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Forward-thinking C-suites know how vital data is to understanding a problem and designing a solution. That’s why increasing numbers of CEOs, COOs and CIOs are adopting data-driven approaches to internal operations, marketing, sales, and above all, customer service. Find out how data can help to deliver the ultimate customer experience through personalized, efficient, and convenient customer journeys.
The growing importance of artificial intelligence (AI) and real-time data analytics is indisputable. Organizations across all sectors are investing vast amounts of money and resources into developing technology to gather and store data and strategies to optimize it. Clearly, an awareness of the value in leveraging data to deliver enhanced customer experience (CX) is at the top of companies’ to-do lists.
The benefits from proper data usage touch on every aspect of an organization and possibilities that derive from a data-driven approach are significant. As Forrester argues in The Data Management Playbook for 2020, “[y]our business is only as fast as your data. What you know – and how well you use that knowledge – fuels your competitiveness and growth.”
All AI-based solutions, whether conversational agents (chatbots or voicebots) or other cutting-edge programs, need data. Why? Because training advanced software means feeding it with data, which develops a familiarization with language and processes and leads to comprehension and autonomy. The more data entered into an AI-powered program, the more capabilities it has. Once effectively taught, it can then be deployed in data collection and storage, either through direct interaction with customers or as part of augmented support of a live agent.
AI empowers data analytics’ capacities as data analytics increases AI’s capabilities. The success of one is based on the success of the other and their functions, if not interchangeable, are inherently connected. AI’s growing capabilities in handling customer service is only made possible through data. AI is the way forward, with Gartner predicting that “by 2022, 70% of customer interaction will involve emerging technologies such as machine learning (ML) applications, chatbots and mobile messaging, up from 15% in 2018.”
The biggest change that forward-thinking organizations need to implement is not technological but operational, in that data, working for and with AI, must be placed at the center of the business model. Investing in technology is important, but establishing a data factory staffed with qualified data engineers and analysts capable of driving the collection and use of data within the company is vital.
Eliminating silos within an organization means educating staff on the necessity of sharing data through an open culture and encouraging the business and data sides of operations to coordinate efforts, align visions, and achieve goals. Firms that synchronize business operations and CX while adopting a data-driven approach will enjoy greater benefits, according to an informative study produced by Capgemini.
Fully integrating AI and data analytics into an organization’s ethos and operations has a transformative impact, in particular with regard to customer relations. Beyond increased efficiency through automation and augmenting agents with tools that ensure better performance, AI and data analytics meet the expectations of the most important feature customers want: personalization. Understanding customers’ needs, wants, and perspectives is the only way to deliver rewarding service.
Modern consumers desire meaningful relationships with brands, and, used to the ease of communication in their personal lives, demand the same effortless connection with companies. Conversations with friends may start on a social platform, move to a text, and end on a phone call. Throughout the various channels, the conversations continued seamlessly. Consumers expect brands to provide the same smooth journey, which can only be accomplished through sharing and utilizing data.
All present and future challenges, whether reducing costs, increasing personalization, automation, AI implementation are connected to data. Making informed decisions and devising forward-thinking strategies depends on analyzing data.
Becoming a data-driven company that harnesses the power of AI is easier said than done. In adopting this approach, what pitfalls can C-suites avoid, and which strategies are the most advisable? The success we’ve experienced at Odigo gives us the confidence to share our observations, insights, and tips in putting AI and data analytics at the heart of your organization.
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