Delivering the next wave of customer experience with a winning AI technology strategy

Customer experience is a key differentiator for all brands, and one that is increasingly becoming a priority for housing organisations too.

Consumers expect their interactions with brands to be ever more instant, personalised and responsive. Delivering against the sky-high expectations set by brands like Google, Apple and Amazon can be a challenge, though, particularly when resources are stretched.

Many brands are turning to automation via artificial intelligence (AI) to bridge the gap. But how does this work in reality – and is the dream of delivering better experience and achieving cost efficiencies a realistic one for housing associations?

Is the future voice-based, and how do we get there?

Conversational AI is set to change every aspect of when, where and how you engage and communicate with your customers.

Deployed across your business, conversational AI has the potential to allow seamless, synchronous conversations with consumers across whatever channel they happen to be using at the time, no matter where they are. Those conversations could be a short one-off request, or form part of a longer-running customer engagement.

The benefits of conversational AI could be transformational – according to Accenture, it could reduce time spent on low-end, repetitive tasks by as much as 20%. The flexibility of a conversational interface could also have lasting impact on customer experience and satisfaction, as well as offering increased accessibility for tenants with disabilities or who lack digital skills.

So how do housing associations prepare themselves to take advantage of AI technologies?

AI technologies and their applications

When discussing automation via artificial intelligence, it’s important to understand the difference between the types of AI technology currently in use. There are two distinct types of artificial intelligence bots, each with their own potential benefits:

Chatbots

These are probably the most easily-recognisable type of artificial intelligence. A chatbot understands and simulates human conversation, and execute business tasks based on a user’s intent expressed through a conversational interface (via “chat”, whether that’s typed in a messenger-style format or via a spoken interface like Amazon Alexa).

At a simple level, chatbots are used to provide predefined answers to common questions. More advanced chatbots incorporate natural language processing (NLP) and AI technologies to simulate human conversations, perform automated business tasks, and learn from their environment and previous experiences to become smarter over time. This makes them a useful tool for human interactions, as they’re able to learn and adapt to different inputs, handle complexity and provide more relevant responses over time.

For example – a simple chatbot could be implemented on a website and provide canned responses to questions about topics like office opening hours or payment methods. A more advanced chatbot could provide more personalised responses based on information stored on particular users, for example their account status or activity levels. This would allow the chatbot to provide a more relevant response based on the individual user’s circumstances.

Robot Process Automation (RPA)

This type of artificial intelligence is not conversational. Instead of taking data and instructions from a conversation interface, a RPA bot extracts data from documents, files, forms, browsers or other data sources to automate common business tasks.

RPA bots are useful for performing repetitive tasks quickly, efficiently and with minimal input from teams, reducing admin loads. Their processes are more rigid than chatbots, with less flexibility to learn and adjust their outputs, so they’re more suited to carrying out standardised tasks and streamlining workflows.

For example, an RPA bot might be used to automatically review repair requests via a form and create job requests with the appropriate team.

Unleashing potential by combining AI technologies

The real business benefits come from combining chatbots with RPA bots in a process known as bot orchestration. By giving a chatbot the ability to delegate tasks to a variety of RPA bots, it’s possible to make a conversational AI capable of executing a wide variety of business tasks. The key difference between orchestration and RPA bots working alone is that tasks can be completed not just on a schedule or in response to a predefined trigger, but based on a user’s need expressed through a chat.

In bot orchestration, a chatbot can hand off a variety of tasks to other bots, completing multiple tasks off a single request, assessing the output and gathering further input from the user to guide the process as necessary. This combined approach makes conversational AI much faster and more versatile than relying on RPA bots alone.

An orchestrated approach could intelligently deliver an entire workflow without any need for human intervention. For example, a tenant could request a repair via a chatbot, which would ask questions to understand the nature of the problem. The chatbot could then deploy RPA bots to check the availability of repair teams, suggest possible repair dates to the tenant, and book in the repair once a suitable time has been confirmed, providing all the necessary details to the repair team.

MRI Software’s work with Converse360 – and how you can get involved

At MRI, we’re making exciting steps to help housing organisations get the most out of artificial intelligence technology. Our vision is to provide the infrastructure to deploy conversational AI that integrates with MRI’s central data, fuelling highly relevant conversations and integrating with all MRI modules to automate tasks based on conversational input from both teams and tenants.

To help realise this vision, we are working with customer experience technology specialists Converse360 to start the process, initially integrating conversational AI into our Digital Self Service offering.

We’re very excited to explore the potential to offer chat interfaces as a new communication method for tenants, and will be demonstrating some early iterations at the Housing Technology 2020 Conference to show the potential impact of artificial intelligence on housing associations and tenants alike.

As part of this work, we’re keen to discuss potential product development opportunities with current and potential MRI customers. All of our service development is based on close partnerships with housing organisations to fully understand their needs, and our work with artificial intelligence is no exception. If you’d like to discuss possible opportunities for your organisation, we’d be delighted to speak to you at Housing Technology 2020, or alternatively please contact us directly.

Client Spotlight

Case study | East Suffolk Council Boosts Tenant Engagement with MRI Digital Self-Service

Providing essential services for residents across the East Suffolk area, East Suffolk Council manages over 4,500 social housing properties, including 12 retired living schemes. The team at East Suffolk Council aim to become the best in class for soci…

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