Famous article on Forbes by Louis Columbus said that “51% of enterprises intend to invest more in big data”. Visionary leaders know how important information/data will be in the digital age. It is primordial to approach and analyze every customer to then be able to predict what are the next user needs. Predicting what the consumers want before they even know it makes them quite excited and helps you provide an unforgettable service as well as build your brand name. Big Data analytics also contributes significantly to help companies when it comes to improving their business performance.
“Without Big Data, you are blind and deaf and in the middle of a freeway”1– Geoffrey Moore
Key statistics about Big Data that you shouldn’t ignore
- 91 % of marketers believe that successful brands use customer data to decide marketing strategies
- 49 % increase in revenue growth for companies that invested in analytics versus those that did not
- 35 % of marketers say that data has improved their customer engagement through personalization
- Retailers who leverage the full power of big data analytics could increase their operating margins by as much as 60%
- 60% of the professionals asked feel that data is generating revenue within their organizations
- 83% of the professionals say that data analysis makes existing services and products more profitable. Asia is leading the way – where 63% said they are routinely generating value from data. In the US, the figure was 58%, and in Europe, 56%
Impressive statistics about 4 V’s of big data analytics
Volume, variety, velocity & veracity
- 43 trillion gigabytes will be created by 2020, and will increase of 300 times from 2005
- 6 billion people have cell phones. The world population is 7 billion
- More than 4 billion hours of video are watched on Youtube each month
- 400 million Tweets are sent per day by 200+ million monthly active users
- Poor data quality costs the US economy around $3.1 trillion a year
- Big data analytics grows to an annual rate of 40% in 2020
Big data analytics case studies
As we all know it, Walmart is one of the best retailers in the world. With more than 245 million customers visiting 10,900 stores and its employee number that is actually more than some of the retailer’s customer numbers.
Walmart uses data which helps them to provide product recommendations to the users based on which products were bought before or which products were bought together. The chief information officer, Linda Dillman, examined sales data after Hurricane Charley to determine what would be needed following the forecasted Hurricane Frances. As well as the predictable increase in sales of flashlights and emergency equipment, the period saw an unexpected increase in demand for beer and strawberry pop-tarts. This data was used to inform stocking decisions, and led to strong sales. Strawberry pop-tarts sales increased by 7 times before a hurricane.
Walmart collected valuable information from each individual consumer, what was bought, where they live and what they are interested in to then predict the customer’s behavior.
Apple’s products make people happy, it’s a fact. Everyone is curious about their secrets, they want to know what are the processes behind all those excellent product designs. It is inevitable that they use Big Data analytics to analyse their user’s behaviors. Apple is interested in user experience, and they always think about how they can produce tech products that would provide the most logic and comfortable feeling to their users. Big Data analytics helps Apple with the “how, when & why” that they need to build products and determine what new features should be added.
When we are shopping online on eBay or on Amazon, you can almost always see some suggested products. For example, when I want to buy a dress, during the time i am purchasing it, I will get suggestions to buy a handbag, a scarf, some jewelry or even a pair of shoes that will help me be more satisfied of the outfit. It’s a sort of inspiration for me and who knows, i might buy more products from them.
In this case, they studied the customer’s behavior by researching data and by analyzing hobbies and habits of customers when they shopped at their stores in previous times. This enables to give a rational suggestion to a specific person, based on past attitudes.
Linkedin has more than 400 million members in over 200 countries and territories. There are 3 million company pages, 2 new members join Linkedin per second and there are more than 100 million unique monthly visitors. The total revenue advanced by 35% year-on-year to $861 M in the Q1 of 2016 Q1.
Big Data analytics is a key tool that helps Linkedin create great features on its platform. Let’s see how wise it is! Linkedin suggests us amazing points: people you may know, skill endorsements, jobs you may be interested in, news feed updates, who has viewed my linkedin profile, etc.
These features increase the value of the platform for the users, increasing therefore their satisfaction and interest. It has helped Linkedin build its success.
Interesting predictions about the future of Big Data by Bernard Marr
- More companies will appoint a chief data officer
- In addition, real-time streaming insights into data will be the hallmarks of data winners
- Big data analytics will face huge challenges around privacy
- “Autonomous agents and things” will continue to be a huge trend
- The data-as-a-service business model is on the horizon
- Algorithm markets will also emerge
- Cognitive technology will be the new buzzword
- “Fast data” and “actionable data” will replace big data
- Businesses using data will see $430 billion in productivity benefits over their competition not using data by 2020