Data mining is: 1) The practice of examining large databases to generate new information and 2) the process of analyzing data from different perspectives to make it insightful and useful.
Data mining is used by companies to increase revenue, decrease costs, identify customers, provide better customer service, listen to what others are saying and do competitive intelligence. And that’s just some of the ways.
Here’s are 20 companies that do data mining and prove it makes their business better.
- AMAZON: With $5 off, for those who use the Amazon Price Check Mobile App – to scan the products in store, take a picture of the product or perform a text search to find the lowest prices, the app also prompts the customers to submit the in-store price. Amazon is collecting intelligence and valuable pricing information from its competitors.
- ARBY’S: The fast food company uses data mining to help them determine the best targets for their advertisements. They can see which advertisements are most effective, while seeing the channels that are most receptive to each ad pitch. This allows them to ensure every advertisement utilizes the appropriate channel to increase the number of leads from their marketing.
- CAPITAL ONE: Data mining and big data management to help them ensure the success of all customer offerings. By analyzing the demographic data and spending habits of customers, they’re able to determine the most optimal times to present various offers to clients, thus increasing the conversion rates of their offers and gaining more leads from their marketing budget.
- DELTA: Large airlines like Delta, monitors tweets to find out how their customers feel about delays, upgrades and in-flight entertainment. When a customer tweets negatively about his lost baggage, the airline forwards to their support team. The support team sends a representative to the passengers destination presenting him a free first class upgrade ticket on his return along with the information about the tracked baggage promising to deliver it as soon as he or she steps out of the plane.
- DUETTO: Known online for their “hotel optimization,” Duetto makes it easier for companies to personalize data to individuals searching online for hotels. Duetto makes it easy for hotels to personalize their prices by taking data such as how much you typically spend at the bar or casino to incentivize you with a lower price for your room. Therefore the hotel can give you a better price, knowing you’ll spend money on other services. The hotel can give you a better price, knowing you’ll spend money on other services.
- EXPRESS SCRIPTS: Which processes pharmaceutical claims, realized that those who most need to take their medications were also those most likely to forget to take their medications. So they created a new product: Beeping medicine caps and automated phone calls reminding patients it’s time to take the next dose.
- FREE PEOPLE: The more bohemian segment of Urban Outfitters, uses millions of customer records (reviewed by an in house analytics team) to shape the next season’s offerings. Information like what sold, what didn’t, what was returned and more fuels the brand’s product recommendations, the look of its website and what kinds of promotions customers see to improve Free People’s bottom line.
- GOOGLE AND CENTER FOR DISEASE CONTROL (CDC): Google proposed a different approach. Using historical data from the CDC, Google compared search term queries against geographical areas that were known to have had flu outbreaks. Google found spikes in certain search terms where flu outbreaks occurred and identified forty-five terms that were strongly correlated with the outbreak of flu. Google then started tracking the use of those terms and is now able to accurately predict when a flu outbreak is occurring in real time. Using this data, the CDC can act immediately.
- KOHL’S: Customers are more likely to respond to an offer when it’s at the moment of purchase. That’s why Kohl’s does real-time, personalized offers. Shoppers can opt in for offers via their smartphones. So if a shopper lingers in the shoe department, for example, they can receive a coupon on the shoes they looked at online but never bought,
- KREDITECH: European company, uses more than 8,000 sources including social media, to create a unique credit score for consumers, which is then sells to banks and other lenders. And they have discovered some surprising correlations between social media behaviors and financial stability. For example, if your Facebook friends use all capital letters, your score is docked.
- MACY’S: Through sentiment analysis of big data, Macy’s finds out that people who are sharing tweets about “Jackets” are also making use of the terms “Michael Kors” and “Louis Vuitton” frequently. This information helps the retailer to identify what brands of jackets should be offered discounts in their future advertising campaigns to attract customers.
- MCDONALD’S: With more than 34K local restaurants serving 69 million customers across 118 countries , 62 million daily customer traffic, selling 75 burgers every second, $27 billion annual revenue- McDonald’s is using big data analytics to gain lot more insight to improve operations at its various stores and enhance customer experience. McDonald’s analytics system analyse data about various factors such as wait times, information on the menu, the size of the orders, ordering patterns of the customers.
- NETFLIX: To create data models and find what makes show or movie popular among consumers, according to the insights they gained from their data, House of Cards was the ultimate entertainment experience. They went all out, winning a bidding war with other companies over the rights and immediately scheduled two seasons of content before showing a thing. It was a huge success, and the best part is they almost knew it would be.
- NORDSTROM: With 225 retail outlets, Nordstrom generates petabytes of data from its 4.5 million Pinterest followers, 300,000 Twitter followers and 2 million likes on Facebook. Their analytics system monitors customer behaviour by tracking – How many people enter the store, which section they walk in, how long they stay at the store and for how long they shop in a particular section. This helps Nordstrom decide what products should be promoted to which customers when and through what advertising channel.
- PANDORA: With 72 million users and the data for approximately 200 million users’ listening habits, Pandora is a name to reckon with in the music industry for providing music recommendations that people really love. Apart from the data like gender, age, zip code that users provide at sign up, Pandora tracks all the songs that a particular user likes and dislikes, from which location they listen, from which devices they listen and more – to provide customers with curated music catalogue based on interests and demographics.
- PREDPOL: The Los Angeles and Santa Cruz police departments, a team of educators and a company called PredPol have taken an algorithm used to predict earthquakes, tweaked it and started feeding it crime data. The software can predict where crimes are likely to occur down to 500 square feet. In LA, there’s been a 33% reduction in burglaries and 21% reduction in violent crimes in areas where the software is being used.
- STARBUCKS: As the leading coffeehouse company in the world, Starbucks manages to open new stores in very close proximity with their other stores, while still guaranteeing a high success rate. Normally, when expanding a company, it’s needlessly risky to open a new location just a block from another location.
- T-MOBILE: Data mining helps reduce customer turnover rate. By analyzing big data, T-Mobile can determine the core causes for turnover, allowing them to implement effective solutions that will keep more clients on board. As a telecom company, they accrue boundless quantities of data every year, and without big data management, the ability to analyze the data would be greatly inhibited.
- THOMSON REUTERS: Financial experts can gain competitive advantage by analysing the twitter sentiment data by tracking specific tweets from various companies and people. This helps financial professionals get an overview on the number of positive and negative sentiments related to any given company. Sentiment analysis along with other advanced big data analytics solution helps the financial professionals spot the financial market and any events impacting the company as they happen.
- WALMART: The mega-retailer’s latest search engine for Walmart.com includes semantic data. Polaris, a platform that was designed in-house, relies on text analysis, machine learning and even synonym mining to produce relevant search results. Wal-Mart says adding semantic search has improved online shoppers completing a purchase by 10% to 15%. “In Wal-Mart terms, that is billions of dollars,” Laney said.
Do these companies prove how data mining could make your business better? Could your company benefit from data mining?
