Business Intelligence Examples: How Data Solves Real Business Problems  

colorful words saying big data

Companies that understand the way big data can improve business for them are hiring data scientists for the job. In fact, they have begun dividing their team of scientists into three tracks that lead to sure success, i.e., for inference, analytics, and algorithms. The higher the clarity, the more effectively such teams will be able to communicate and add value to businesses.

If your company hasn’t yet determined what data science means for your business, it’s time it did! Beware though because, after all the thought that was put into segmenting the many sub-domains of big data, many organizations still miss the point. Data science isn’t about specialized degrees or algorithms. It is for solving real business problems.

Finding it hard to believe? Here are some Business Intelligence Examples:

With Data, You Can Determine The Probability Of Whether A User Will Buy Your Product Or Not

This year, the total value of e-commerce generated sales will be more than $3.45 trillion from all over the world. Sure, droves of customers are buying from Amazon or Alibaba, but those aren’t the only sites trying to sell their products. Other companies are making huge efforts while trying to get themselves noticed. From cross-platform marketing to advertising and content marketing, they are doing a bit of everything.

All their hard work may pay off but then again, it may not. That’s because the companies don’t know how effective their ads or the sites where they promote those ads are. Many of them realize that and want to answer a simple question: Are the customer engagements and impressions that we are turning into real dollars or not?

Data can help you answer that question. Let’s say your e-commerce business sells kitchen equipment. You are spending as much as your budget allows on the cross-promotion of products on other sites and your own eCommerce site. By showing diligence in the use of tracking cookies, you are aware of the average purchase rate you get from all sources.

To become one of the Business Intelligence Examples, you can use data to find out how much money to invest in future campaigns. If, say, ten people from site A purchase your products in an hour, using Poisson’s distribution to calculate the probability of how many people (n) will show up every hour.

With ten people, you have a 94% chance of selling at least ten items in an hour. The figure drops to 70% with six people showing up within the hour. Therefore, you can use data to decide whether you want to advertise on-site A or not.

With data, it is also simpler to reduce customer churn.

Use Data To Keep Callers From Hanging Up

We have another one of the many Business Intelligence Examples made possible by the use of data. It isn’t news that your customers don’t like to wait for service; they never have. But in the digital age, the hatred has seen an exponential increase. Most information is available to a consumer at the touch of a keyboard. Why should they wait? The time from three years ago when they were willing to wait 13 minutes for it is gone. Survey shows that over 65% of the respondents consider waiting to consist of just two minutes-long. About 13% said they would prefer no waiting time.

Chatbots may be limited in functionality by what they can do. However, besides answering simple questions from the customers throughout twenty-four hours, they can do one more thing. They can learn to identify the questions, analyze them, and improve via machine learning and NLP, based on the best answers that human service reps give to more complicated queries (existing data).

While companies use this data to train other customer service reps, a larger number of qualified human beings will be free to talk to the customer. Thus, companies can use big data to improve their customer’s overall brand perception.

You may already have read another example in our previous post (Insert Link Here) about Machine Learning and fraud detection.

Data Science Improves Degree of Customization

Airbnb, one of the world’s biggest vacation brokers, uses data to inform itself about its customers’ needs. From predicting the prices and which places will be available for renting to understanding renter demographics, they leverage data science to its fullest. But that isn’t all they or businesses who are facing a large amount of data from customers can do with it.

Their open-source pricing system, Aerosolve uses machine learning techniques to predict the optimal price for any rental based on various attributes. Thus, their customers get a place to rent that is exactly ideal for fulfilling their vacation needs. A high degree of customization like that usually improves business!

Want information on more Business Intelligence Examples that are similar to the business you run? Are you just about ready to enter the world of big data? In either case, call us to talk to a 4sights data analytics expert right away!

Leave a Reply