A3 in customer experience: Possibilities for personalisation

The value of A3 in customer experience

This report considers the financial value to a telco of using A3 technologies (analytics, automation and AI) to improve customer experience. It examines the key area which underpins much of this financial value – customer support channels – considering the trends in this area and how the area might change in future, shaping the requirement for A3.

Calculating the value of improving customer experience is complex: it can be difficult to identify the specific action that improved a customer’s perception of their experience, and then to assess the impact of this improvement on their subsequent behaviour.

While it is difficult to draw causal links between telcos’ A3 activities and customer perceptions and behaviours, there are still some clearly measurable financial benefits from these investments. We estimate this value by leveraging our broader analysis of the financial value of A3 in telecoms, and then zooming in on the specific pockets of value which relate to improved customer experience (e.g. churn reduction).

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The diagram below illustrates that there are two parts of the customer journey where A3 will add most value to customer experience:

  1. The performance of the network, services, devices and applications is increasingly dependent on automation and intelligence, with the introduction of 5G and cloud-native operations. Without A3 capabilities it will be difficult to meet quality of service standards, understand customer-affecting issues and turn up new services at speed.
  2. The contact centre remains one of the largest influencers of customer experience and one of the biggest users of automation, with the digital channels increasing in importance during the pandemic. Understanding the customer and the agent’s needs and providing information about issues the customer is experiencing to both parties are areas where more A3 should be used in future.

Where is the financial benefit of adding A3 within a typical telco customer journey?

A3 customer experience

Source: STL Partners, Charlotte Patrick Consult

As per this diagram, many of the most valuable uses for A3 are in the contact centre and digital channels. Improvements in customer experience will be tied with trends in both. These priority trends and potential A3 solutions are outlined the following two tables:
• The first shows contact centre priorities,
• The second shows priorities for the digital channels.

Priorities in the contact centre

A3 Contact centre

Priorities in the digital channel

A3 Digital channel

Table of Contents

  • Executive Summary
  • The value of A3 in customer experience
  • Use of A3 to improve customer experience
  • The most important uses of A3 for improving the customer experience
    • Complex data
    • Personalisation
    • Planning
    • Human-machine interaction
    • AI point solution
  • Conclusion
  • Appendix: Methodology for calculating financial value
  • Index

Related Research:

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Driving the agility flywheel: the stepwise journey to agile

Agility is front of mind, now more than ever

Telecoms operators today face an increasingly challenging market, with pressure coming from new non-telco competitors, the demands of unfamiliar B2B2X business models that emerge from new enterprise opportunities across industries and the need to make significant investments in 5G. As the telecoms industry undergoes these changes, operators are considering how best to realise commercial opportunities, particularly in enterprise markets, through new types of value-added services and capabilities that 5G can bring.

However, operators need to be able to react to not just near-term known opportunities as they arise but ready themselves for opportunities that are still being imagined. With such uncertainty, agility, with the quick responsiveness and unified focus it implies, is integral to an operator’s continued success and its ability to capitalise on these opportunities.

Traditional linear supply models are now being complemented by more interconnected ecosystems of customers and partners. Innovation of products and services is a primary function of these decentralised supply models. Ecosystems allow the disparate needs of participants to be met through highly configurable assets rather than waiting for a centralised player to understand the complete picture. This emphasises the importance of programmability in maximising the value returned on your assets, both in end-to-end solutions you deliver, and in those where you are providing a component of another party’s system. The need for agility has never been stronger, and this has accelerated transformation initiatives within operators in recent years.

Register for our upcoming ‘How to drive operator agility’ webinar on 16th June

Concepts of agility have crystallised in meaning

In 2015, STL Partners published a report on ‘The Agile Operator: 5 key ways to meet the agility challenge’, exploring the concept and characteristics of operator agility, including what it means to operators, key areas of agility and the challenges in the agile transformation. Today, the definition of agility remains as broad as in 2015 but many concepts of agility have crystallised through wider acceptance of the importance of the construct across different parts of the organisation.

Agility today is a pervasive philosophy of incremental innovation learned from software development that emphasises both speed of innovation at scale and carrier-grade resilience. This is achieved through cloud native modular architectures and practices such as sprints, DevOps and continuous integration and continuous delivery (CI/CD) – occurring in virtuous cycle we call the agility flywheel.

The Agility Flywheel

agility-flywheel

Source: STL Partners

Six years ago, operators were largely looking to borrow only certain elements of cloud native for adoption in specific pockets within the organisation, such as IT. Now, the cloud model is more widely embraced across the business and telcos profess ambitions to become software-centric companies.

Same problem, different constraints

Cloud native is the most fundamental version of the componentised cloud software vision and progress towards this ideal of agility has been heavily constrained by operators’ underlying capabilities. In 2015, operators were just starting to embark on their network virtualisation journeys with barriers such as siloed legacy IT stacks, inelastic infrastructures and software lifecycles that were architecture constrained. Though these barriers continue to be a challenge for many, the operators at the forefront – now unhindered by these basic constraints – have been driving a resurgence and general acceleration towards agility organisation-wide, facing new challenges around the unknowns underpinning the requirements of future capabilities.

With 5G, the network itself is designed as cloud native from the ground up, as are the leading edge of enterprise applications recently deployed by operators, alleviating by design some of the constraints on operators’ ability to become more agile. Uncertainty around what future opportunities will look like and how to support them requires agility to run deep into all of an operators’ processes and capabilities. Though there is a vast raft of other opportunities that do not need cloud native, ultimately the market is evolving in this direction and operators should benchmark ambitions on the leading edge, with a plan to get there incrementally. This report looks to address the following key question:

Given the flexibility and driving force that 5G provides, how can operators take advantage of recent enablers to drive greater agility and thrive in the current pace of change?

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Table of Contents

  • Executive Summary
  • Agility is front of mind, now more than ever
    • Concepts of agility have crystallised in meaning
    • Same problem, different constraints
  • Ambitions to be a software-centric business
    • Cloudification is supporting the need for agility
    • A balance between seemingly opposing concepts
  • You are only as agile as your slowest limb
    • Agility is achieved stepwise across three fronts
    • Agile IT and networks in the decoupled model
    • Renewed need for orchestration that is dynamic
    • Enabling and monetising telco capabilities
    • Creating momentum for the agility flywheel
  • Recommendations and conclusions

A3 for enterprise: Where should telcos focus?

A3 capabilities operators can offer enterprise customers

In this research we explore the potential enterprise solutions leveraging analytics, AI and automation (A3) that telcos can offer their enterprise customers. Our research builds on a previous STL Partners report Telco data monetisation: What’s it worth? which modelled the financial opportunity for telco data monetisation – i.e. purely the machine learning (ML) and analytics component of A3 – for 200+ use cases across 13 verticals.

In this report, we expand our analysis to include the importance of different types of AI and automation in implementing the 200+ use cases for enterprises and assess the feasibility for telcos to acquire and integrate those capabilities into their enterprise services.

We identified eight different types of A3 capabilities required to implement our 200+ use cases.

These capability types are organised below roughly in order of the number of use cases for which they are relevant (i.e. people analytics is required in the most use cases, and human learning is needed in the fewest).

The ninth category, Data provision, does not actually require any AI or automation skills beyond ML for data management, so we include it in the list primarily because it remains an opportunity for telcos that do not develop additional A3 capabilities for enterprise.

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Most relevant A3 capabilities across 200+ use cases

9-types-of-A3-analytics-AI-automation

Most relevant A3 capabilities for leveraging enterprise solutions

People analytics: This is the strongest opportunity for telcos as it uses their comprehensive customer data. Analytics and machine learning are required for segmentation and personalisation of messaging or action. Any telco with a statistically-relevant market share can create products – although specialist sales capabilities are still essential.

IoT analytics: Although telcos offering IoT products do not immediately have access to the payload data from devices, the largest telcos are offering a range of products which use analytics/ML to detect patterns or spot anomalies from connected sensors and other devices.

Other analytics: Similar to IoT, the majority of other analytics A3 use cases are around pattern or anomaly detection, where integration of telco data can increase the accuracy and success of A3 solutions. Many of the use cases here are very specific to the vertical. For example, risk management in financial services or tracking of electronic prescriptions in healthcare – which means that a telco will need to have existing products and sales capability in these verticals to make it worthwhile adding in new analytics or ML capabilities.

Real time: These use cases mainly need A3 to understand and act on triggers coming from customer behaviour and have mixed appeal to telcos. Telcos already play a significant role in a small number of uses cases, such as mobile marketing. Some telcos are also active in less mature use cases such as patient messaging in healthcare settings (e.g. real-time reminders to take medication or remote monitoring of vulnerable adults). Of the rest of the use cases that require real time automation, a subset could be enhanced with messaging. This would primarily be attractive to mobile operators, especially if they offer broader relevant enterprise solutions – for example, if a telco was involved in a connected public transport solution, then it could also offer passenger messaging.

Remote monitoring/control: Solutions track both things and people and use A3 to spot issues, do diagnostic analysis and prescribe solutions to the problems identified. The larger telcos already have solutions in some verticals, and 5G may bring more opportunities, such as monitoring of remote sites or traffic congestion monitoring.

Video analytics: Where telcos have CCTV implementations or video, there is opportunity to add in analytics solutions (potentially at the edge).

Human interactions: The majority of telco opportunities here relate to the provision of chatbots into enterprise contact centres.

Human learning: A group of low feasibility use cases around training (for example, an engineer on a manufacturing floor who uses a heads-up augmented/virtual reality (AR/VR) display to understand the resolution to a problem in front of them) or information provision (for example, providing retail customers with information via AR applications).

 

Table of Contents

  • Executive Summary
    • Which A3 capabilities should telcos prioritise?
    • What makes an investment worthwhile?
    • Next steps
  • Introduction
  • Vertical opportunities
    • Key takeaways
  • A3 technology: Where should telcos focus?
    • Key takeaways
    • Assessing the telco opportunity for nine A3 capabilities
  • Verizon case study
  • Details of vertical opportunities
  • Conclusion
  • Appendix 1 – full list of 200 use cases

 

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