In 2019, Energy & Utilities must leverage Conversational AI Platforms to boost Customer Experiences
Photo by Bence Boros on Unsplash
- January 21, 2019
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Today, Energy & Utility (E&U) companies are reeling under pressure in coping up with the evolving expectations of customers in the digital era. To address this challenge, one key approach is to bring in conversational user experience, as part of your CX strategy. This will elevate your Customer Experience (CX) by harnessing the power of AI onto customer facing systems & operations. In this context, E&U companies are showing a strong preference to leverage the technological advancements of Intelligent conversational interfaces to drive customer interactions through chatbots, virtual assistants, voice enabled smart-home devices.
They bring in the significant advantage of saving time, while simultaneously providing a convenient form of communication, that can help energy companies to create more positive customer impressions.
We have seen very positive developments of conversational AI in Technology & Retail industries, but energy companies are still waiting by the fence to understand its potential and are hesitant to quickly bring it for everyday use.
The growing maturity of conversational AI promises to unlock many creative opportunities for boosting CX.
Example - Imagine the future where the art of possible can bring an interesting intersection of conversational platforms with immersive experiences. This will lead to potential developments of conversational immersive experiences in a world where humans and technology-enabled systems interact in increasingly open, connected, coordinated and intelligent ecosystems.
While this sort of propositions, might look too far-fetched from reality, four key recent citations from Gartner also provide impetus to these sort of developments -
- By 2022, more than 50% of all people collaborating in Industry 4.0 ecosystems will use virtual assistants or independent agents to interact more naturally with their surroundings and with people
- 25% of customer service and support operations will integrate virtual customer assistant (VCA) or chatbot technology across engagement channels by 2020, up from < 2%in 2017
- Nearly 72% of consumers showcased that they were interested in AI to manage their Connected Home solutions (i.e. Utilities in the home like Heating, lighting etc)3
- Virtual Agents will account for 46 percent of the global AI-derived business value in 2018 and 26 percent by 2022
Two key advantages that conversational platforms bring in that inspires trust in these emerging trends are -
- Informal & Bi-directional interactions – This is important as it provides loads of opportunities to better engage with customers through personalization. Also, it has the potential to mature into the preferred form of customer communication channel for its simplicity.
- Data as an asset for Voice of Customer - Understanding conversational data with a proper context will uncover critical insights around the inherent individual preferences, views, opinions, feelings, and inclinations. These insights provide astonishing recommendations for improved decision making
Let us analyse some most popular E&U use cases used for conversational experience, which have brought in the advantages of automated self-service along with the ability to escalate to a human agent in complex situations
- Customer Care - MyAccount: Today E&U companies invest heavily in Call Centre operations for fulfilling tons of customer service requests & complaint resolutions. Most of these queries are fundamental in nature, that have immense potential to be efficiently transformed with an automated self-service solution in combination with intelligent human intervention capabilities. The conversational system can also be embedded with intelligence to perform certain automated workflows to fulfil service requests like billing usage analysis, setting reminders, proactive alerts and notifications, to complex work flows like make bill payments through saved cards etc. This will eventually lower cost of operations and simultaneously increase your customer satisfaction.
- a. Customer outreach communication for energy efficiency programs
- b. Enrollment in energy saving or demand response programs
- c. Account issues, such as password reset
- d. Initiating service moves, cancellations, address changes etc.
In this context, it is equally important to understand the premise and assumptions for such service flows
- Need 24/7 support
- Can resolve predictable requests with simple results
- Have low involvement and are low-touch interactions
- Repeatable processes
- The data already exists in backend systems
- The information customers are seeking is relatively simple to provide to the end user
- Technology enabled Employee interactions with Equipment/Devices: This is appropriate specifically in Field Operations. Voice technologies work well in environments requiring hands-free requests for real-time information, a common scenario for lineman and other utility field workers. When connected to backend systems like GIS, DMS, and OMS it can provide hands-free access to critical operational information like service history, transformer power ratings, current network status etc. for field worker, which boosts worker efficiency and improved access to data on the field
- Management Reporting – Superior convenience can be brought-in by integrating the virtual assistants with Business Intelligence systems for utilization in creation of management reporting activities, especially operational reports which are consumed on a daily basis.
Industry First Movers
Blue Lab, EDF Energy’s innovation accelerator, Brighton, UK
In Collaboration with Amazon, they established an initial Voice User Interface (VUI) framework to identify & develop four use cases to meet core customer needs and provide a stand-out experience:
- check account balance
- check when next payment is due
- check the contract end date
- submit a meter reading
- TXU Energy, a retail electric provider, Texas, USA
Using Amazon's in-home assistant Alexa, TXU customers can:
- Adjust their thermostat make customers' homes smarter and change their TXU iThermostat’s settings anytime, from anywhere
- Access billing information Understand their account balance, make a payment, and Alexa can even provide the 24/7 phone number to TXU Energy's friendly customer service team
- Exelon company has built a working prototype of the chatbot that continually monitors and adapts to how people ask questions and what they expect.
Busting some myths
There is also confusion created when AI is interchangeably used with intelligent platforms. AI can be used within a conversational system to drive decisions or perform voice recognition, language processing, etc. but conversational systems are not simply “AI”. Same is the case for RPA. RPA works great as a quick way to integrate systems and automate tasks without costly systems integration but has little to do with conversational interfaces. However, RPA can be used within a conversational system.
To better understand this let’s look at this simple example in airline bookings - a user might use a chatbot or voice assistant to book a flight – the chatbot can call out to execute an RPA process on the back-end to click around and enter data within another system to book the flight
Then what are the conversational platforms which are most recognizably implemented and experimented by leading E&U companies?
Virtual personal assistants (VPAs), such as Amazon Alexa, Apple’s Siri, Google Assistant and Microsoft’s Cortana
Virtual customer assistants (VCAs), such as IPsoft’s Amelia, Watson Virtual Agent, and VCAs from Artificial Solutions, Interactions, Next IT and Nuance
Chatbot frameworks, such as Amazon Lex, Dialogflow from Google, IBM Watson Assistant and Microsoft Bot Framework
So how do the companies choose and differentiate among the available intelligent platforms? Should they wait longer for the technologies to become more mainstream? As cited in Gartner Top 10 Strategic Technology Trends for 2019, one of the primary differentiators among conversational platforms will be the robustness of their conversational models and the API & event models used to access, invoke and orchestrate third-party services to deliver complex outcomes.
It is also forecasted that through 2020, application vendors will increasingly include conversational platforms in their packaged applications, that will drive the maturity of conversational ecosystem in the enterprise landscape.
Another important dimension that needs to be reflected upon for deployment is the IT Security challenges arising from these shifting user experiences. The aspects of Privacy & Security for the connected ecosystem where some of the devices that are in “always listening” mode for collecting information from users without their consent, will also come under tight regulatory scrutiny.
Many Utility companies are still at a very nascent stage and engage in multiple rounds of discussions with technology services vendors and only a handful are directly interacting with product companies like Amazon, Google, to pilot these systems in real environments. One of the critical challenges these vendors face is to educate the Utility Management on carving out the boundaries for conversational AI, to quick move from POC’s stage. They want to create short term wins to help increase management confidence and garner acceptance for widescale implementation across diverse areas.
Some best practices to tackle this challenge is -
- Set up-front the context of Conversational AI to align everyone to the same definition
- Carve out its boundaries within the enterprise ecosystem in the first meeting itself
- Bust popular management myths around ‘Super Intelligence’ through good examples of advanced conversational AI usage across industries
- Briefly help them to appreciate how it is interdependent on underlying frameworks, and the possibilities will evolve with platform maturity
Once we set this stage, then we can follow-up with business understanding sessions in identification of a pilot use case. This approach reduces risk of longer turnaround time for seeking approvals to start pilots.
The next stage after successful pilots is to lay a foundation to incorporate a self-learning mechanism so that the chatbot gradually becomes more intelligent with each conversation. (More on this in a new article)
Key Take Away
Till date, the advantages of working under regulatory safety net has created a monopolistic culture for E&U companies to allow a slow pace for CX transformation. But now have they understood the need for faster time to reinvent themselves in becoming ‘customer obsessed’ enterprises. Conversational AI is one such potential technology to aid them for this cause.
Through this journey, Energy & Utility companies can break the grounds of stereotypic perceptions from the minds of the people and communities, where they serve and truly adapt to align with the evolving digital landscape, meeting the expectations of their future Prosumers.
Title image Credits - Photo by Bence Boros on Unsplash