Important Ways AI and ML Improve Customer Experience Strategy

The modern retail industry never really sleeps. After a demanding back-to-school season, retailers are now quickly shifting gears to lock in their holiday strategies for this year.

The holiday season is typically the harvest season for many online and offline businesses around the globe. Be it the beautiful red and gold decorations, delicious food, or gifts, people visit their favorite stores to spread the holiday cheer every year.

Already hindered by fears over supply chain disruptions and longer waiting times, this year's holiday season will be one of the most daunting the industry has ever seen. And with that, brands are finding better ways to deliver a seamless experience to the customers. AI and ML are proving to be the key assets in bridging those gaps in retail.

Importance of AI and ML in Delivering Personalized Customer Experiences

There's no denying that AI and ML will play a significant role in improving the customer experience in the coming years. 80% of the marketing leaders are already leveraging artificial intelligence to drive better CX.

Better customer experience leads to improved customer satisfaction, loyalty, and advocacy. With traffic predicted to shoot up exponentially in the holiday season, e-commerce businesses need to be prepared for the massive online wave. This needs businesses to aggressively discover patterns across different data points to deliver a consistent experience across all channels.

This is where AI and ML become so vital to manage customer experience and deliver rich shopping experiences across all online mediums.

How Can AI and ML Enhance Customer Experience in This Holiday Season?

Technology is developing rapidly, with AI and ML taking the reins. It has already helped in ushering a massive industry evolution across the world. For example, starting from automated cash registers to the next level of security authentications, AI & ML have changed how online shopping works while delivering a better customer experience every time.

AI and ML can help brands guide their target audiences in the right direction by enhancing their journey. Here are some tactical ways in which AI and ML can play a pivotal role in enhancing CX for organizations.

Customer Journey Analysis and Personalization

For any retailer, the first and foremost priority is to drive conversions. Here lies the importance of knowing more about the buyer journey and the characteristics of every customer. However, creating an immersive customer's journey can be quite challenging, given how complex the shopping landscape has become. With AI and data engineering, retailers can extract data from all the touchpoints to develop an integrated and evolving view of the customer to cater to each of them with personalized offerings.

Recommendation Systems for Personalized Gifts and Better Email Holiday Offers

According to Accenture's Pulse Check, 91% of people prefer shopping with brands that provide relevant offers and recommendations. Here, 'relevant' is the keyword as most brands offer discounts and offers during the holiday season but seldom do people fall for them. So, analyzing what customers expect and delivering as per their expectations becomes a significant feature to woo crowds online.

A recent consumer poll by CreditCards.com said that 62% of shoppers wish to make their holiday gift purchases online. This denotes that the modern shopper has become adept in finding the best visibility into prices, offers, and availability for every product. With multiple mediums and interaction points for customers, brands need AI and ML to adapt and inspire customers in real-time. Emails are still the most prominent marketing medium for B2B brands across the globe.

AI enables the automation of customized newsletters for every subscriber with different recommendations. As real data back everything, it's no longer just a prediction but the complete analysis that makes AI and ML so effective.

AI-Powered Ads for Mobile Shopping

Most customers use mobile phones as their preferred devices for shopping. But not all ads are suitable for mobile, and this can create an unpleasant experience for customers. Integrating AI into mobile ads can give a competitive edge since AI can help know customer behaviors and audiences in real-time. This is especially helpful to know what works best and what doesn't. In addition, this will enable retailers to customize their ads for the specific devices and the individuals using them. AI customization has a whole set of different features for retailers to explore the personal preferences of the particular user group, gather important insights, know customer patterns and choices that might take years to recognize.

Dynamic Inventory Maintenance

From next-day delivery to BOPIS, retail brands have done a fantastic job of innovating their operations in much less time, given the disruptions in the last two years. This has led customers to get familiar with the super convenient delivery system. This means the holiday supply chain is set to be even more stressed as brands try to keep up with the delivery norms. Here, AI and advanced computing tools can be of help. For instance, AI can help retailers better oversee their inventory and shipping operations to make sure products are ready to be shipped when needed. In addition to that, AI keeps tabs on the supply chain operations as a whole on behalf of the retailers, enabling them to become more responsive and agile when there's any delay or disruption.

Predictive personalization

Customers who purchase in bulk face challenges while monitoring the inventory levels. However, AI makes the entire process more straightforward with its intelligent reporting and customization. It enables customers to have an improved and tailored experience. Brands can evaluate the inventories of customers and deliver them before they run out of stocks. This is especially useful in saving time and avoiding any mishaps, which makes the entire experience seamless and efficient.

Building Blocks for True Implementation of AI and ML in Customer Experience

AI and ML are meant for more than just personalization. They are intended to nurture prospects into customers at every interaction point through customer journey orchestration. So, it's about optimizing customers' goals and overall experience as per the context. When a brand understands the building blocks of AI and ML, they get empowered to implement technology to engage users at these optimal points in real-time through the most effective channels. Read on to understand more about the primary pillars for the true implementation of AI and ML in CX.

Data Unification

The digital landscape consists of multiple data points and categories. As a result, it can sometimes become overwhelming for marketers to understand what customers want. This calls for technology that employs data unification to serve a single customer view in behavioral analytics. Artificial intelligence is the key in such cases as it thrives on information.

AI and ML together make the complex task of data collection, interpretation, and management easy to visualize, fast and affordable. This is a great ploy for marketers who know valuable data insights for a great CX strategy.

Real-time Insights Delivery

The digital ecosystem is fast-paced. A marketer cannot analyze and manipulate data from diverse sources manually. Even if they do, the information might not be easily accessible to all departments across the enterprise. AI accelerates the analytical process by establishing relevant relationships in large data sets for a clear understanding. These insights are created and shared simultaneously across different departments in real-time.

With AI and ML, brands can connect customer behavior and business outcomes to enable teams across different verticals to collaborate on customer journeys and better manage, measure, and optimize them.

Business Context

No business has similar needs, KPIs, touchpoints, or customer journeys. So, while adapting your tech stack to the customer experience journey, make sure to understand the business context of the solution for optimum value. Whether revenue, profitability, customer lifetime value, or customer satisfaction, awareness of factors that drive business performance should be prioritized.

When AI systems are equipped with a clear strategy, they can explore fallacies in CX strategies and fill the gap with exclusive customer journeys at every step. How the use of these technologies vary from business to business can be seen from the examples of Amdocs and Opun Ltd.

Tune in to Customers' Expectations with AI and ML

According to Servion, 95% of customer interaction channels will be assisted by AI by 2025 Customer expectations have gone up with changing times, and customers need more than just shopping from an e-commerce brand.

Brands need to interact with their customers in a way that makes them feel special. This is not possible manually as the conversion cost would cross the limits but not if AI and ML are employed in the proper manner. A team of humans and the proper use of AI and ML can help brands acquire confidence among customers. It can do this by changing the way a brand interacts with its audience and making it easy for them to make decisions in the following ways.

Empowering Self-service - Chatbots and Virtual Assistants

Chatbots are visible on all e-commerce marketplaces because 1 in every 3 Americans is willing to make purchases via chatbots. Virtual Assistants are great at engaging users even on topics that might need extensive troubleshooting or include noisy conversations. They offer instant availability and accessibility across different platforms with the same finesse. AI self-service options are so close to replicating humans that some virtual assistants have even passed the Turing test.

Delivering Deeper Customer Insights and Personalization

AI and ML algorithms can segment traffic based on customer behavior and recommend products or services at the right moment. With AI and ML, arriving at this moment becomes easy with the help of demographics, user history, and customer interests compared to those of other customers. Predicting behavior to deliver unique, personalized experiences helps brands increase engagement and offer dynamic, one-to-one touchpoints for customers in real-time.

AI personalization helps you scale personalized experiences with machine learning, minimize marketing risks due to flawed decision-making, enhance content relevancy, and optimize ROI and revenues. It also allows marketers to gather deeper customer insights and create strategies to maximize brand appeal.

Time to Leverage AI and ML for better CX in This Holiday Season

Holiday season is never easy for retail brands. Likewise, this year isn't going to be any different. By embracing AI & ML driven approach, brands can successfully address the troubled spots of this holiday season.

Examples of leveraging AI and ML in e-commerce range from product recommendation, personalization, price optimization and image search to virtual assistants, fraud detection, image search and categorization and customer segmentation. As businesses evolve continuously in this new age, it's vital not to remain stagnant or fall behind competitors on any front.

Icreon has enabled multiple clients with AI and ML solutions to act as game-changers in the service and innovation industry and create more innovative, more efficient business outcomes.