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Artificial Intelligence and Machine Learning Will Drive Customer Relationships in Future

Artificial Intelligence

The idea that artificial intelligence (AI) and machine learning (ML) will become key enablers for leveraging the huge volumes of data that organisations now hold on their customers is not a new one.

In time, many believe that these technologies will form the basis for managing all customer relationships and for enhancing customer value. For example, Gartner predicts that more than 85 per cent of all customer interactions will be managed without human involvement by 2020. Will Gartner´s prediction be right? Nevertheless, it’s a question of ‘when’, not ‘if’.

AI refers to the capability of a machine to learn and mimic human behaviour – for example, speech recognition, speech to text, speech analytics and decision making – while machine learning is a subset of AI that uses algorithms to enable machines to learn and improve from experience automatically, without external programming.

Many organisations have been investing in data analytics for some years, collecting large amounts of information on customers and customer interactions, which holds a tremendous amount of value.

The challenge, however, is how to unlock that value and use the data intelligently to provide rich insights into customer behaviour and to predict future behaviours. Data processing needs to be automated, so that organisations can more quickly obtain insights. This is where artificial intelligence, machine learning and speech analytics come in.

Any AI programme requires a rich source of data, or a “data lake” from which the ML algorithm can evolve. In the context of Touch Call Recording, this data is obtained from the conversations that take place between your employees and your customers – mobile, fixed, SMS, Chat, and so on – which are recorded and stored. These communications then provide the source material for highly valuable insights.

Text to speech and speech analytics provide ways to interrogate data sources and isolate keywords from mobile and fixed line voice calls, while metadata reveals who called, at what time and how often. When combined, these recordings provide a rich data lake that can enable organisations to extract more and more value from the data contained in their daily interactions with customers.

Any organisation that records its voice and digital interactions – whether for compliance, training or business purposes – has a rich source of data at its fingertips. Advanced speech to text and speech analytics capabilities can then be applied to extract the data from any voice or data communication, enabling organisations to gain valuable insight, and optimise future customer interactions and campaigns.

So it's important to think about how you might make more use of digital recordings (across all channels) when thinking about implementing AI programmes in future. Choosing the right recording partner that is aligned with strategic AI programmes and that can provide data in the right format for your algorithms is therefore essential.

Touch Call Recording ensures that all conversations are captured, across every channel, so it provides a ready-made solution to ensure that you can create a rich data lake as you implement new AI and ML programmes for speech and data analytics.

In conclusion, AI and ML, in combination with speech to text and speech analytics, have the potential to unlock new insights, as well as predict future customer behaviours. We're all just starting out on this journey, but Touch can help. If you want to know more and are thinking about implementing AI programmes, then Get in touch and find out how we can help you to harness and unlock the value in your daily communications.

Written on 16 January 2019
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