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Transforming CX with AI and Machine Learning
Artificial Intelligence is everywhere! It is the evolving world where programs and algorithms are helping transform almost every aspect of a business. From data capturing, filtering, and labeling in an ecommerce store to onboarding talent in a company. Every industry segment leverages technology to cut operational costs and save time internally. However, in a world where technology holds excellent power and returns: customer experience.
Customer experience has emerged as a new brand identity. Today, companies across the globe are experimenting with the latest technologies like artificial intelligence and machine learning to not only improve the customer experience but to own it and stand out from the competition.
30% of customers will stop continuing with a brand or switch a brand due to an unpleasant experience, and 27% of companies say improving their customer intelligence and data optimization are their top priorities regarding customer experience.
That said, intelligent technologies will be more useful in uplifting customer interactions and will be able to deliver transformational customer experiences.
Rise of AI & ML to Back New Brand – Customer Experience
Artificial intelligence and machine learning have been used widely in bringing exceptional results to online shopping. According to a survey by SnapLogic, 61% of companies have been investing in the use of AI to enhance customer experiences through data analytics.
Supporting the statistics, Digital Experience Platforms (DXPs) like Sitecore, Optimizely, and Drupal have also surfaced to offer tailored and connected experiences. The platform combines content and commerce to ramp up conversion rate through personalization and focus on customers.'
Online customers cannot use Amazon or Alibaba without getting personalized recommendations related to their purchasing history, browsing history, and other factors.
This is not limited to online retailers. Many big players, including:
- Amdocs, a leading software company, uses a machine learning and personalization engine - Amdocs Academy, a personalized suite of tools specifically designed and developed to help its large clientele upskill its entire employee base. It comes with Immersive Learning & Language.
- Understanding features to identify training flow using agent response. It also gives an agent a score based on the conversation and suggests suitable learning material.
- Swedish Bank SEB uses a virtual assistant to manage natural language conversations. It assists customers on how to open an account and how to make cross-border payments.
- MetLife also uses an AI-enabled voice analytics software application, which helps call center agents to understand callers' moods
As many companies have already set up AI-enabled programs to keep up with customer expectations, AI and ML will undoubtedly continue to play a vital role in backing this new brand identity in the years to come. Now, let's see how various AI and ML factors play their role in enhancing customer experience:
Data is the Key to Bring Exceptional CX
In the immense realm of customer experience, everything begins with data - Who are your customers? Do they matter to your business? What are their unique traits? What sort of behavior are you getting from them?
Obtaining a complete picture of customers' activities is essential in understanding their needs. What sort of data do you have about them, and how is it valuable and relevant? Algorithms based on AI and ML are increasingly being used in data gathering, processing the fragmented data streams drawn from sensors, apps, and other sources, and cleaning them against the live data.
ML Chatbots – Promising Greater Customer Engagements
Machine learning-based chatbots are gaining traction among businesses to enable greater customer engagement and interaction. Such bots use conversational-based algorithms to serve effective, personalized services to their customers.
For example, Opun Limited, Home Improvement Experts, has built a chatbot system that handles a variety of customer service requests – Bathroom designing queries, Appointment tracking, Issue raising and tracking, Confirm (un)availability and free time, Schedule calendar, do survey and NPS scores, and more -- just like a human does. By leveraging machine learning intelligence (based on the Microsoft bot framework and LUIS), the bot can handle many variations of the same questions.
So, in the snippet below, if you ask the bot, "I need my loft covered," it will identify the requirement and post that will create the order.
Mednections, a doctor referral platform, works on a secured web-based platform for primary care. The portal uses machine learning-based service (Amazon Polly), artificial intelligence, and voice response as the primary technologies to replace human interaction of calling the patients and specialists and then scheduling appointments.
Predictive Behavior Analysis - Real-Time Effective Decisioning With AI
As AI is all about data and analytics, these two factors fundamentally optimize the customer experience. AI allows you to conduct predictive analysis based on customer behaviors. From a technical point of view, predictive behavioral analysis is the ability of artificial intelligence to understand trends in recent data and make an effective decision in real time.
Predictive analysis, also called cognitive decisioning, is one of the most valuable features that assist decision-making with an almost negligible latency rate.
One great example is Precognitive. They offer an AI-based predictive analysis tool that takes around 200 seconds (total response time) to make an effective decision based on real-time data received from the customer. AI recognizes the customer's intent through activities on an online interface. This data then enables businesses that leverage AI to make predictive analyses and personalized decisions to display relevant content on the customer's interface in real-time. This feature can be integrated into your web application with the help of the Application Programming Interface (API).
Again, as AI deals with big data, it performs predictive analysis with a short response time, providing actionable insights that you can work upon to improve your interaction and communication with your customer. Thus, this is how cognitive decision-making results in a much more influential customer journey and experience.
How is AI Improving the Customer Experience?
In the coming time, customers will no longer base their loyalty on the price or product. Customer experience will act as the key brand differentiator. Most organizations expect to stand out from their counterparts primarily based on customer experience.
And when businesses leap to satisfy their customer needs or requests immediately, the trends show enterprises are no longer fighting the conventional odds but digital ones.
So, how is AI being applied to Improve Customer Experience? Let's find out.
Automated Customer Service
Automated, or you can say, contactless personalized customer care is considered one of the key areas where AI contributes significantly to improving customer experiences. It includes chatbots and virtual assistants deployed in different customer engagement events to provide quick, personalized responses round the clock. Companies are going digital and adopting such intelligent AI setups to make their customers' journeys hassle-free.
Predictive Trends and Personalization
Artificial Intelligence transforms the customer experience by anticipating and making predictions on customers' preferences of where what, and when they will buy.
Intelligent recommendation systems make customers feel as if the product or service was customized just for them. Such models can predict future behaviors of customers with high accuracy while keeping track of underlying factors for achieving excellent customer satisfaction.
Using Augmented AI Analytics, businesses can develop customer profiles, generate real-time insights, and customize the marketing-mix strategy for individual customers to improve their sales funnel.
Every customer wants to feel valued. Most marketers think personalized content is more effective in reaching customers. Using ML algorithms, companies can analyze their customer behavior to strategize a campaign targeting the right message to the right audience.
Many digital touchpoints, including social media channels, mobile apps, and website visits, can all be injected as data sets of ML algorithms to learn more about customer interactions and past activities. This will help companies predict which touch base is most valuable to them.
Incremental Increase in Productivity
Companies are adopting AI to automate labor-intensive tasks and thereby reduce operational expenses. AI-powered bots can proactively initiate conversations with customers, providing quick assistance or guiding them in fixing some issues. As AI can work around the clock without taking any lunch breaks and learn new skills without making human errors, companies can achieve greater productivity and improve the customer experience.
Move Towards Better Customer Experience with AI
Today, customers need experience. Machines, simulated with human intelligence, promise to deliver highly personalized experiences while trying to minimize costs. Artificial intelligence and machine learning solutions help companies optimize their customer experiences-from data quality to customized recommendations for customer acquisition and retention. Way forward, more companies would deploy AI to own the new brand - customer experience.
Here at Icreon, we work on Artificial Intelligence, Machine Learning, and Deep Learning to build next-gen solutions that match your customer needs and preferences. Our algorithm experts strategize, identify high-impact areas within an industry, and pair that with proven AI successes to create opportunities that matter in your customer experience journey. Explore Icreon's Emerging Technology Development Services.