Speaking of Disruption: How Messaging and AI will Disrupt the Contact Center
Evolving customer preferences, powerful new messaging platforms, and AI-driven technologies are fundamentally altering how contact centers interact with digital channels. Organizations must react to this shift by focusing on their data strategy, and ensuring that contact center teams integrate seamlessly with their digital partners. Failing to do so puts brands at a strategic disadvantage against competitors as well as new entrants, creating risk of disruption. This article will explore the roots of the coming shift and recommend steps on how to prepare based on practical insights gleaned from lessons learned in implementation.
Messaging Platforms are exploding
Chat platforms such as Facebook Messenger or iMessage are evolving to become a primary touchpoint for customers and brands. Trend data illustrates just how much users like messaging; key metrics like Monthly Active Users (MAUs) of major platforms such as WhatsApp and WeChat have been growing rapidly for more than five years . Moreover, tech leaders, including Apple, Facebook and Google are creating the next generation of messaging apps. These platforms work across devices and support rich functionality, such as the ability to browse a catalog, purchase tickets, or call data from an app or website.
The implications are significant: imagine a customer journey that is driven by a conversation, moves across devices, and lets users complete tasks without leaving their preferred messaging tool. Brands must move from an omnichannel mentality to an ecosystem-driven approach, where events in one place trigger personalized outcomes in another. Consider how brands such as Spotify or Amazon customize millions of experiences , and now imagine contact centers tying these unique digital experiences together.
Evolving customer preferences, powerful new messaging platforms, and AI-driven technologies are fundamentally altering how contact centers interact with digital channels
To do this, traditional barriers must be broken down; brands need to move from “phone or chat or app” to “phone and chat and app” where devices can be used together, or in no particular order. Reps will have to be able to quickly surmise what a user did last on another platform, what they need now, and what they’ll do next. This requires deep familiarity with digital offerings and customer behaviors, and a fundamental change in how brands engage users.
• While there is no silver bullet to address the challenges inherent in this shift, organizational changes can provide good workarounds.
• Ensure that digital product managers and contact center leads work together to design user journeys and overall digital strategy.
• Encourage collaboration between reps and engineers when designing features.
• Explore a holistic approach that ties together contact center and digital channels through conversational interfaces.
AI will accelerate the evolution of the Contact Center
The aforementioned steps will help contact centers mesh with digital platforms and prepare for rapid change; however, it’s not enough. If the messaging trend continues along its current trajectory, brands must find ways to automate the bulk of customer journeys, or risk either overwhelming existing contact centers that become prohibitively expensive to run. Artificial Intelligence, specifically Natural Language Processing (NLP), will make this feasible for brands that start preparing now.
Though NLP has been around for years, only recently has it become more powerful, as computers become more adroit at understanding speech patterns and tying words together. NLP uses machine learning and large quantities of voice data to understand what people are saying, and offer up relevant responses.
Although speech technologies are improving almost exponentially , NLP is only as good as your data. It is crucial that organizations audit, organize, and clean their speech transcripts before embarking on any heavy lifting with speech driven UI. Voice data can be hard to get and poorly captured, leading to roadblocks that are hard to fix down the road. For example, data from traditional contact center Interactive Voice Response (IVR)systems are frequently hard to use as training data, due to how it’s captured. Understand what information the organization has, determine the costs to retrieve it, and identify which data you can use to create dynamically run speech interfaces. Preparing for NLP-driven experiences is dependent upon, and essential to, a solid plan of data capture, retention, and analysis by contact centers.
New Behaviors, New Tech, New Opportunities:
Users love messaging, and the big tech firms are fueling changes to continue the aggressive growth of these platforms. As new tools come to market which empower brands to talk with customers and serve up individualized experiences, it is incumbent upon organizations to prepare. The CIO must be proactive in exploring what this future vision looks like, making organizational changes to spur growth, and tirelessly capture, clean, and curate data to ensure the best experience possible for customers.