inc. post by Elizabeth Woyke. Revolve Clothing, an online apparel retailer, was faced with the challenge of getting repeat customers. The company's chief marketing officer, Kobie Fuller, determined that the answer was in the retail store's Big Data archives, which dated back to 2003. Using the services of Custora, a data analytics engine, Revolve was able to see certain customer patterns, such as shoppers who made repeat purchases within 90 days proved to be most profitable. Revolve also noticed that 90-day email messages generated 30% more repeat purchases, so the company adjusted its marketing efforts to target this group of customers.
The second example comes from Mark Troester, Global Product Marketing Manager for SAS, about a healthcare consultancy in the United States that uses medical practices data from 10,000 doctors to create a virtual clinical integration model. These independent physicians are measured against 90 care standards to determine if they meet Federal Trade Commission (FTC) guidelines. After analyzing the data, the consulting firm helps the physicians understand how well they meet the guidelines, whether they qualify for enhanced reimbursement, and if they are in a position to negotiate their health plans with the FTC.
What about you?
How is your business or organization using Big Data to improve efficiency and drive sales? Let us know by posting in the discussion.