- January 25, 2020
- Posted by: admin
- Category: Big Data Analytics
By the end of 2020, the world will witness two major changes impacting communications, brought about by Data Analytics. These changes are mainly about the revival of consumers’ trust in voice communications and a shift in how users customize their communication experiences.
End of bad calls with good data
Data scientists feel that the ultimate hero of 2020 will be CPS or Calls Per Second. It is basically the number of calls that can be handled per second. This data originating from CPS can help communications service providers understand if the calls are legitimately made by humans or by automated machines, like robocalls. Although CPS alone is not the solution to ending robocalls, this year will witness the launch of more technologies that will fulfill this aim.
Over the years, robocalling has attracted much attention, with traditional and wireless service providers putting in their best efforts to track and eliminate suspicious and untrusted sources. That is why FCC has mandated that handset providers and carriers use SHAKEN/STIR which assigns a call after validating it with certificates proving its legitimacy. In this way, calls with a low level of verification would be blocked at the network level to completely stop them from reaching consumers.
Communication providers can accomplish this by combining voice-based authentication with CPS thresholds. The mechanism will be somewhat like a CAPTCHA that verifies whether you are a human or bot, to detect suspicious patterns and regulate outbound traffic.
Researchers are hopeful that this will result in more people answering calls in 2020 than they did in the last few years, and the primary credit will be offered to the Big Data and analytics.
Next-level customer interaction with communications data
nowadays, customers actually prefer to chat with customer service personnel than actually talking to them. But this is likely to change this year with more and more people preferring to opt for the traditional method of calling up businesses in case of queries. Now when customers choose to reach out via conventional channels, data scientists can extract that data and mine them for more detailed information that would not only improve the brand presence but also boost customer engagement levels.
For instance, the CRM data can be treated as an onset of the Rich Call Data or RCM that is mainly based on the buying history and the overall shopping experience of the customers. An example of this would be a customer ordering a food item via Uber Eats and receiving a call from the driver with the order ID as the calling ID. And along with this, there can also be an automated message saying ‘driver would want something to know about your food order’.
With companies using multiple data sources to enrich their customer experience, it would not be long since they start utilizing RCS or Rich Communication Services to further improve services by allowing their customers to browse the menu and place an order through a native messaging client. All of these advancements would be powered by none other than Data Analytics.