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Suman Reddy

Suman Reddy is managing director of Pegasystems in India. Pegasystems Inc. is a Nasdaq listed company that develops agile and strategic applications for sales, marketing, service and operations.

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Why AI is the Secret Force Behind Real-Time Customer Engagement

An Australian telco, Telstra, deployed AI in its customer service practices, resulting in a 30 percent reduction in customer complaints, and improving customer service advocacy by a 180 percent.

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If you’ve followed the media lately, it’s no secret that the hype around AI is off the charts. The technology has evolved to the point where businesses are increasingly deploying it to gain better insights into customer needs and provide more personalized service, sales, and marketing. A recent IDC report predicts business revenues will boost $1.1 trillion over the next four years due to improvements in customer experiences with artificial intelligence.

The promise of AI brings the opportunity to move from one-to-many customer relationship management (CRM) to one-to-one engagement along the entire customer journey, powered by big data analytics, machine learning, and CRM. These systems converge colossal data feeds, distilling and analysing trends to predict how the customer might interact with the organization. Marketers can use the power of AI to uncover customer-brand interaction patterns and identify opportunities to satisfy unmet customer needs. AI derives insights from all customer interaction points to help brands convert sales at the moment of truth (customers’ engagement at peak) to drive more impactful customer engagement.

Real-time insights driving real-time engagement

Brands intent on improving the client experience now need to cut through the noise. It is hard to find any technology vendor today who is not touting the AI capabilities of their products and services. At a time when many executives are looking for new ways to boost customer engagement, it’s important to think critically about how AI can actually solve a business’s particular challenges.

Organizations must figure out apt AI-based tools that will provide real value to achieve real results. But while it’s important for brands to understand the potential AI can bring to their organization, it’s more important to first analyze how they are engaging with customers today and where they want to go in the future. Only then, can they understand how AI can help them optimize this engagement.

For example, are organizations trying to move from marketing campaigns blasted out to broad population segments to personalized campaigns targeted to the individual? Are customer support agents bombarded with analytics data with few actionable insights when they should be equipped with guided intelligence to help them satisfy every customer? In these cases, and more, many companies large and small are using the practical power of AI to engage with customers based on their individual needs and actions.

Staying ahead of the customer journey is proving essential for organizations in an increasingly digital world. With increasingly competitive markets combined with shifting consumer needs, organizations need to be entirely in tune with their customers’ needs in real time. With every customer action – be it a website click, an opening of an email offer, or a product purchase  – an AI-powered engagement platform continually adjusts and learns in real time so it can predict their next move and meet them in stride.

For example, Australian telecommunications provider Telstra deployed artificial intelligence and self-learning algorithms into its customer service practices, resulting in a 30 percent reduction in customer complaints, and improving customer service advocacy by a whopping 180 percent. While automated workflows removed enormous routine workload from the agents, the self-learning algorithms also analysed and predicted potential hiccups in the customer-brand relationship. The software suggests the most relevant offers for agents to make to each individual customer. By combining the power of AI with service agents, this also helps  the agents focus their time  on the most valuable actions likely to lead to the most desirable result – be it customer retention or acquisition.  All of this really needs to be an ongoing process, where the systems only get better, learns as it goes, and provides more impactful results.

The business imperative to keep pace with centralized decisioning

While the Internet of Things (IoT) has empowered enterprises to access a vast array of user data and engage with consumers across platforms, many enterprises still fall short of meeting their expectations – in part due to disparate systems of intelligence. Businesses are in a way drowning in data and can’t make meaningful connections between the analytics and the actions they should take based on the data.  An intelligent, centralized decision system can produce relevant, suggested actions to take in real-time with customers, while making sure that decision management is unified consistently and coherently across all channels – from online, chat, voice and beyond.  

Sure, AI has a “cool” factor that has many fantasizing about the science fiction like scenarios that may someday become real. And of course, AI already is immersed in many aspects of our lives, from smarter phones to smarter dwellings – offering hints of the collective promise of the future of AI. But, to stay competitive, organizations should be implementing the right AI solutions that can demonstrate real value for them today in a more practical way.  If you can cut through all the hype, you can find these AI solutions dramatically improving businesses right now across many industries. These systems leverage customer data, finds insights, and puts them into action - returning significant value for customer engagement and bringing customers back for more.

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house

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