As organizations reset their business strategies and plans, they are focusing on providing TX ( total experience) to its users, which captures key moments combining sales, marketing, and CX under a single umbrella with clear and unambiguous accountability to maintain and grow customer lifetime value and profitability.
Organizations are increasingly creating and managing AI-powered customer experiences, from real-time personalization to conversational voice interactions.
AI, Marketing, Sales & CX
AI, has potential to transform business functions and practices at scale. It offers customers a digital and personalized consumer experience, with content tailored to their needs, with better segmentation, that helps to build lasting relationships with customers on their terms.
AI in Marketing
Smart Marketing Campaigns: The role of marketing specialists is increasingly becoming obsolete, as AI takes on duties of constructing the campaign dialogue or journey management workboard, connecting and triggering different channels and smart content in customers’ journey.
Personalized Experience: AI is enabling marketings to tailor a real-time personalized user experience with tailored content, smart offers, and promotions using propensity modeling, machine learning, machine vision, and NLP.
NLP - We are increasingly using NLP in conversations without realizing it, and as the advances in natural language processing (NLP) progresses marketers are leveraging it for running smart campaigns using AI & NLP.
ML ( Machine Learning To Help Identity resolution): Machine learning algorithms are helping to sift through and map billions of ad impressions and hundreds of millions of device identifiers to provide marketers with greater confidence that the right message reaches the right person.
Augmented marketing analytics: With easier-to-use analytical capabilities AI continue is expanding across the marketing technology landscape, including natural language querying, natural language contribution analysis, prescriptive actions, and logo detection.
AI in Sales
Organizations are using AI in sales to grow business and help the sales team.
Price Optimization: Using AI-assisted algorithms price optimization to suggest optimal pricing for every deal, along with historical data to work out ideal discounts level to secure the win.
Customer Lifetime Value Analysis - Organizations have started to use AI to provide customer health scores for all kinds of activities (e.g., churn, upselling).
Lead Scoring - Uses ML models to predict conversion likelihood, to prioritize sales leads.
Cross-Selling and Upselling - They are using ML to identify new business opportunities for existing customers.
Demand Generation - Identifying new prospect segments from known characteristics of known segments.
Territory Optimization - AI is helping to produce a balanced set of territories, based on geographic, account, and product data.
Sales Content Personalization - ML algorithms are being used to recommend personalized content to sellers for nurturing customers.
Lead Discovery - Organizations are using AI to automate routine business conversations and provide better lead qualification.
Knowledge Management - ML models are being used to surface relevant information to sellers for managing customer requests better and faster.
Sales Forecasting - Sales Teams are using AI to predict sales forecasts based on historical data and seasonalities.
Guided Conversations - Leveraging NLP to uncover customer sentiments and helps in guiding customer conversations.
Opportunity Scoring - Using AI to predict win probabilities by sales stage for prioritizing next steps.
Account Intelligence - Sales and marketing teams are using AI to recommend curated content about the prospects/clients based on current news feeds.
Relationship Intelligence - Organizations are using AI to identify and suggest relevant business contacts within the seller’s social network.
AI in CX
Business brands exists because they provide the experiences they enable. How they differentiate from the competition and connect with consumers. But today’s brands are under increased pressure to ensure they deliver extraordinary end-to-end humanized customer experiences. AI is the key enabler in taking up this challenge.
AI has the power to fundamentally transform interactions between consumers and brands
AI can enable brands to behave more like people, to offer truly humanized experiences. Infusing AI into digital customer platforms makes the customer experience more human – at a scale previously unimaginable – and increases the level of engagement.
Indeed, AI-enabled technologies can understand customer’s feelings and express empathy, apply humor or/and show understanding and respect. By fuelling AI with individual customer learning and understanding, it becomes possible to continuously translate customer interactions into actionable insights. Employees and enterprise systems can better predict and address customer needs for a differentiated experience.
AI has become a powerful weapon to drive loyalty, increase growth and improve efficiency
It can improve the quality of life for the individual customer and employee, while creating a wealth of new opportunities for businesses to increase their operational efficiency, grow sales and loyalty, improve and speed up decision-making and become more relevant and innovative in the development and delivery of products and services.
Unleashing the full potential of AI for CX – defining essential use cases
The impact of AI on customer experience is being significantly felt in two ways:
- New ways of interacting, such as conversational interfaces.
- Performance improvement of existing methods, such as employee intelligence augmentation,
- Better analysis of data that customers provide
- And/or greater personalization through better understanding and better anticipation.
Identifying and choosing the right use cases to deliver business value in a particular domain is essential for seizing new AI opportunities.
Organizations should look at four identified interconnected application domains to enable the deployment and humanization of customer experiences:
- Customer Understanding
- Customer Engagement Augmentation
- Conversational Interfaces
- Immersive Experience.
Challenges Implementing AI Application Domains At scale
As organizations evolve from exploration to implementation at scale, they should think holistically and inclusively and prepare for complex challenges.
- In establishing AI-infused customer platforms
- Connecting to a state-of-the-art customer data ecosystem
- Selecting and using AI technology portfolio, from our network of partners
- Ensuring trust through echo system, with right compliance, transparency, ethics and accountability.
- Employee the necessary people and talents to generate the results.