SHARLENE is a hairdresser with a growing customer base, which she mainly takes by appointment, each of which is recorded on her computer. Sharlene notices that some of her clients always come to see her on the Friday or Saturday evening before big weekend parties. She starts taking note of upcoming party dates and comparing them against her clients' appointments. Sharlene finds that her theory is correct and realises that she can proactively manage her customer appointments using this information.
Having her customers spend five disgruntled hours in her salon on some Fridays and Saturdays while slowly making their way to their desired hairstyles is now a thing of the past. Instead she now calls or sends text messages inviting them to book their appointments at a mutually convenient time. In particular, she knows those clients whose preferred styles will last longer so she can schedule them for the Thursdays ahead of big parties. She also knows the clients who don't seem to be party-goers, so when party weekends are coming up she schedules them for earlier in the week. In doing so, they avoid competing for her services with the party-goers on the busier Thursdays, Fridays and Saturdays.
Sharlene is using "big data" (a combination of her internal data about appointment bookings and external data about upcoming events) that she has collected about her clients and about external events to:
* Manage her business more effectively - she can schedule her clients for optimum efficiency;
* Increase her revenue opportunities - she can take on more business;
* And improve customer satisfaction - no more five-hour salon visits for her clients.
What is 'big data'?
The terms "big data", "data mining" and "business intelligence" have been buzz words in the business world for the last few years. If you're a business owner, you may have heard any or all of these terms and wondered what they could mean for your business, if anything at all. These terms tend to be used interchangeably, but they're not the same thing. For today, we will focus only on the concept of big data.
Big data is a popular term used to describe the exponential growth and availability of data. It is usually defined using three 'V's': volume, velocity and variety. This simply means that there's a lot of data (volume), moving in and out of information systems at speed (velocity) and that this data comes in different formats and from different sources (variety).
You can understand why it's called "big" when you consider the assertion that data is growing so fast that 90 per cent of the data in the world today was created in the last two years. Before we dismiss this claim as totally ridiculous, let's think about the 350 million photos that are uploaded to Facebook every day, the two million Google searches requested every minute and the over two billion people using the internet, leaving data trails everywhere. Words that, before now, were limited to professions that dealt in really large numbers are starting to enter mainstream language in order to describe the sheer size of the world's data; words like "quintillion" (1 followed by eighteen zeroes) and "zettabyte" (1021 bytes).
Your own business is contributing to this data explosion daily. Each time Sharlene books a client's appointment or sends a text message, she is recording data. If she is capturing their email addresses, she can entice them back to her salon with special email offers and promotions. Of course, her email campaign to her clients just joined the other two hundred million emails sent every minute - more data being generated. After a while, Sharlene decides to start capturing each customer's date of birth and address by inviting them to sign up for a loyalty programme; she is adding more data to what already exists for her business.
When Sharlene decides to expand her business to include her own line of hair care products, she creates a website so that she can sell them online. Now she is capturing data about each person who visits her business through that medium. She knows which country they live in, the language that they speak, the pages on her site that they visit, and whether they use an iPad, a desktop computer or a smartphone to access the site. This basic information informs the marketing and technology strategies for her site and helps her to know where to concentrate her company's resources.
Not just for the big boys
A few years ago, an irate father entered a Target store in Minneapolis demanding to know why the company was sending coupons for maternity and baby products to his sixteen-year-old daughter; were they encouraging her to get pregnant? The store manager apologised profusely and promised to look into the matter. A few days later when the manager called the father to apologise again, the father contritely admitted to the manager that it was he who should apologise, as his daughter was in fact pregnant. How did Target know that the girl was pregnant before her father did?
Target used "big data", the massive amounts of data that it had on customer buying patterns and medical information to come up with a "pregnancy predictor". They figured out that if a woman purchases a certain combination of about twenty-five products, they are able to predict with fair accuracy that the woman is pregnant and what trimester she is in. They then use this data to send coupons appropriate for her stage of pregnancy to the expectant mother, enticing her to fulfil her maternity and baby-shopping needs at Target. The company does this because they know that capturing a customer during this stage of life could capture them for life.
Target is a huge retailer with vast resources and a predictive analytics department that does nothing but analyse data. However, the fact is that no matter how large or small your business, you are sitting on an invaluable asset called data. There are hidden treasures there that could save your business money or spark off a new business idea. Big data is not just for the big boys.
Big data is also not a fad; it is here to stay. As long as you own a business or run any type of organisation, you cannot afford to ignore this concept. It will take commitment and some level of technology investment, but commit you must. Get the jump on your competitors; start embracing your big data now.
Kristine Bolt is an industrial engineer. You can cantact her via her twitter handle @kristinebolt.