AIThority Interview with David Lambert, VP & GM, Strategy & Growth, APAC, Medallia

AI-driven customer experience management software companies are ruling the SaaS marketplace. These companies leverage AI to serve CX marketers, empowering them with potent data analytics and insights about customer behavior and intent signals. Medallia is one such company that ranks high in AiThority’s AI-powered CX software RADAR. Recently, the CX enabler announced it surpassed more than 1 million active weekly. Top brands use the platform to capture in-person signals and transform their cloud contact centers with real-time communication. The CX platform supports more than 15k+ pre-learned topics on personalization, trained on Medallia’s proprietary AI NLP/ NLU datasets.

We spoke to Medallia’s VP & GM, Strategy & Growth, APAC, David Lambert, on how AI is transforming the cloud contact center operations and delivering high-end CX automation.

Here’s what David said to us.

 

How do cloud contact centers benefit from using AI-powered personalization? 

David Lambert: Better experiences for each customer translate into better business results for the contact center. There are three main benefits:

First, the customer gets to the right place for their issue to be solved.

If a customer encounters an issue, a company should know about it in real-time, and proactively help that customer get to the right part of the contact center that can solve the issue in the fastest time, while considering that customer’s support preferences.

This is achieved through Experience Orchestration software that stitches together each customer’s journey as it happens and across channels. The software understands and prioritizes the intent and context of each customer journey about that customer. The benefits are that each channel is more optimized – “good” call deflections increase, first call resolutions increase and handling time decreases.

Then, the customer’s issue is resolved in a more reasonable time. 

Contact center agents are great at understanding customer sentiment and pain points, and how to adjust their conversation to deliver greater empathy. However, AI can speed up resolutions for each customer by surfacing and prioritizing the next best experiences or actions.

Experience Orchestration software can help understand the intent and context of the customer’s current journey, and which past actions of similar customers lead to the best resolution. This will increase first-call resolutions, increase agent satisfaction and decrease handling time.

Lastly, future customers are less likely to have the same issue impede their experiences. 

The contact center solves customer problems but often doesn’t create them. Companies need to ensure that insights from Ai-powered personalization are democratized across the enterprise to the right teams in real-time. This allows teams to take action to prevent those problems from happening again, thereby reducing the burden on the contact center.

This is accomplished through Experience Management software that connects insights and actions from any customer journey, including those that pass through the contact center, and easily serves them to the right teams. This helps the contact center reduce future similar issues.

What are the major trends in AI and machine learning development that are specifically creating differentiation for predictive intelligence and call center analytics used in customer service?

David Lambert:  Several key trends in AI and machine learning development are driving differentiation. Major trends include:

Real-time Journey Visualization: Experience Orchestration software stitches together a customer’s journey in real-time, even as the customer interacts across channels, and prioritizes the intent of each journey. This has allowed companies to “see” actual customer journeys. This new view allows the contact center and its systems to understand the context and intent of each customer’s journey as it arrives at the contact center so that each customer’s issue can be resolved faster.

Advanced Prescriptive Models: AI and machine learning algorithms in Experience Orchestration software are becoming increasingly sophisticated in prescribing the next best experience or action for each customer in their current journey. These models can analyze large volumes of customer data, such as current and historical interactions, purchase history, and customer behavior patterns. This enables call centers to proactively orchestrate the next step in each customer’s journey to address customer concerns, personalize interactions, and optimize each journey.

Real-time Speech & Text Analytics: With AI and machine learning advancements, speech and text analytics can now process and analyze data in real time. Call centers can monitor ongoing customer interactions, identify emerging trends, and take immediate action. Real-time speech and text analytics help detect potential issues during calls or chats, provide real-time guidance to agents or bots, and allow call center supervisors to make data-driven decisions on the spot.

In summary, these AI and machine learning development trends empower call centers with prescriptive intelligence and advanced analytics capabilities. They enable call centers to see customer journeys, anticipate customer needs and personalize interactions in real time, and continuously orchestrate every customer’s journey to improve their experience.

Thank you, David! That was fun and we hope to see you back on AiThority.com soon.