6 Areas AI Will Disrupt Customer-Facing Industries by 2020

There is hardly an industry left that has not been disrupted by digital transformation trends.

Recent advances in artificial intelligence and deep learning are taking that transformation to the next level. Major players in the global market are investing in software that can learn on the basis of processed data and transform itself into an efficient tool.

In this article, we take a closer look at the current technological disruption resulting from AI and deep learning in customer-facing sectors to see how they will be transformed by these technologies in the near future.

Leaders in Digital Transformation

Gathering a wealth of consumer data, customer-facing sectors such as retail, hospitality, and transportation are in the unique position of leading other industries in digital transformation.

That is especially relevant to the Middle East and Africa region where the segment of digital consumers is rapidly rising and businesses are rushing to match them. In 2017, the Middle East was ranked as the top destination for quickest digital growth.

These sectors, today occupying both online and offline spaces, have recently adopted many cutting-edge digital transformation tools both regarding software and hardware. They are also considered as the early adopters of digital customer insights that derive from implementing of artificial intelligence. And that shouldn’t come as a surprise - the majority of critical trends for these sectors is closely connected with the development of solutions that support digital transformation. 

Why AI and Deep Learning?

Organizations in customer-facing sectors can significantly benefit from solutions that help to combine online and offline insights. But to make the most of such technologies, they should link modern digital transformation trends such as business analytics, big data, and customer insights, with innovative AI applications. The combination allows delivering faster and smarter product innovations, optimize their operations, and boost customer engagement in both real-time and long-term perspective of the customer lifecycle.

 Thanks to AI-powered solutions, organizations will:

•       Gain access to transformative insights,

•       Improve automation of manual and time-consuming processes,

•       Remove technical barriers to enjoy all the benefits of digital transformation.

In the near future, we will witness the convergence of in-store and online shopping experiences as organizations in these sectors focus on bringing a seamless digital experience to their customers.

 Here are 6 areas AI and deep learning will disrupt by 2020 

1. Predictive Analytics and Customer Outcomes

Modern digital tools allow brands to engage their customers in real time, positioning that type of marketing interactions as the new standard. However, an increasing number of organizations are not only concerned with acquiring data that accounts for current customer behavior but also predicting its outcome in the future.

Predictive analytics powered by AI and deep learning offers insights of unprecedented precision and scale. Technological solutions used by companies to gather information about customer interactions are beginning to implement AI components to generate actionable insights that enable short- and long-term planning.

 Here’s how other brands implement it: The professional soccer association of Spain, LaLiga, uses Microsoft Azure AI and predictive analytics features to deliver personalized content fans are looking for. The organization plans to use these cognitive capabilities to track the behavior and preferences of their target audiences as well. For example, by better forecasting the demand for specific online content, LaLiga can evaluate new services before they’re introduced, creating new revenue streams with top efficiency and guaranteed ROI.

2. Interactive AI Chatbots

 Another AI solution gaining traction in consumer-facing sectors is virtual assistants or chatbot solutions.

 Chatbots use machine learning algorithms to interact with humans using natural language and:

•       Help customers navigate simple tasks without the need to involve a human agent,

•       Respond to requests that have been filtered out as not requiring human interaction at first,

•       Escalate the request to a human agent only when needed, helping agents avoid answering every single customer request and allowing them to focus on more complex problems,

•       Allow delivering instant customer service and building customer loyalty,

•       Prove a better experience - especially crucial for companies that operate in these interaction-intensive industries.

Have a look at this Forbes infographic to see how chatbots will transform customer experience in the near future.

Success story#1: A Microsoft customer, the electronics retailer Dixons Carphone, developed better customer engagement by offering personalized and differentiated service with the help of AI-driven solutions. The organization implemented Microsoft Cognitive Services in the context of customer interactions to create a bot that assists customers in searching for products online. By gathering data about the criteria they used, the bot enables human staff to pull up that information and present the customer with highly relevant offers. Thanks to the bot, Dixons Carphone has access to valuable business intelligence about the products customers are looking at, the sentiment of their interactions, and the questions they ask.

Success story#2: The retailer Macy’s optimized the shopping experience on its website by introducing a virtual agent based on the Microsoft Dynamics 365 AI solution for customer service. The virtual agent solves customer issues and transfers customers seamlessly to a human agent when necessary. Macy’s uses the system’s dashboard to monitor performance and gain insight into customer behavior on the website - that enables the retailer to make instant adjustments and improve customer experience as quickly as possible.

Chatbots will allow retailers to track, analyze and visualize customer data to better identify consumer preferences and deliver highly relevant, personalized experience. Experts predict that AI tools will soon be able to react with emotional intelligence that rivals human capabilities.

3. Combining Online and Offline Customer Engagements

AI solutions can track customer behaviors not only online (for example, in e-commerce stores), but also offline thanks to technologies like the beacon, which allows for physical analytics in public spaces such as airports or malls. Gathering that type of business intelligence will enable brands to better personalize messages as well as gain a more holistic view of the full customer lifecycle.

Marketers are currently using solutions that leverage AI and deep learning in display advertising to present consumers with more relevant product recommendations and increase the ROI of personalized retargeting

By analyzing the habits, behavior, purchasing history of consumers, and many other metrics, these solutions create mathematical models that can derive more reliable and rich descriptions of customer preferences to be used for more precise targeting.

Here’s how other brands implement it: Nordstrom Rack installed in-store beacon technology built on the Microsoft Cloud to engage customers, personalize shoppers’ experiences, and increase speed and convenience. Beacons also gather data to improve the service further, direct shoppers to available fitting rooms and show extended product offerings available online while they’re shopping in-store.

4. Fraud Detection

AI and deep learning solutions are commonly used to track customers with loyalty in mind. However, these solutions are not only implemented to top-line growth points and can be used to monitor fraudsters as well. Companies can use AI and deep learning to secure their bottom lines and ensure that they are adequately protected against fraud and compliance with regulations.

 AI-driven solutions are currently used in hospitality and transportation to prevent customers from booking flights with stolen credit cards or reselling their bookings.

Here’s how other brands implement it: Contidis is building the new Candando superstore chain in Angola and uses Microsoft solutions to get faster, more in-depth insight into critical financial and operational data. The reports and alerts help boost customer service and uncover fraud, inventory errors, and the effects of store promotions on revenue. 

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