Once upon a time, you went to the same neighbourhood bakery every time you needed bread. Even before you placed your order, the shopkeeper already had a loaf bagged and ready. As you paid, she would ask what was new with your family. She might remind you to order a cake soon so it would be ready in time for your daughter’s birthday. You appreciated the personalized service and wouldn’t think of shopping at any other bakery.
Now you buy bread at the supermarket, a big box retailer, or even online. You don’t chat with the owner, who in turn provides excellent personalized service because she knows you so well. But with the rise of big data, this sort of customer relationship is returning. While the concept remains a big buzzword for many, smart companies are investing in big data so they can provide better services for customers.
Here are five ways companies are using big data to treat customers more like individuals — and build better long-term relationships so those customers happily buy more and more.
1. Predict exactly what customers want before they ask for it
Remember when that shopkeeper had your loaf of bread all wrapped up and ready to go before you even told her that’s what you wanted? Providing that same service for online shoppers based on their past behavior is exactly how companies are using big data to increase customer satisfaction — and increase purchases.
Companies gather a ton of data on customers, not only what they’ve purchased but also what websites they visit, where they live, when they’ve contacted customer service, and if they interact with their brand on social media. It’s an overwhelming amount of seemingly unrelated data (that’s why it’s called big data), but companies that can properly mine this to offer a more personalized touch. To properly predict the future, companies must promote the right products to the right customers on the right channel.
Amazon long ago mastered the recommendation of books, toys, or kitchen utensils that their customers might be interested in. Other companies have followed suit, such as recommending music on Spotify, movies on Netflix, or Pins on Pinterest.
2. Get customers excited about their own data
“Show me the data!” just might be the new “Show me the money!”
With the rise of wearable tech like Nike+ FuelBand, FitBit and Jawbone’s UP, customers have access to more data about themselves than ever before. The food diary platform MyFitnessPal gives people not only a rundown of how many calories they’ve consumed each day but also breaks down protein, fat, and carbs. Sites like Mint.com and LearnVest allow consumers to review their spending by category and see where their money went in a given week, month or year.
Of course, just giving customers tons of data about themselves is not enough. Companies need to sift through all of the data and extract the most relevant info as an easily digestible experience for customers. But if done right, data that makes a difference for customers’ daily lives — whether it pertains to their health and fitness or to their money — can make a difference on a company’s return on investment.
By providing customers data that’s meaningful to them, these companies are using big data to develop superfans. Once they get hooked on their own personal data, they’re more likely to continue logging in or using the product. And if it all goes according to the master plan, they will have become brand loyalists along the way. The man who loves his Fuel band will perhaps buy more Nike athletic gear. The woman who loves how UP has improved her sleep may invest in another Jawbone product.
3. Improve customer service interactions
For many companies, leveraging big data is the hot ticket to more effective marketing and product development. But those who are using data to improve their customer service are taking it one step further. When a customer reaches out, the representative can more quickly and efficiently solve the problem if they have the right data in front of them. They won’t need to ask as many questions of the customer because they already know the answers.
Using data to improve customer relationships is especially important when customers have more channels than ever to connect with brands. Whether it’s a social media manager on the other end of an angry tweet or a representative answering a phone call, those companies who equip their employees with tools that provide in-depth customer data stand apart because they provide great service, which only improves with each interaction. Southwest Airlines, for example, is using speech analytics toextract data-rich info from live-recorded interactions between customers and personnel to get a better understanding of their customers.
And while customers may be aware that companies gather data on them, there’s a line between being creepy about it and using data to help the customer. Companies must ensure their customer service not only has the right data but also knows how to communicate (or not communicate) the knowledge of that data to customers.
4. Identify customer pain points and solve them
Most companies know what some of their customers’ pain points are (if they don’t, they aren’t paying attention to their customers.) Those who are digging deep into the data to solve those difficulties are improving their customers’ experience.
Take Delta. All airlines know a top concern for passengers is lost baggage, particularly when they are on a flight that’s delayed and missed connections involved. Delta looked further into their data and created a solution that would remove the uncertainty of where a passenger’s bag might be.
Customers can now snap a photo of their baggage tag using the “Track My Bag” feature on the Delta app and then keep tabs on their luggage as it makes its way to the final destination. Even if a bag doesn’t make it on the intended flight, passengers save time tracking it down. Finding a new way to put big data to use for the benefit of their passengers put Delta out front in a competitive market.
5. Reduce health care costs and improve treatment
In the health care industry, big data is being put to work to improve the quality of patient treatment — and save lives. Health care providers in Singapore are beginning to gather big data insights from analytics platforms to transform how they manage chronic diseases.
Take diabetes, a condition that can lead to extended hospital stays, which is both costly and puts strain on medical infrastructure. But when Singapore healthcare providers dig into analytics to better understand each patient’s condition, lifestyle choices, work and home environment, they can create personalized treatment plans tailored to that person’s individual behavior. For example, if the patient struggles to remember when to take her medication, her specialized treatment would address that specific problem.
Other health care providers are following Singapore’s lead to better manage patient care, cost and outcomes. By making sense of the data available on an individual patient, doctors and other providers can better understand that person’s history, genetics and even important demographic and cultural factors to more quickly and cost effectively diagnose patients.
23andMe, which sells an at-home mail-in DNA testing kit, has developed its whole model around pulling insights from big data to give customers a 360-degree understanding of their genetic history. 23andMe previously offered health-related results as well so customers would know if they were at risk for certain diseases and conditions. But the FDA wasn’t a big fan of the potential false positives in the results and ordered the company to stop. 23andMe is now gearing up to launch a new online platform that will invite patients of chronic illness to share health-related data to can draw insights — and potentially solve problems doctors can’t — using big data.
It starts — but doesn’t end with — big data
While companies of all industries can better understand their customers and provide better service with the help of big data, there’s more work to be done beyond simply collecting customer data. Companies that use big data well excel in sorting through the white noise of data, filtering out the relevant information and drawing insight from its analysis. Only then can companies begin to put big data to work to target and retarget the right customers, personalize their experience, solve their problems or build products suited to their needs. Big data can certainly be valuable — but only with actionable insight.