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The Adaptive Technology Serving Billions of Unique Customer Demands

By Martin Laesch, Chief Technology Officer, Neural Technologies

As our digital ecosystem becomes increasingly connected, enterprises face unprecedented levels of unique customer service demands. To do more than just survive in today’s business environment, organizations need adaptability, innovation, and flexibility. To thrive, enterprises must maximize their ability to charge for personalized services, which end users now expect and demand in our ever-connected world.

The rise of personalized demands

As customer service providers move to 5G, more Internet of Things (IoT) applications and connected markets are creating new experiences and new potential services. Consumers are at the center of this drive, as they expect to contribute to and dictate a unique, customized experience with many digital experiences at their fingertips. From connected smart homes to wearable technologies, the more personalized the experience is, the more value it brings to the consumer’s life.

The majority of consumers said they would be willing to pay more for a customized product or service, according to research by Deloitte. In addition, businesses that do not create personalized experiences risk losing revenue and customer loyalty. However, it is not easy to make sure that each customer has a unique experience while still making a profit.

In such a competitive landscape, each opportunity to meet a unique service demand needs to be recognized as an opportunity to explore a new potential revenue stream. With personalized services dictating customer loyalty, providing such services is becoming more of a necessity for sustainable business growth, as opposed to an option. With so many personalized and individual needs to be met, an automated approach to charging for services is the only feasible way to charge customers accurately.

Nothing is too complex

As enterprises rise to the challenge of managing the complexity of services and accurately charging for them, they will turn to a flexible, automated solution that will successfully support the progression of its business model. Within this, they will need to adapt and create new tariff structures for unique services.

An automated, flexible, multi-levelled tariff ecosystem is being used by leading telecom operators to enhance customer experience and attract loyal customers. This approach is an automated solution that uses deep analytics to identify and charge customers for the unique services they require. The use of dynamic technology can support the growth of business models through its power to innovate new services using data intelligence at the time when a customer needs it the most. Fundamentally, using a charging solution can help measure what customers want and position processes and resources to deliver.

Harnessing data intelligence

The learning process is key within this relationship between the personalized service and the customer. It needs to be right, and getting it right is different every time. The use of sophisticated Machine Learning (ML) technologies is the difference between making the right business move and making the wrong business move. By using data intelligence and deep analytics, enterprises can make more informed business decisions based on what the customer wants, and which services are needed.

Following years of delivering ML solutions to enterprises and telecommunications service providers around the world, Neural Technologies has witnessed first-hand the power of digital transformation solutions to support the growth of business models and revenue streams. The use of data is available to every enterprise. With the support of a leading ML solution, it can harness this data and automate effective and profitable charging processes.

Avoiding revenue leakage

While a flexible charging solution helps identify new services to charge customers for, it also helps capture services that are not being charged for. Using data intelligence, the technology can capture and report discrepancies and prevent customers from being over-charged or under-charged. Amid a constantly evolving tariff system, a flexible service charging model is necessary for retaining loyal customers. With the use of automation, a flexible charging system can also help enterprises meet customer service demands in “real time” and maximize profitability from these transactions.

As a complete cloud-based charging, analytics, and revenue assurance platform, CaaS has the ability to adopt a wide variety of tariff structures at any level of complexity. This includes all charging deployments, from peak hours, to discounts, to geo-zoning, ensuring that all scenarios of customer usage and billing are covered. Being a multi-levelled tariff ecosystem, CaaS can support use cases such as Utility Metering, IoT Rating, Revenue Assurance, and Billing Reconciliation.

The solution provides both maximum flexibility and profitability to improve customer experience and enhance profits, while future-proofing the network and leaving room for inevitable structural evolution. Offering effective solutions to facilitate operations in every aspect of customer charging, it works to develop innovations that not only serve the purpose of optimizing current network efficiency, but also support continual growth, both corporately and technologically.

To help combat the challenges faced within the industry, CSPs are increasingly harnessing revenue assurance capabilities to guarantee an accurate and safe revenue stream with no leakages. With built-in platform security, this type of solution also offers cutting-edge data quality, ensuring an accurate and secure means of transformation, while maintaining ROI and enhancing customer experience.

Bio

Martin Laesch joined Neural Technologies in October 2015 as Senior Vice President of Professional Services and is now the Chief Technology Officer. Martin is responsible for the global Strategy and Products, Solutions development as well as the Consultancy Services to customers. Martin has more than 20 years’ experience in telecommunications services and the software industry, filling roles from Project Manager to Managing Director. Martin joined Neural Technologies in October 2015 by acquisition of Enterest GmbH, which he co-founded in 2003. Martin holds a Master of Computer Science degree.

Look in the Mirror and Foresee the Future of Telecommunications

By Martin Laesch, Chief Technology Officer, Neural Technologies

The adoption of 5G will unleash the full potential of augmented and virtual reality, Smart Cities, and the Internet of Things (IoT); this will present opportunities for Communications Service Providers (CSPs) to strengthen current revenue sources or create entirely new revenue streams. Consumers continue to display an insatiable appetite for data and with the consumption of data-hungry applications securing a place in consumers’ daily lives, data usage is set to continue increasing exponentially into the future.

CSPs currently face the ever-increasing challenges of leveraging 5G networks and offering customers new types of services. To overcome these challenges, new digital technologies are required to automate complex business processes to provide customers with the personalized service they have come to expect in a fast-evolving, digital world.

By 2025, CSPs should already be leveraging 5G networks to offer new types of services to various customer segments. The challenges of this endeavor will lie in the ability to scale telecom platforms, automate lifecycle management of network slices, and incorporate predictive demand and maintenance – all while ensuring operational efficiency and a behind-the-scenes workforce to support platform optimization.

Using automation to improve customer services

To address these challenges, an Analytical Data Model (Artificial Intelligence [AI] Data Model) and Machine Learning (ML) were used to develop the Digital Twins technology and tested as part of the 2019 TM Forum Digital Twins catalyst project. The technology serves as a virtual representation of a real-world entity or system, which acts as a mirror to provide a means to simulate, predict, and forecast behavior in the digital world. As part of the catalyst project, the Digital Twins technology was applied to various use cases, such as networks, individuals, organizations, and processes, to determine their effectiveness for telecom industry applications in order to address the aforementioned challenges predicted for 2025.

For the Digital Twins technology to be possible, a common data model is essential. All data needs to be classified and structured in the same way for the digital technology to perform. Digital Integration is the first step to making this possible.

One example of a Digital Twin is that of a customer. A customer’s Digital Twin will be represented in a heatmap with icons to help visualize aspects of their digital lifestyle, such as whether they spend a lot of time gaming, have high mobile usage, or are physically inactive. This twin can then be used by the CSP to tailor messages to that individual. For example, the Digital Twin may show that the customer has a low step count, which could trigger a notification to the individual to be more active.

Using a Digital Twin, operators can also determine where there will be a significant increase in latency within the network, and then share that information with the customer’s Digital Twin to find out what is going to be affected and determine the next best action.

The Digital Twin can also speed up product development cycles, save time and money, and create new business models based on intelligent outcomes. This allows enterprises to personalize the customer experience and meet their precise demands, thereby enabling the enterprises to grow and improve their customer base through targeted campaigns, tailored services, and promotions. In turn, this generates greater customer loyalty and retention as well as customer spending through personalization with timely, individually tailored offers.

Proven methods for the future

The TM Forum Digital Twins catalyst project proved that Digital Twins not only work for the manufacturing industry, but for the telecommunications space as well. As part of the project, Neural Technologies successfully created a Customer Twin alongside the collaborative development of a Mobile Network Twin and an Enterprise IP Network Twin, all originating from the core AI Data Model.

In addition, the catalyst project also demonstrated real-time communication between the twins. Using the proposed TM Forum Open Application Program Interfaces (APIs), Neural Technologies was able to share such simulated, forecasted, and predicted outcomes so that each individual twin was able to recommend a more informed action, instead of a siloed view.

Ultimately through using Digital Twin technologies in the telecommunications industry, a more holistic view across the whole of the operator’s network will be achievable, making it possible to not only make more informed recommended actions, but also make equally fast decisions. As a result, all such “what if” scenarios could now be done in the virtual world without affecting the real world.

Next to the challenges the telecommunications industry will face with the ever-growing volumes of usage data, software vendors like Neural Technologies need to provide solutions that are able to exchange data with any kind of connected system. Information exchange between systems will be key. and the usage of real time APIs will grow. Industry standards for these APIs, like those specified through the TM Forum Open APIs, will help to standardize the exchange of information which Neural Technologies fully supports already today.

With more data becoming available through the Internet of Things and 5G in the future, operators need to prepare themselves to leverage this data. Data is every operator’s asset, and using AI and ML, these assets can be mobilized to enable CSPs to strengthen current revenue sources by creating entirely new revenue streams. Ready to help CSPs achieve these goals, Neural Technologies’ state-of-the-art digital transformation and analytical technologies can help CSPs leverage this data and create new revenue streams.

Bio

Martin Laesch joined Neural Technologies in October 2015 as Senior Vice President of Professional Services and is now the Chief Technology Officer. Martin is responsible for the global Strategy and Products, Solutions development as well as the Consultancy Services to customers. Martin has more than 20 years’ experience in telecommunications services and the software industry, filling roles from Project Manager to Managing Director. Martin joined Neural Technologies in October 2015 by acquisition of Enterest GmbH, which he co-founded in 2003. Martin holds a Master of Computer Science degree.