In this roundup, much of the new research has to do with organizational success. From Avaya comes a new study on the relationship between business success and the so-called “Total Experience” approach. In Hiya’s new report, the popularity of the phone call is rated against email, text, video chat, and other modes of communication. Meanwhile, breaking up with a customer may be just as important as keeping one to ensure business success, according to Gartner. And the role of artificial intelligence (AI) is discussed in two reports: AI and subscriber churn, from Salesforce; and AI implementation in India’s financial sector, from PwC and the Indian Chambers of Commerce. Details follow.

Avaya: The “Total Experience” for Business Success

A new study from Avaya, the provider of cloud communications and workflow collaboration solutions from Durham, North Carolina, indicates that the most successful businesses advocate an interconnected approach of four key elements: customer, employee, user, and multiexperience.

The approach, dubbed “Total Experience,” recognizes good CX as intrinsic to a brand; empowers employees with up-to-date tools and platforms, such as chats and virtual assistants; provides the human user meaningful interaction with data and technology; and affords memorable, personalized interactions in moments that matter.

“A monolithic, one-size-fits-all approach doesn’t meet the wide range of needs businesses and their constituents have,” says Simon Harrison, senior vice president and chief marketing officer at Avaya. “When companies intentionally combine customer, employee, user, and multiexperience thinking, they elevate everything these approaches can achieve on their own—enabling them to deliver exactly what’s needed at every interaction.”

Hiya: Phone Calls Are Still No. 1

In its 5th annual State of the Call 2022 report, Seattle-based caller profile provider Hiya says consumers and businesses prefer the phone call over all other methods of communication. The top communication channels for consumers, according to the report, are the phone call (32%), email (20%), text or instant messaging (12%), video call (6%), website chatbots (5%), and other/NA (26%).

Across the globe, consumers prefer to pick up the phone when they need to connect with institutions or service providers, but especially with coworkers, friends, and family. Businesses  also turn to voice to connect with customers, particularly for time-sensitive interactions, such as responding to customer inquiries, scheduling appointments, and closing sales.

Spam and fraud calls are a growing problem worldwide, the report adds, with an estimated 117 billion spam and fraud calls occurring last year in the US, Canada, UK, Germany, Spain, and France, equivalent to an average of 14 spam and fraud calls per month for every user. A quarter of consumers in these countries reported losing money to a phone scam in 2021, at a loss of $542 on average per victim. 

Gartner: Companies Must Formulate Customer-Breakup Strategy

Recently released research from Gartner reveals that by 2025, 75% of companies will break up with poor-fit customers, as the cost of retention overshadows the acquisition cost of good-fit customers. Given the likelihood of these breakups, in which an organization—and not the customer—proactively ends the relationship, companies will need to develop viable customer breakup strategies. 

The cost of keeping a poor-fit customer includes outsize time spent on servicing custom-made solutions; the emotional damage that could lead to further attrition among customer service teams, often already under pressure; and the prospect of long-term profit erosion, as investing in poor-fit customers may boost revenue in the short run but compromise profitability in the long run.  

When formulating a breakup strategy, Gartner provides a few guidelines. One calls for companies to create a customer-fit score to decide whether to grow, maintain, or break up a customer relationship. Another calls for working closely with the C-suite team to acquire good-fit customers and compensate for the loss of revenue from dropping poor-fit customers. Organizational key performance indicators (KPIs) should also be adjusted to include not only growth targets but also customer breakups when considering employee incentives, the report notes.

Salesforce: AI Can Help Predict Telecom Customer Churn

Citing data that show telecom subscribers are likely to switch to a different communications service provider (CSP) if their needs are not being met, Salesforce says AI can be harnessed to predict when customer churn is about to take place, and then provide proactive measures aimed at customer retention.

With research data from 36 mobile CSPs across 24 countries showing churn rates to range from 14% to 75% for all customer types, Salesforce, the provider of customer relationship management (CRM) software from San Francisco, says it built a new feature, dubbed churn predictions, for its Tableau CRM business intelligence software to help CSPs keep subscribers engaged.

Using AI, the churn predictions feature combines insights derived from customer interactions and data, such as customer case history and resolution, with external data like billing, network, and data usage. The resulting information is then used to develop a predictive picture of subscribers on the likelihood of their staying with—or leaving–a provider.

PwC-FICCI: Enhancing CX is Chief Reason to Implement AI for India’s Financial Sector

A joint report by multinational consulting firm PricewaterhouseCoopers (PwC) and the Federation of Indian Chambers of Commerce and Industry (FICCI) asserts that enhancing CX is the top reason that financial services organizations in India implement AI. At least 83% of business leaders in the banking, financial services, and insurance (BFSI) industries in India support that view, notes the report AI in Indian Financial Services: Uncovering Ground Truth.

Other important business drivers in deploying AI for India’s BFSI space are to improve productivity (57%), increase revenue (56%), reduce costs (53%), and ensure regulatory compliance (26%).

The principal BFSI use case for AI is the deployment of chat bots to ease the task of providing customer service (83%), followed by the use of AI engines to detect fraud in financial transactions (65%). Security and privacy issues rank as the chief concern (61%), but a vast majority (83%) believe their business to have a well-defined AI strategy, the report findings also show.