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How to achieve contact center AI maturity in 2023 (+model)

Raghavendra Rao

January 12, 20237 min read

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In a VUCA (Volatile, Uncertain, Complex, Ambiguous) world customers are increasingly reaching out to customer support teams. For example, during the pandemic, incoming calls and escalations rose by over 300% in the contact centers. Organizations such as Decathlon shifted entirely to live chat and messaging to reduce the number of incoming calls, allowing its customer care agents to focus their efforts on solving critical issues rather than trivial ones. 

More brands are investing in AI for customer service to aid quick resolutions and address such high volumes of queries. Gartner predicts that one in 10 agent interactions will be automated by 2026 using conversational AI, reducing 95% of contact center costs. 

In this blog, we delve deeper into the concept of contact center AI(CCAI) and how AI maturity impacts contact centers. 

Top 3 challenges faced by contact centers

Here are the three key challenges faced by contact centers. 

1. Evolving customer preferences

The pandemic acted as a digital accelerant and has caused a dynamic shift in customer preferences. Additionally, customers prefer and consume content in different formats. Different generations of customers have left a huge digital footprint and left brands to deal with many petabytes of structured and unstructured data. 

2. Lack of personalization

Due to limited visibility into a customer profile, care agents offer generic and relatively less helpful responses to customers. Siloed customer view results in a lack of personalization.

3. Fragmented AI solutions

Fragmented AI solutions are expensive, difficult to use, and have limited reusability. An average contact center uses multiple-point solutions, making it difficult to understand the customer, their journey and preferences in entirety.

How does AI maturity impact contact centers?

AI maturity is the degree to which contact centers have mastered the required AI capabilities to achieve high performance for their customers by improving their experience and offering quick resolution. Since different contact centers have different levels of AI maturity, their automation levels differ along with their customer experiences.

Accenture suggests that only 12% of organizations can be categorized as AI-mature organizations which will double down by 2024. In the pre-pandemic era, AI mature organizations recorded 50% higher revenue than their peers.

Given the importance of AI in customer service, Sprinklr suggests four key elements to evaluate the AI readiness of organizations:

1. Strategy

Organizations must have a clear and detailed plan of action to support AI. There should be transparency around the current strategy, gaps, KPIs, and budget constraints. 

2. Organization culture

Any AI and digital transformation initiative would fail if the organization doesn't have a change culture. Org culture becomes critical to onboard employees. 

3. Technology & operations

For a successful technological implementation, organizations must consider their current state of AI deployment and work on creating an AI roadmap for clear outcomes. Usually, two technologies are used at the forefront of customer services: conversational AI and contact center AI

4. Data & analytics

Organizations must be aware of the data processes and governance across the organization. Since AI technologies use machine learning for precision and accuracy, the data should be high quality and less noisy. 

Sprinklr’s CCAI maturity model

For a better understanding of the AI maturity levels and AI readiness of an organization, Sprinklr proposes a four-stage contact center AI(CCAI) maturity model.

Level 1 - Beginner
This is the initial phase of AI maturity wherein the organization has built a basic foundation and awareness. However, the actual implementation of AI technology is still pending.

Level 2 - Competent
In the second level the organization has implemented basic AI capabilities with minimal data sources to automate lower-complexity customer journey tasks. There are a minimum number of integrations present. For example, creating a single support channel with one language to provide a few rudimentary responses. In this phase, an organization can address deflection but not customer satisfaction concerns. 

Level 3 - Proficient
AI Proficient organizations work on the expansion of their AI capabilities. They have multiple data sources, comparatively higher integrations in the tech stack, and can address low to medium-complexity tasks. In this stage organization focuses on deflection, improving CSAT scores, and employee efficiency and satisfaction. For example, multiple support channels handle customer concerns in multiple languages.

Level 4 - Advanced
AI mature organizations have advanced AI capabilities to address highly complex customer use cases. They can collect information from all the available data sources and have a tightly integrated or unified tech stack for an easy flow of information. They can go over and above improving customer satisfaction to focus on increasing revenue. 

An image showing four stages of the Contact Center AI Maturity Model

Progressing from beginner to advanced stage in the maturity model

Contact centers must aim to become experience centers by leveraging advanced AI capabilities. Instead of treating the customer service function as a problem-solving function and a cost center, contact centers must view it as a shared value creation function — engaging customers at every step of their journey. Here are the top three ways to help you transition from an AI beginner to AI mature center:

  • Proactive customer care: using a predictive approach to customer service and in-depth customer insights can help you create loyal customers. Support agents must be trained to identify potential issues and plan for customer outreach.

  • Self-serve strategy: self-service options such as FAQs, AI/automated chatbots, customer-facing knowledge bases, and online community forums, are preferred by customers more than interacting with an agent. 

How to craft a winning customer service strategy using self serve

Sprinklr's Conversational AI fosters a self-serve culture within the customer care functions. The chatbots are powered with advanced AI capabilities which can offer support across multiple channels (chat, social, and messaging) in different languages. Conversational AI obtains customer data from over 30 channels and 100 million data points — providing accurate and precise responses for the support queries.

An image showing how Sprinklr Conversational AI works on intent detection.
  • First contact resolution: Agents must be empowered to solve issues quickly in the first interaction by providing a 360-degree view of customer information right at their fingertips. The selected AI-automation capabilities must make the omnichannel customer experience personalized and seamless.

How to select a contact center AI solution that fits

With multiple point vendors and application suites in the market, every other AI solution seems like a 'me-too' product with minimal differentiation available. It becomes highly challenging for organizations to choose an AI application that will cater to specific business requirements. 

Here are the top three parameters that differentiate Sprinklr's unified contact center AI from its competitors:

1. Features

Sprinklr offers a wide selection of in-house advanced AI capabilities to offer unified customer service. Additionally, Sprinklr offers a high level of customization according to the brands' requirements with over 80% accuracy.

According to the NLU benchmarking method, Sprinklr’s NLP accuracy by the recall and F1 macros is higher than the contemporaries — Google Cloud, Azure Language Studio, and AWS Comprehend. For both small and large data sets, the Sprinklr NLU engine is a clear winner.

An image showing how Sprinklr's AI capabilities have an edge over its competitors

2. User-friendly

Since the Sprinklr CCAI is a plug-and-play solution, your agents don't need to contact IT frequently for support. They can explore the application and accomplish desired tasks.

3. Scalability

With Sprinklr CCAI, organizations can quickly scale in terms of 30+ channels and 100+ languages support as per their requirements.

Let’s dive into how Sprinklr is enabling leading brands to deliver loyalty and growth through Unified AI.

1. World Health Organization

World Health Organization was exploring a solution to address the following challenges during the pandemic:

  • Reduce the spread of misinformation about COVID-19

  • Disseminate critical information

  • Track citizens' interactions across digital channels

As part of the collaboration, the WHO Health Alert Bot was enhanced with Sprinklr’s conversational AI capabilities and included on WHO's official Facebook page to reduce the spread of misinformation. The bot is also integrated with country stats updates & other informative features like Self Help Course, Quit Tobacco Program, Myth Quiz, Surveys and more.

An infographic on how WHO benefitted from Sprinklr's Unified-CXM platform.

2. Cdiscount

Cdiscount, a French e-commerce leader, was looking for a solution to address the following challenges:

  • Understand customer sentiment 

  • Improve customer interactions for their 10M customers. 

  • Assist their quality management teams to analyze 100% of support conversations

  • Coach their agent

Sprinklr’s unified AI architecture works as an overlay solution without replacing any current systems, leading to a low degree of change management and internal churn. Sprinklr’s Contact Centre AI module enables Cdiscount to analyze omnichannel customer interactions at scale to understand conversation themes— such as delivery issues, refunds, and subscription questions. Every interaction has an associated customer satisfaction (CSAT) score and quality score to explore agent training opportunities and opt for a proactive customer service approach.

An infographic showing how Cdiscount benefitted from using Sprinklr.Louis Brun Ney Customer quote

3. Aramex

Aramex, a leading logistics and transportation solution provider, was looking for a customer experience solution to address the following challenges:

  • Reduce delivery reattempts

  • Decrease Logistics costs

  • Improve customer experience

Aramex leverages Sprinklr’s AI chatbots in four languages to automate responses, improve efficiency, and drive positive customer experiences across channels such as emails, live chats, and Whatsapp. Aramex is now able to automate the rescheduling process and suggest nearby pickup locations to its customers.

Moi Abeidat Customer quote
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