Nowadays analyzing big data has become a significant business tool. It’s constantly changing the way brands operate and market their products across various fields and industries. In fact, every company today, regardless of size, is considered to be a data business in some measure.
Therefore having a well-thought-out data strategy is ultimately important in case you want to achieve success these days. So if you’re still drowning in statistics trying to collect as much information as possible, stop. Here are some basic guidelines on how to use data analytics to your advantage and help your business thrive.
Upgrade user experience
There are hundreds of ways that can help you create the best UX possible. But one of the most effective and accessible tools any company can use to enhance user experience is data.
All because it allows building better consumer profiles. Gather information from your website, analyze the Facebook page or any other web-based content of yours and voila! You have a comprehensive overview of who your clients are, what they like, when they attend your platform, and, what is more essential, how they perceive your brand.
Of course, it’s not as simple as it seems. Because — surprise — this information is absolutely useless unless you learn to extract the specific patterns of customer’s behavior that affect user experience. But once you find them, you’re good, having brilliant data-driven engaging UX that can easily win customer loyalty.
Deliver superb client service
Processing information in real time is essential for top-grade service. With the help of big data, you can send product notifications once your clients enter the mall, navigate them to the store or even identify their preferences in one click.
http://fortune.com/2017/06/08/nordstrom-weighs-going-private/
And if it sounds too futuristic and non-viable to you, take a look at such brands as Nordstrom. This fashion retailer has already integrated data insights into their business strategy. For instance, their shops are equipped with digital devices that give recommendations based on the client’s purchase history both online and offline — practically replacing live personal shoppers.
Optimize prices
With the help of data analytics, you can constantly adjust the prices to the current situation. It helps you monitor the competitor’s pricing, growth or decline in demand, customer interest, market trends and so on.
The examples are countless: e-commerce stores that give a last-minute discount to avoid customer leaving the shopping cart, airlines that change ticket cost according to destination’s popularity or hotels that lower their prices during a storm. All those manipulations help not only maximize the income but even discover certain buying patterns that can play a major role in a company’s future.
Prevent customer turnover
https://blog.rjmetrics.com/2013/01/08/ecommerce-churn-rate/
Losing customers? Use a predictive churn model to find out who of your clients are about to break ties with your company and why. This technique processes historical purchase and behavior data of the lost customers, arranges it into a pattern and searches for a match.
If some correspondence has been found, the tool indicates the clients who are at risk, giving the company a chance to initiate remedial actions. Plus, it helps business owners understand the main reason of churn, which in some cases may be extremely hard to define.
Personalize and customize
While most of your competitors use “one size fits all” business strategy, you can create experience perfectly tailored to your consumer’s needs and interests . Processing big data analytics allows you not only personalize service and communication but deliver unique custom products.
As Jim Vernon, CEO and founder of first AI-based custom jewelry company RockHer and the first worlds digital diamond expert Rosi, says: “Customers are tired of going to retailers and simply picking a ready-made engagement ring off the shelf, almost feels anti-climatic to them; they want something special made just for them”.
Forecast demand more accurately
Thanks to data analytics, nowadays companies can go far beyond outdated demand forecasting techniques. Instead of using obsolete methods built upon the age-old adage, you can apply big-data advanced analytics and radically improve the accuracy of your predictions. It is especially helpful for big supply chains and large retailers that need to decide precisely how much, when and which products should be stocked in inventory.
Optimize delivery and distribution
By monitoring GPS and telemetry data along with real-time traffic and weather situation you can improve the quality of your delivery service. For instance, find optimal routes, shorten order-to-delivery time or even foresee the upcoming orders.
“How is it possible?”, you would ask. Well, take a close look at Amazon’s anticipatory shipping system they have patented nearly four years ago. As soon as you realize that big brands already use and benefit from it, the idea of shipping products before they have even been ordered won’t seem to you so blue sky anymore.
Boost advertising effectiveness
Big data analytics also helps business owners analyze marketing channels and spread the financial resources accordingly. So forget about wasting budget on ineffective advertising. Instead, analyze the behavior of each consumer and use click-by-click data to identify what ads your customers better respond to.
If you know that third of your clients ignore web banners, but read the personalized notifications about the same product, you would definitely think twice before spending money on those banners again.
To sum it up
Using data analytics is a killer business strategy. Even though it takes time and lots of effort to figure it out, it gives your priceless insights and opportunity to achieve your business goals faster than ever before.
We all understand that the days of relying on gut feelings in business have passed. The era of “intuition is everything I need” has ended and today nothing works best than data-driven strategy and analytics.
So don’t be afraid to experiment and step out of your comfort zone. Use data analytics to your own benefit and revolutionize your business while others bury their head in the sand.