ChatGPT and GPT-4 have taken the world by storm and despite AI still coming off the hype curve, many business leaders are feeling the market pressure to adopt the latest tech to remain competitive.
However, the success of any AI-based solution relies on one thing: data. As Forrester reports, “your business is only as fast as your data. What you know – and how well you use that knowledge – fuels your competitiveness and growth.”.
Training advanced software requires huge amounts of data, which in turn develops a familiarisation with language and processes and leads to understanding and autonomy. The more data entered into an AI-powered programme, the greater its capabilities. However, often the data needed to train AI algorithms is siloed across myriad places in a business, reducing its helpfulness to those who want to benefit from the latest generative AI and natural language processing (NLP). To scale the mountain of potential, breaking down data siloes is the natural first step.
The danger of data siloes
Imagine a world where customers ring their favourite brand and are routed instantly to an agent who can, based on multiple data points such as matched personality or preferred region, take the quality and personalisation of that phone call to a completely new level. This doesn’t seem that unattainable, especially as all this data already exists.
However, the volume of data that flows through a contact centre at any given moment is immense, making it very challenging to use it to its full potential. Often, this data sits, siloed, in multiple databases and platforms with little to no integration, rendering it unhelpful in today’s digitally competitive customer environment.
Given AI’s growing capabilities for handling customer service are only made possible through data, the risk of not breaking down internal data siloes is sizeable, not just in terms of missing opportunities. Companies could also see a decline in the speed and quality of their customer service as contact centre agents need to spend longer navigating multiple platforms and dashboards to find the information needed to help answer customers’ queries.
Breaking down barriers requires a culture shift
Eliminating data siloes requires educating everyone in the business to understand the necessity of sharing data through an open culture and encouraging the data sides of operations to co-ordinate efforts, align visions and achieve goals. The synchronisation of business operations with customer experience, alongside adopting a data-driven approach, can produce significant benefits such as increased customer spending. Indeed, Capgemini found 81% of customers are willing to pay more for an enhanced customer experience.
The biggest change for forward-thinking businesses here isn’t technological, it’s operational. Data, working for and with AI, must be placed at the centre of the business model. This means getting board buy-in to establish a data factory run by qualified data engineers and analysts who are capable of driving the collection and use of data within the organisation.
Supercharge growth with AI and data analytics
Once data siloes are no more, organisations can benefit from the truly transformative impact of integrating AI and data analytics, especially when it comes to customer relations. Beyond increased efficiency, provided through augmenting agents with automation tools which create better performance, AI and data analytics enable companies to meet customers’ growing expectations for personalisation. As understanding customers’ needs, wants and perspectives is the only way to deliver rewarding service in today’s heavily personalised society.
Consumers now expect brands to provide the same effortless connection they experience in their personal lives. A conversation with a family member might start on a social platform, move to text and end with a phone call. As they move from channel to channel, the conversation continues seamlessly. Providing this seamlessness in a business setting can only be done through better sharing and utilisation of data.
Solving today and tomorrow’s problems – whether increasing customer personalisation, reducing costs, or harnessing the latest ChatGPT release – all depend on analysing data. However, becoming a data-driven company which can harness the power of AI is easier said than done. But by breaking down data siloes internally and establishing a collaborative culture, businesses can put themselves in the best position to supercharge growth and opportunities.
About the Author
Stuart Clarke is Head of Business Development at Odigo. Odigo provides Contact Center as a Service (CCaaS) solutions that facilitate communication between large organizations and individuals thanks to a global omnichannel management solution. Thanks to its innovative approach based on empathy and technology, Odigo enables brands to connect with the crucial human element of interaction while also taking full advantage of digital possibilities. A pioneer in the customer experience (CX) market, the company caters to the needs of more than 250 large enterprise clients in over 100 countries.
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