Using AI and Data Analytics to Monetize Data: 4 Techniques

Companies can monetize data by using metrics to upsell and improve customer experience, among other techniques.

The economic value of data for companies is challenging to conceptualize and measure directly. Many executives have the wrong perception of data monetization.

To them, the only way to derive economic value from data is to sell it to other companies. As a result, they overlook the immense untapped value that it represents. Companies can monetize by improving customer experiences, reducing costs, finding new customers, and so much more from the data that is produced directly or indirectly using big data analytics and AI.

Of course, this isn’t news to everyone. Many B2B businesses understand that data monetization using AI and data analytics can create higher returns on investment and streamlined operations. However, despite the will and the knowledge, they are unable to maximize results.

The reason for this is simple: They’re still treating data as the tech component of their larger strategy. What they should be doing is putting data in the driver’s seat.

Let’s examine how data analysis using AI and Big Data Analytics can assist in monetizing data.

While upselling may have originally been viewed as a way to sell more products, it’s now a way to sell more relevant products. With data analytics driving the decision-making, businesses can suggest products that are complementary to their customers’ purchases and that bring value to customers. Greater value for the customer means their satisfaction increases, which helps with customer retention.

In addition, the original goal of making more sales is achieved as well. When the customer sees that their needs are being predicted and addressed, they will likely appreciate the service more. This new way of sale shows that businesses can make more sales and additional revenue by optimizing their operations with a data-driven approach, without selling the data to a third party.

It’s no surprise that customers return to businesses that are easier to deal with. Delivering high-quality support is a growing pain point for many companies. Chatbots based on machine learning algorithms can help relieve some of this pain. These chatbots can handle the most common use cases, and a representative can step in for more unique demands. It can reduce query response times and maximize customer satisfaction.

Chatbots play a crucial and helpful role in solving minor problems for customers, which frees up precious time for customer reps to focus on the more complex issues. Consumers prefer to interact with companies that can respond in real time while making a purchase, much like interacting with a sales associate at a brick-and-mortar store.

Thus an AI-driven chatbot can help your customers find answers to their questions when they place an order. It gives the impression that your brand is always there to serve their needs, even during those late-night shopping binges (when all your sales reps are probably asleep!) Furthermore, AI can integrate fragmented data sources to collect all the information regarding customer experience, to create a customer-centric approach.

Anyone with experience in sales knows that it’s a war zone. Having the highest quality data can optimize the entire process. Salespeople can benefit significantly through an AI-based data-driven business model.