Telcos tapping into Flytxt's AI-driven marketing automation software for customer satisfaction, profitability

Flytxt is using machine learning and artificial intelligence to focus service providers' marketing efforts. (Pixabay)

For the past eight years, telcos have tapped into Flytxt's automation and machine-learning software to increase customer satisfaction and profits.

Flytxt is a customer-engagement technology firm that leverages machine-learning software to create improved marketing opportunities for telcos.

As networks become increasingly complex, machine learning, artificial intelligence and automation are essential ingredients for networks, services and applications. Customers want the same on-demand, intuitive services they are now getting from the likes of Google and Amazon. In order to become more dynamic and flexible, telcos are looking to deploy more machine learning and AI to meet those customer expectations.  

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"Our technology maximizes the value of customer interactions for telcos as well as for other business-to-consumer enterprises," said Flytxt CEO Vinod Vasudevan in an interview with FierceTelecom. "The software learns about the telco customers from a vast amount of dynamically changing data. It learns. It predicts and it recommends. That's really what the software does."

Vasudevan said telcos use this information for customer-experience management by building deeper, more sustainable relationships with their subscribers by marketing the services and applications customers actually want.

"The software predicts what the customers' expectations are and then makes recommendations from the portfolio of products and capabilities that telcos have," he explained. "It compliments what is best for the customer.

"We have 100 companies that we serve around the world with more than 60 of them being telcos. Across the board, they get a 2%-to-7% uplift in their net revenues every month that is measured by the software."

Last month, Flytxt announced it had signed a deal with America Movil Group, which serves customers across Latin America and the Caribbean. America Movil is using Flytxt's software across its quad play services. Other Flytxt customers include Vodafone MTN, Viettel Telecom, Airtel and Zain Group.

The software, which is called NEON-dX, uses machine learning to understand subscribers' preferences and to predict the products they are most likely to want. A recommendation engine uses both machine learning and AI to make subscriber recommendations. These can go back to the telco or directly to the customers.

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"First, you use intelligence and ML to automate the process," Vasudevan said. "Then you go to making the process far more efficient with the marketing automation part. Today, depending on the telco and the network, marketing processes can take anywhere from seven to 28 days. We basically make it fully automated so that the telco can act in a matter of minutes.

"The intelligence comes in where you make recommendations and engagements far more sharper. So that's the second stage."

Similarly to how Amazon matches customers with products, in the third stage Flytxt works with telco customers to determine the balance between customer satisfaction and profitability by matching products with the service provider models.

Flytxt can gather data from telcos' OSS/BSS systems, data nodes, text messaging nodes and Facebook or company websites.

"So, typically the telco has to decide which sources they want to use," Vasudevan said. "We don't store the data and we don't look at the information. It flows to our platform and our software analyzes it in real time and extracts the insights and then uses those insights for predicting and recommending."

Vasudevan said the value of his company's software would increase with virtualized networks because it will become easier to extract more data from a variety of sources.

"When the network functions are virtualized—telcos are still in an early stages—we expect the recommendations and machine learning will significantly improve," he said. "We are expecting that we will be able to go 7%-to-10% uplift in revenue at the upper end when there is more virtualization and software-defined networks in place. 

"We work with hybrid networks, mobile network operators, which are less virtualized, and MVNOs, which are much more virtualized. So across the board we work with a variety of service providers today."

As for Flytxt's road map, Vasudevan said his company is working with telcos to create a common view of the products they have and then dynamically decide which products should be designed and offered going forward.

Flytxt competes with SAP, Adobe and IBM on the large end, and against niche area companies such as Pontis and Pega Systems.