Importance of AI and ML in Delivering Personalized Customer Experiences
Customer experience is a competitive driver of growth for ecommerce brands. A sound understanding of customers is an ideal step toward personalized customer experience. Leveraging artificial intelligence (AI) and machine learning (ML) can accelerate it. Marketers, salespeople, support agents and employees in customer-facing roles cannot extract insights from a customer’s entire history in real time. Data insights are one of the most helpful tools to enhance CX on an online portal. The complexity of data sets and impromptu customer behavior is precisely the reason AI and ML are valuable to deliver enriching customer experiences.
Better customer experience leads to improved customer satisfaction, loyalty, and advocacy. With traffic predicted to shoot up exponentially in the holiday season, ecommerce 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?
From lockdowns, store closures, reopening and again lockdowns, 2020 has been full of surprises. The holiday shopping season has been added to this year’s list of unprecedented events. Before 2020, most businesses had a defined marketing strategy for the holiday season. There were only a few strategic changes that marketers had to employ every year. This year it’s different and brands need to evolve the way they engage with customers to stay ahead of a continually uncertain curve. According to Acodez, 30% of global retail sales will be digital in 2020.
AI and ML can help brands guide their target audiences in the right direction by enhancing their journey. Here are some of the tactical ways in which AI and ML can play a pivotal role to enhance CX for organizations.
Reduced Advertising Costs for Better Performance
The first use of Artificial Intelligence in advertising was seen in a 60-second spot, directed by Oscar-winner Kevin Macdonald, for Lexus, the automobile giant in 2018. The script was developed with the help of IBM’s Watson AI system. It analyzed 15 years’ worth of footage, text and audio for Cannes Lions awarded car and luxury brand campaigns to understand what audiences resonate with.
AI and ML empowers tons of data, including measurable impressions, click-through rates, bid levels, demographics, and more to achieve desirable results. This not only saves a lot of time for the marketers but is also cost-effective eventually. Reduced operating capital, time and effort saved on manual reporting, and real time monitoring are some benefits that AI and ML bring to advertising.
Perfect Content at the Right Time
A research by Epsilon indicates that more than 80% of consumers make a purchase when brands offer personalized experiences. More people prefer highly personalized content while shopping. This has made the process of content creation more challenging for marketers. The need to create and deliver the right content at the right time is vital for succeeding in today’s digital marketing landscape.
With AI and ML, marketers can assess the digital footprints of their targeted audience and employ intelligent content strategies in real time to drive better conversions. Even better, it allows nurturing of customers across distinct phases of their journey making shopping a treat for all.
Recommendation Systems for Personalized Gifts and Better Email Holiday Offers
According to Accenture’s Pulse Check, 91% people prefer shopping with brands who provide relevant offers and recommendations. Here, ‘relevant’ is the key word 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 major feature to woo crowds online.
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 automation of customized newsletters for every subscriber with different recommendations. As everything is backed by real data, it’s no longer just a prediction but the complete analysis that makes AI and ML so effective.
Improved Customer Experience
AI and ML are not just about reducing time and effort. It’s also about increasing efficiency. To stay efficient, brands need to keep up with the latest trends in the market. These evolving trends may involve the latest technology, customer expectations or unplanned events like COVID-19. This holiday season, customers will be bombarded with advertisements, offers, deals and what not. Though, are these things what customers primarily want?
With digital at the forefront, ecommerce brands need to market rather than advertise their USP. They also need systems that help them keep up with the changing interests of their users. This is essential to create loyal and recurrent customers that prophesize and recommend a brand to their peers.
Building Blocks for True Implementation of AI and ML in Customer Experience
AI and ML are meant for more than just personalization. They are meant to nurture prospects into customers at every interaction point through customer journey orchestration. So, it’s about optimizing customer’s 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 true implementation of AI and ML in CX.
The digital landscape consists of multiple data points and categories. 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 how valuable data insights can be 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.
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 it is 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.
How AI and ML can Change the Way Customers Interact with A Business
According to Servion, 95% of customer interaction channels will be assisted by AI by 2025. After COVID-19, this seemed to have gained pace even more. With the world moving online for all needs, ecommerce brands have seen a sudden traffic surge. Customer expectations have also gone up with changed times and customers need more than just shopping from an ecommerce brand.
Brands need to interact with their customers in a way that makes them feel special. This is not possible manually as the cost of conversion would cross the limits but not if AI and ML are employed in the right manner. A small team of humans and the right 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 make it easy for them to take decisions in the following ways.
Empowering Self-service - Chatbots and Virtual Assistants
Chatbots are visible on all ecommerce marketplaces because 1 in every 3 Americans are willing to make purchases via chatbots. So, they are helpful and have proven their worth. Now, the world has moved on from using chatbots just as IT helpdesk assistants to AI virtual assistants that drive sales. This is possible due to cognitive computing techniques like Natural Language Processing (NLP), and Natural Language Understanding (NLU) designed to interpret user intent and assist them in real time.
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 to this moment becomes easy with the help of demographics, user history and customer interests as compared to those of other customers. Predicting behavior to deliver unique, personalized experiences helps brand 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, enhanced content relevancy and optimizes 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
The holiday season in 2020 is the best time for businesses to revive the losses incurred after the spread of coronavirus. It is a time when people are online looking to fill their shopping carts with everything, they got on the streets last year. AI and ML together interprets this behavior in statistical form and automates decisions to offer recommendations and take actions.
Examples of leveraging AI and ML in ecommerce 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 from competitors on any front.
Icreon has powered multiple clients with AI and ML to act as game-changers in the service and innovation industry and create smarter, more efficient business outcomes.