While content marketing may always be the number one way to reach customers on the web, using data science is the number one way to keep them around once you’ve caught their attention. Data science, also called big data or machine learning, helps companies develop the kind of customer experiences that leave customers satisfied and looking for more from a given company.
Building customer loyalty is of course key to longstanding success in any market. How can data science help a company succeed over time with an exceptional customer experience?
Personalize Services To Net Rewards
While customers get worried when services are a little too customized (the classic example being when Target knew people were pregnant before they did), recommendation services that are high quality and geared towards recommending new products to customers has the potential to dramatically improve sales per customer and price point per order.
Amazon, Netflix, and Spotify are all examples of systems that do a great job recommending new products to us that excite and entrance us.
Collect and act on NPS-powered customer feedback in real time to deliver amazing customer experiences at every brand touchpoint. By closing the customer feedback loop with NPS, you will grow revenue, retain more customers, and evolve your business in the process. Try it free.
Give Customers What They Need
One reason that potential customers might avoid using a service like Uber is not knowing how much their fare will be. To address this issue, companies have created fair price calculators that allow customers to get a best guess of what their fare will be before they book a ride.
This is a great example of two ways that big data can be used. Through collecting data, Uber realized that one reason customers were holding back instead of booking their uber ride was being uncertain about what the price of the ride might be. With a fair price calculator, customers can get a solid estimate of what the ride will cost before they book it, and can make sure that what they end up paying isn’t too far off what they were expecting to pay.
Calculators like this also use big data to estimate the costs of a ride. After all, it’s impossible to determine the cost of any single fare before it is complete. Uber can, however, look over available customers data who traveled similar distances at similar times and feel comfortable that they’re fairly accurate with their suggestion. A fare calculator is only as valuable as its estimates; if it underestimates, customers will get mad about overpaying; if it overestimates, it may turn off customers before they make their purchase.
Fix Issues Before They Happen
It’s always been important to avoid issues with customers, but given how quickly a negative story can spread on social media, it’s more important than ever to avoid unpleasant customer experiences whenever possible.
One way that big data can improve customer experiences is spotting problems that the average human simply can’t see. For example, several separate customer service reps might all get singular calls reporting a minor issue with a product and disregard them. A computer dedicated to machine learning, however, may be able to identify the problem across several call logs and alert someone to investigate the problem immediately.
This can also be important on manufacturing floors and other similar situations. Master Data Science can track small signs that machinery is wearing out or breaking down and alert technicians for a fix before the machinery begins to create quality control issues.
Optimizing Product Locations
In both brick and mortar stores and online retailers, organizing products in an optimal pattern is always interesting. If a customer is browsing for a fire pit, for example, having barbeque tools nearby may just be logical.
But big data can tell you that, perhaps, someone purchasing a fire pit might also need a new table and chairs for their deck, or a game for the backyard. This can allow you to better arrange your store by creating product associations and increase the amount a customer purchases per visit.
Companies do need to be careful of the extent to which they use big data. Many customers do not trust corporations with their information, and will opt out of cookies and other collection options whenever possible.
The best way for businesses to improve customer willingness to share their information is to be responsible with it. This means that it will be protected from others, never sold, and used carefully.