AiThority Interview Series with Kirill Rechter, CEO at LogNet B******

AI-based algorithms can be applied to consumer data to make sure that a business is run efficiently and operational costs are minimized.

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In your professional opinion, how has the b****** operations of service providers evolved in recent years?

There was a time when b****** was just an operational function. Twenty plus years ago, when there was just one phone company, one gas company and one electricity company in each market, b****** only meant that usage was calculated and invoices were sent to customers on a monthly basis.

Over time and especially in recent years, b****** in most service markets has become extremely complex and now covers multiple services. Take the telco vertical, for instance, where most service providers are offering a multitude of services, each with its own pricing and b****** parameters. Individual services are typically bundled into packages and offered as part of some type of promotion, which is often based on a highly involved cross-service threshold and volume discounts.

At the same, customer expectations regarding b****** activities has changed dramatically in recent years. Given that customers in most service markets have competitive alternatives to choose from, they expect complete transparency and full control over b****** data and charging information. This point is the main driver behind most digital transformation initiatives at service providers in many vertical markets, especially in the telco and energy supply sectors.

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Would it be correct to say that b****** is now a strategic part of a service provider’s operations, especially in competitive verticals such as telecom?

Yes, this is absolutely correct.

We have a concept that we promote called Modern B******. The idea is that a service provider can leverage its b****** operation as a driver to attract new business and keep customers satisfied and loyal. Automated service delivery, simplified customer support, and transparent b****** are all part of this Modern B****** concept and create important advantages for service providers in competitive markets.

A strong b****** infrastructure that supports multiple services can be used to pursue strategic plans, such as entering new service markets or improving customer service and so on.

Can b****** be considered a direct extension of the customer journey?

B****** is not just an extension of the customer journey, but rather a significant and important component of it. Much of the conversation in the media and other published content about the customer journey focuses on managing communication and interaction touch points with both potential and existing customers.

Efficient b****** processes, especially within the framework of our Modern B****** concept, will definitely add value to and improve the overall customer journey. Most of the communication and interaction touch points of the customer journey involve b****** in some capacity. For example, in the utility market, there is a concept of “Meter-to-Cash.”

These are the operational processes that support energy and utility suppliers business and operations, customer interactions and revenue generating activates. The functional coverage of Meter-to-Cash processes is much wider than say five to ten years ago and is constantly expanding. B****** plays a central role in Meter-to-Cash processes and must be integrated with other systems that are used, including omnichannel contact centers, e-commerce platforms, CRM tools, chatbots, BI systems and more.

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How can AI be applied to b****** operations to improve the overall customer experience?

Artificial intelligence can certainly be used in a number of areas that will benefit both the b****** operation and customer experience. One example is applying AI-based predictive models to compare actual and expected b****** output using data points of any given customer. These are referred to as sensibility checks and are used to avoid operational mistakes on immense and otherwise unmanageable volumes of data and ensure the accuracy of b******.

AI and Machine Learning can also be used to make more accurate estimations of consumption trends to better forecast expected charges and income. This has many applications in various verticals and is essential for service providers managing multiple service environments in which they need to reconcile with external service suppliers by utilizing both internal historical and external data reports.

AI-based algorithms can be applied to consumer data to make sure that a business is run efficiently and operational costs are minimized. This is common in the energy supply business for forecasting demand and better managing inventory.

AI can also be used for fraud detection and recognizing suspicious communications traffic or abnormal consumption patterns.

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Where and how has AI been incorporated into your MaxBill technology?

AI and Machine Learning is incorporated in many areas of our MaxBill solution and is being used by our service provider customers in different vertical markets.

Our energy supplier and utilities customers are using the AI-driven capabilities in MaxBill to accurately predict future demand based on historical consumption data. These predictions allow these service providers to better negotiate prices with their suppliers and maintain the correct inventory levels.

Our telco customers regularly run AI-driven “what-if” scenarios to understand the market potential of new products and service packages. For voice communication services, data analytics can be applied to call histories to evaluate and forecast the most valuable service propositions for targeted market segments.

In the gaming sector, our online c***** operator customers have highly complex, multi-layered business agreements with their partners. Our AI-driven reconciliation capabilities provide automated calculations on large volumes of granular data that expand the business capacity of our gaming operator customers.

How are your customers benefiting from these AI-enabled capabilities, in particular, in the areas of Sales and Marketing? 

The AI-enabled capabilities in our b****** system are allowing our service provider customers to better personalize service and product offerings to specific customer segments. This is being done in both B2B and B2C environments. This is often done by running highly granular “what-if” scenarios that include detailed parameters of each service and can involve multi-layered analyses of cross-service package options.

We also offer many AI-driven applications for predicting customer behavior that can be used for reducing churn and identifying upsell opportunities.

Of course, chatbots are fully integrated so that b****** information is available over this AI-driven communication channel and can be leveraged to provide recommendations in the context of consumer data.

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What additional applications of AI do you see being rolled out in service provider operations in the near future?

The use of AI will continue to grow most strongly in the areas with applications involving improving the customer journey. The emphasis will remain on the personalization of customer communication to bring the best customer experience. This will include services recommendations that will bring the most value for the customer or predictions of the expected charges.

Service automation is another area that AI applications will continue to expand in terms of service delivery and network management.

Thank you, Kirill! That was fun and hope to see you back on AiThority soon.