AI to Fuel Customer Experience (CX) in 2022

Resources 8 min read
In this article
Dec 24, 2021
Author Varsha

Shifting Customer Expectations Pushing Companies Towards Analytical Technology

The customer experience has always been crucial in business innovation and digital transformation with several digital touchpoints. The end-to-end customer experience improvement is expected each time companies aim to scale their business and companies do try to anticipate the needs of customers and provide a personalized experience. In the era of automated technologies becoming an organization with great customer experience isn’t novel. Companies are now trying to step into a business of Experience (BX) with shifting consumer behavior. The new reality pushes businesses to step into a new phase to make their customer experience their brands in depth.

A great experience is achieved when customers’ experience (CX) touches the desired outcome where companies can’t sit on the excuse of changing consumer expectations. A mature step of Business of Experience (BX) in the upcoming year 2022, will be a more holistic approach where all stakeholders will contribute to developing the exceptional customer experience. 

When companies provide the best customer experience, they start creating a positive financial impact as well. So organizations are now trying to step into technologies like AI and ML, that serve a ubiquitous purpose of CX. Customer experience has covered miles in terms of digital touchpoints and the internet and evolution in intelligent technologies has made it compulsory to march towards improving CX.

6 AI Strategies to Uplift Customer Experience 

In the age of AI, it’s time that customer segmentation strategies are more actionable on a personalized front. AI has the power to improve the customer experience journey at every step. As technology experience grows, customers too find that digital services can be improved across a variety of sectors. Provisioning of the desired level of specificity is possible through collaborative, elastic, and responsible AI at an enterprise scale. 

According to IDC’s survey, leading organizations that are well-positioned in their technology and data capabilities are in a better position to capitalize and pivot for opportunities arising from pandemics. 

Here are some strategies of leveraging AI for better CX:

1.Customer 360 (C360) Through AI: What customer experience demands are complete insights about customers that can serve customer satisfaction (CSAT) and personalize the experience with them. Customer 360-degree view  (C360) refers to information about every interaction from inquiry to product purchase made by them. The following steps would determine what customer 360-degree insight you get:

  • Predicting Survey Scores for Better CX from CX: Instead of taking reports from customers, take reports from survey reports to detect the anomalies and try resolving them. 
  • Engage Employees in Streaming Analytics: AI has the capability to provide microlearning so employees need to practice customer-centric behavior in real-time which enhances customer satisfaction (CSAT). 
  • Watch on NPS for Better CSAT: Net Promoter Score (NPS) is a core KPI within organizations, the higher the score, the more satisfied the customer you have. AI directly impacts NPS and implementing it can resolve NPS issues for organizations. Some ways AI can improve NPS score:
  • Companies can develop chatbots for a more effective self-service environment for customers or any AI for customers to do transactions or account changes.
  • Using AI, an intelligent routing system can be developed to guide customers to the fastest solution to problems.

6 AI Strategies to Uplift Customer Experience

2. Personalization Engine: A personalization engine measures the optimum experience of individual customers based on their past interaction, current practices, and predicted intent, which enhances the marketer’s knowledge about customers. 

  • Customer Intelligence Platform: Adding AI to this platform engine brings the digital experience of customers to the surface like layout, menubar, CTA buttons, etc., for any channel according to the visitor’s persona. This uniquely does:
  • Optimize personalization in real-time based on clicks and purchases.
  • Deliver targeted and dynamic content that unifies disparate sources of data in real-time.
  • Provide content-rich individual digital experience.

Watson Assistant by IBM is a full-service AI chatbot that integrates your CRM system to automate tasks and guide the marketers to the information needed to resolve customer queries. 

  • Product Intelligence Platform: AI-powered product intelligence platform provides a 360-degree view of your product positioning and performance. This provides data about product availability across the siloed system, service lines, and geographies. Also enhances the product design by incorporating customer feedback.

3. Machine Learning for Automated Learning: Machine learning (ML) ) provides systems the ability to learn automatically so that they can respond according to data given to them. When used with a chatbot, it will not only learn about specific responses but also determine when should the conversation be handed over to the human agent. This definitely is a step ahead in conversational AI to enhance customer experience. 

In this direction, Uber has its Customer Obsession Ticket Assistant (COTA) empowered by ML providing a most accurate solution to the thousands of tickets surfacing daily on the platforms. 

In a forward approach, companies must proactively use ML to engage customers at the right moment rather than waiting for customers to ask for new products and provide reviews. 

  • Start with core journey dataset and build to improve accuracy: customer-level data, operational data, financial data
  • Combine with customer interaction data

Predicting Customer Churn Rate with ML:  This rate is basically the health indicator of business which tells the percentage of customers who abandon the product. With the use of ML companies can find out which customers aren’t fully satisfied with the service, this is Effective Churn Modelling. With this effective customer retention actions can be made.

4. Use Data to Align with Business Objectives: After customer profile what organizations need is to figure out what insight they want to generate. Syn the tech, data, and human agenda for achieving bigger objectives and reimagine business objectives and operating model. With advances in customer expectation, enabling customer-eccentricity at a greater scale to integrate tools, technologies, data, and processes is imperative. This will build and maintain the business of experience (BX).
When it’s about data, building agile technology with cloud keeping in view the technology stack of companies will take it to the next level in 2022. With cloud capabilities, companies will reinvest in data powered by AI to drive performance.


5. Marketing Attribution Platform: The process of evaluating touchpoints on the path of the customer journey is called marketing attribution. Marketing attribution software allows marketers to determine which channels, campaign landing pages had the greatest impact on revenue. The manual process of attribute collection does not capture use engagement adequately.
Automating and scaling the painstaking process of the attribution process will reduce the manual process and introduce more automation by integrating CRM (customer relationship management). This has perfect space for AI to incorporate vast amount of data from various sources in a scalable way down to a granular level.

  • Build Recommendation Engines: This is a data filtering tool that uses ML to recommend the most relevant item to a particular customer. It operates on the principle of finding patterns in consumer behavior data and improving business across industries. The more data it collects, the more efficient and effective it will generate suggestions. 

6. More Focus on Use Case to Drive Value: It is important to have a clear vision of how the information will be applied and to focus on some specific use cases that will create immediate feedback. As a simple structure, organizations can look at key sources of opportunity, weak spots, or both across customer journeys and think about how a predictive system might create new or improve existing solutions that might have. a direct impact on customer behavior and sale. Leaders need to ask which use cases present a clear opportunity to drive value so they can build momentum and gain support.

Overall, companies need to be more thoughtful about where to focus their efforts, as current regulatory and economic scenarios require a reassessment of long-standing practices. As leaders strive to get a more complete picture of customer preferences and behaviors, they continue to rely on outdated surveys that have been the backbone of CX for decades and this needs to be changed.

Transforming Customer Data into Action to Expedite Business of Experience (BX)

In an era of digital interaction, AI has brought pace in various sectors of life and changed various performance parameters, especially in customer-centric businesses. Companies approaching towards providing greater customer satisfaction (CSAT) will need automated and more personalized plans, adjust their marketing strategies, and need to find or develop more use cases that will drive business value and flourish in the business of experience (BX). Importantly, AI and ML have reached several touchpoints with data-driven and analytical approaches like never before and continuously improving customer experience over time.

The context of using AI for a customer-centric approach aligns more with withdrawing relevant data and how it can be improved whether, through customer 360-degree approach, personalized engines or to develop use cases with help of data, and all processes are continuously evolving. The next step of disruption will lie in the business of experience (BX) where companies are heading now.  The winning plan will be successful for companies when they will be aware of what customers will look forward to i.e., take relevant customer data, make experience innovation a regular habit in the organization, and synchronize tech, data, and human agenda with company strategy. 

Techment Technology plans to implement a more customer-centric approach to enhance the entire customer journey and improve CSAT. With our offering of design, marketing and content we are trying to improve CX for the future and finding new ways to win customers.

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