Rohan Joshi is the CEO and co-founder of Wolken Software, a leading IT service management and customer service desk software provider.

Customer experience has long been considered to be a greater priority for B2C companies, but it is now clear that B2B buyers expect their vendors to supply consumer-level customer service.

In many ways, the expectations for superior customer service have become greater for B2B companies as customers want the option to quickly find answers on a vendor’s website by accessing knowledge bases, chatbots or other digital platforms—or by calling a customer service agent. Regardless of the channel, they expect to find immediate solutions that address their specific issues, which are often complex and unique to the individual customer. For many B2B companies, addressing this situation is now accompanied by AI to enhance the customer experience.

Optimizing The Customer Service Management Solution

An organization’s customer service management (CSM) solution is much like the body’s central nervous system. It plays a critical role in keeping operations running as they should by serving as a central hub to access pertinent company details and the self-help features global B2B enterprises use. As the brain is inextricably connected to the central nervous system, so, too, is the link between AI and the potential power of a company’s CSM platform.

The CSM is key for delivering personalized experiences for specific customers. This is not new information; customer portals have long offered advanced personalization features. This allows businesses to tailor the user experience according to specific customer profiles, purchase history and interaction patterns, thereby delivering a level of personalization that not only enhances user satisfaction but also boosts customer loyalty.

AI’s Role In Improving CSM

AI is helping to supercharge these pathways of connection between businesses and their customers in several ways.

Many B2B companies still require agents to partake in the manual process of reviewing a customer’s history and situation, combing through internal data (often from multiple sources) to find relevant information and creating a custom response that is directly related to the specific customer and query. AI can help turn this arduous task into an automated workflow that delivers the end result in minutes, allowing agents to more quickly and effectively resolve service issues.

When it comes to self-service channels, generative AI has quickly permeated both consumer- and enterprise-facing chatbots due to its ability to quickly pull custom and relevant articles from organizational knowledge bases and external sources to meet specific customer queries or needs. This has helped decrease resolution times while allowing support teams to focus on higher-level issues.

AI can also be used to predict potential customer issues. “Customer health” monitoring can predict churn before it happens, enabling proactive engagement that can potentially salvage the engagement via tailored product usage suggestions and timely responses. AI-driven KPI reports, trend analysis and productivity optimization can help with resource allocation as well, ensuring that customers most in need of hands-on intervention receive it in a timely manner. Integrating AI into an organization’s CSM can also help identify upselling opportunities by shedding light on customer behaviors and service requests.

How B2B Companies Can Get Started

As more executives begin to leverage AI solutions to optimize their CSM platform, it is necessary to make customizations that will improve the specific processes that exist within their organizations. However, there are focus areas that must be a priority for any organization to fully maximize the benefits of new AI enhancements:

Make the CSM a single source of truth for all customer data.

Many global companies are recognizing the need for a single source of truth for their entire enterprise. It is an ongoing exercise, and regular data audits to measure data currency and integrity are important steps to get an enterprise ready for a robust CSM solution. Many organizations have allowed loosely defined governance standards, but that is changing due to the adherence to standards like SOC 2, among others.

This path to getting their data right is essential for a CSM to deliver an individualized experience to users. Personalization can only happen if AI has access to all of the necessary and correct data. When customer data is siloed or incorrect, there is a greater chance that AI can deliver incorrect data—which could lead to a negative customer experience. One negative experience with AI-powered customer service can leave a lasting impression, so it’s critical to set the right foundations at the outset.

Invest in enhanced security and compliance.

As long as enterprises and people exist, there will be errors. Continuous training, performance monitoring and adopting workflow safeguards are great first steps, however, technology can also be used to help detect and correct these errors at the source level.

This investment is particularly important for protecting customer data, which should always be a top priority, especially for global businesses dealing with sensitive information. Any CSM must support compliance with international regulations, such as GDPR, to ensure customer data is handled responsibly and legally.

Support solutions that are accessible to all consumers.

A global enterprise must be able to support and service a global customer base. Diverse customer bases will have distinct needs and preferences that AI cannot ignore. CSM solutions should be customized to collect, store and leverage the specific information unique to different customer segments as needed.

Similarly, multi-tenancy and multilingual support can offer a huge advantage for teams and clients. B2B organizations must be able to manage multiple clients or departments with secure data separation as well as serve a global audience with multilingual functionality. However, note that care needs to be taken when adding in these services to ensure that AI translations and dialects are always correct for customers in every geography and language that a company services.

By implementing these strategies, B2B enterprises can take the first step in optimizing their CSM solutions to enable the significant growth potential of AI.

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