How Businesses Can Harness the Power of AI to Drive Customer Experience and Loyalty


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To understand how organizations can harness the power of AI to drive customer experience and loyalty, it’s important to acknowledge the #1 business trend that’s currently disrupting the nature of customer experience and loyalty as we’ve known them: digital transformation.

With brands investing in new digital channels as a result of the COVID-19 pandemic, increasingly today’s customer experience is a digital and omnichannel experience.Business leaders are recognizing that gathering customer feedback via traditional surveys is only one step of capturing the voice of the customer.

Gaining a clear picture of the new customer journey is now a much more complex and multifaceted process. More and more companies are realizing they have other key customer signals — implicit behavioral data — that they must collect, analyze, learn from, and leverage to drive customer experiences and loyalty.

Contact center conversations — which increased by up to 800% due to the pandemic — can shed light on agent performance, customer sentiment, employee training opportunities, potential product and service innovations, and more. Digital behavior can be an indication of points of frustration and churn across brands’ websites and apps. Social media interactions, reviews, and conversations can help brands pinpoint opportunities for improvement and what they’re getting right.

At the same time, savvy executives have come to one other important conclusion. It’s simply not humanly possible to analyze, gain insights from, and respond to the massive amounts of structured and unstructured data that’s being generated at every single touchpoint across the entire customer journey in real time at scale without AI.

Analyzing all of these inputs is, in fact, the ideal scenario for AI to be implemented. AI powered by deep machine learning algorithms is purpose built for this very business use case and can help organizations understand, organize, and change experiences in real time to solve the challenge of driving loyalty in this new era of digital transformation.

The steps businesses should take to prioritize improvements that will have the greatest impact on customer experience

While many brands use AI to look backwards and analyze what has happened, forward-thinking organizations must use AI to predict and prioritize what might yet happen and suggest next best actions moving forward, by taking these four key steps.

Step 1: Collecting customer signals across channels, including solicited feedback (like surveys) and unsolicited feedback like social media reviews, call and chat logs, digital engagement and behavior on digital channels, apps, websites, and more.

Step 2: Organizing and understanding customer experience data in a way that makes sense, uncovering sentiment — including customers’ positive and negative feelings, emotions, and perceptions — and trending topics that are of the greatest concern to the business.

Step 3: Prioritizing addressing factors that are having the greatest negative impact on business by looking at keywords that are negatively impacting customer sentiment and NPS®.

Step 4: Predicting outcomes and prescribing solutions: Creating predictive models that work at the:
Systematic, overall customer level to have positive impact on overall business, including on an organization’s financial bottom line.
1:1 customer level to personalize individual customer interactions using lookalike audiences.

Businesses can and should personalize customer interactions for better outcomes

Successful businesses don’t think in channels. They understand that the entire customer experience should be customized based on individual interactions and, as a result, work to deliver personalized offers, products, and services across digital and human touchpoints and interactions and equip their contact center and other customer-facing teams with the insights needed to understand the up-to-the-moment customer journey, such individuals’ transaction histories and interactions with customer service agents and digital properties, to drive positive outcomes.

If you have all of your key customer data — from social and digital to contact center and in-person interactions — then you have the intelligence necessary for personalizing every interaction, every channel, and every touchpoint across the entire customer journey. And this should happen right from the start. From the very first interaction, point of sales, or acquisition, and throughout the customer lifecycle, brands should be continuously listening to customer signals using AI and ML and adapting as customer needs change.

Without a machine learning backbone, siloed and disconnected data will make it impossible to understand the customer and enable this kind of 1:1 personalization. Individual teams may be able to optimize their respective channels, but may lack clear insight into what’s happening across other channels.

Solving for this challenge requires ensuring connections between all of the systems that touch the customer experience and journey, so that brands can truly understand customers across every touchpoint and personalize interactions everywhere.

Businesses should operate in real-time, and voice and video tools can help

Organizations that fail to understand and respond to customer experience signals in real time simply won’t be able to compete when it comes to increase of customer wallet share, retention, and loyalty.

By using innovations in AI-powered voice analytics, companies have access to real-time analysis of phone conversations, which can help to train and prompt contact center agents in real time to improve customer interactions as they’re happening. Similarly, digital behavior analytics are helping brands deploy tools like live chat when it appears like customers are frustrated, in distress, or likely to churn. As an example, by using AI, hotels may unlock insights about how the type of pillows, coffee, or toilet paper they are offering guests is causing a spike in customer experience complaints. Or retail brands may detect that their returns process is driving customers away.

Some companies are using video feedback tools as an alternative to surveys to get a clear picture of the experience for hotel guests, patients, restaurant customers, and more. Rich media like video can be incredibly powerful compared to traditional text-based feedback, as video allows brands to conduct facial, emotional, tone, and sentiment analysis. Some are even using video to conduct object analysis, or real-time market research, to understand what products and items consumers are using in their daily lives — such as what brands they’re wearing or otherwise consuming — as captured as part of the videos they submit.

Intervening in the moment when it matters the most enables brands to step in and offer personalized help and attention right when customers need it. Businesses that get this right can expect to see gains in service recovery, customer retention, share of wallet, and customer satisfaction.


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