In the next five years, we’re going to see a rapid rise in the use of data analytics when it comes to enterprise organizations. Most enterprise companies are blessed with data; the reality is they are almost blessed with too much data.
As we move forward into the next decade, data will be used to shape organizations, products, services, and consumer or client behaviour. The organizations that know how to decipher the data they have will be at an advantage.
Data analysis with machine learning and artificial intelligence will shape how enterprise organizations do what they do. It will also determine how they are structured.
The Benefits of Predicative Data Analytics
Companies are now using data to manage or forecast inventory demands, customize their store layouts to maximize sales, or identify a potential customer churn.
The use of algorithms to solve specific business problems with the help of enterprise data can put companies’ years in front of their expected timelines.
These algorithms can be used to identify credit score systems for clients, forecast time-driven events, and increase customer retention.
An example of this was a U.S based insurance company that used data from landing pages to determine a reasonable insurance risk from a bad insurance risk.
Determining those potential customers that used sentence case vs lower case were a better insurance risk.
Armed with this knowledge, they are in a far better place to increase the organization’s profit whilst reducing its risk exposure.
The Advantage of Data Patterns
Combining historical data with machine learning and artificial intelligence, you will be able to predict the future.
All data has a story within it and a pattern that represents your organization’s heartbeat.
How many times does a customer talk with your call centre before they decide to churn?
How many interactions does a typical client have with your website or advertising before they choose to become a client also?
What are the demographics of the client that is most loyal to your business?
What products or services do your existing clients continue to ask for that you currently don’t have in place?
Within your data lies the answer to every one of these questions. Your ability to discover this information will differentiate you from your competition.
Being able to segment your client base into specific clusters and characteristics, you can devise strategies for each group at the micro and macro level.
Of course, this can be often referred to as personalization at scale. But at its essence, what we’re talking about is understanding your client base and solving their problems. This should be the purpose of any and every organization, large or small.
The Future of Data Analytics
As artificial intelligence continues to evolve, it will reach a point where it uses historical data to identify products and services you didn’t know were possible. Or, for that matter, there was a need for them.
AI will use data to predict things about your organization that you couldn’t conceive today.
Presenting a plethora of opportunities for you to get closer to your customer and improve every interaction of your organization. It will show you patterns in your data that you did not know were there. Not to mention your profitability.
We are, of course, at the beginning of this journey but do not doubt that this journey has begun. Data is not the most valuable commodity an enterprise organization has.
Your ability to interpret that data and predict your future is!
