Selecting and implementing new tools into your tech stack can often be a daunting process, especially customer service and support tools. These tools often involve complex setup and management processes, leading to frustration among support teams. This is particularly true with the integration of AI in customer support. The complexities of implementation, steep learning curves, and delayed value realization for AI-driven customer support tools make onboarding a strenuous task.

This guide will help you navigate the complexities of selecting and implementing AI-powered customer support tools. Additionally, it will help streamline the process to eliminate bottlenecks and ensure a smooth transition.

What does AI in customer service look like?

AI customer service tools entered with the promise of enhancing customer experiences by delivering fast, personalized resolutions at scale. In terms of use-cases, AI-powered customer service tools enable organizations to automate routine tasks, assist agents, and ultimately improve long-term productivity.

The potential impact of AI in customer service is immense. According to Gartner, by 2025, 40% of all customer service interactions will be managed entirely by AI systems with significantly reduced human interaction.

What benefits does AI in Customer Support provide? Why is Ema special?

Before diving into the implementation, let’s review the key benefits that AI based customer support tools offer:

• 24/7 Availability: AI systems provide around-the-clock support, ensuring customers have access to assistance whenever they need it.
• Scalability: Unlike human agents, AI tools can handle multiple conversations simultaneously, making it easy to manage spikes in demand and seasonal fluctuations.
• Cost-Efficiency: Automating routine tasks reduces operational costs, allowing human agents to focus on more complex and high-value issues. Companies using AI for customer support have reported a reduction in customer service costs by up to 30%.
• Consistency: AI ensures uniform responses across all interactions, adhering to company policies and maintaining a consistent customer experience.
• Data-Driven Insights: AI tools analyze customer interactions to provide valuable insights that can drive business improvements. A study by McKinsey found that companies leveraging AI for customer insights saw a 10-20% increase in customer satisfaction.

Ema’s Agentic AI based customer service solutions takes these benefits to the next level:

• Ema is available 24/7, autonomously resolving over 80% of customer tickets. Unlike legacy tools, Ema can scale to handle any volume of customer queries.
• Ema can solve complex and unstructured queries working across multiple tools that typically require human agent involvement.
• Ema mirrors your best agents, providing contextual, human-like responses based on customer history and existing knowledge base. To top it off, Ema maintains your brand’s tone and voice across all interactions and languages.
• Ema combines the power of hundreds of LLMs to provide unparalleled cost-efficiency and accuracy.
• Ema autonomously improves over time, ensuring your customers consistently receive the most empathetic, personalized experience.

To fully realize the benefits of AI CX tools, it's crucial to choose the best-fitting solution for your needs and to then ensure a seamless and straightforward onboarding process. As you're exploring AI customer service solutions, you've likely encountered a variety of products and wondered how to choose the best tool.

Which AI customer support tools are best for my company?

Choosing the right AI customer support tool depends on several factors including business needs, industry context, customer communication style, urgency of support and existing infrastructure.

Here’s a breakdown of the pros and cons of the two main types of AI customer support tools before the advent of Gen AI:

1. Legacy Chatbots:

• Pros:
  • Ideal for handling simple, repetitive queries
  • Relatively easy to implement and maintain
  • Can be integrated with websites and messaging platforms
• Cons:
  • Limited ability to handle complex or nuanced issues
  • May frustrate customers if not properly designed or implemented
  • Rely heavily on keyword patterns and decision trees
  • Cannot handle multiple languages or channels

2. Agent Assistants:

• Pros:
  • Enhanced decision-making capabilities by analyzing large volumes of data.
  • Increased efficiency and scalability.
• Cons:
  • Lacks the human touch necessary for certain interactions.
  • Limited in solving complex problems and taking decisive actions.

Learning from the limitations of traditional chatbots, Ema has been designed to overcome their shortcomings with the philosophy that a chatbot should enhance your support, not hinder it.

With Ema’s Agentic AI-powered chatbot, you get:

• Auto-categorization: No need to set up decision trees or canned responses.
• Agent-like empathy: Ema mirrors your best agents’ tone and style for a seamless customer experience.
• Continuous improvement: Ema evolves and improves autonomously, much like an internal employee.

Ema also offers an AI Agent Assistant designed to empower your customer support team providing:

• Real-time personalized response suggestions based on previous conversations, product knowledge, and your internal communication style
• External App Interaction: Ema takes action across hundreds of apps, reducing the need for additional steps by your team.

After selecting the right solution, preparation is the next critical step. Proper planning and setup are essentially to ensure a successful implementation meeting your organization's needs.

What are the steps involved in AI customer support implementation?

1. Assess Current Workflows:

• Traditional AI Products: Map out your existing customer support processes, identify bottlenecks, and determine tasks suitable for automation.
• Ema: Supercharges this by looking at your past transcripts and automatically generating topics that drive large query volumes and contact center insights.

2. Identify Opportunities:

• Traditional AI Products: Analyze customer feedback and support metrics to pinpoint areas where AI can improve response times, resolution rates, and overall customer satisfaction.
• Ema: Goes beyond solving simple L1 tickets and can take action and resolve more complex queries.

3. Prepare Data:

• Traditional AI Products: Compile FAQs, knowledge base articles, and historical support data, and structure it for AI training.
• Ema: Can save your team hours spent on compiling the data as there is no need to clean up the data or prep the knowledge base. Ema can ingest data in any form you have.

4. Configure the AI Tool:

• Traditional AI Products: Set up integrations with existing systems and define conversation flows and decision trees.
• Ema: Comes with 100+ pre-built integrations and auto-categorizes tickets so you don’t have to set any decision trees up.

5. Train the AI Model:

• Traditional AI Products: Feed it with the prepared data, conduct initial testing, and refine the model as needed. This process can be time consuming and require ML knowledge.
• Ema: Simplifies this part and you conduct evaluations using a simple UI and give natural language suggestions that Ema immediately incorporates.

6. Deploy in a Controlled Environment:

• Traditional AI Products: Start with a pilot program or limited rollout (for example, roll out to a percentage of users or start with a few categories of tickets), monitor performance, and gather feedback.
• Ema: Customers usually experience a smooth and easy rollout with Ema automatically gathering and learning from feedback rather than doing it manually.

7. Refine and Optimize:

• Traditional AI Products: Continuously improve the AI model based on real-world interactions and update the knowledge base as necessary. Refinement and optimization is where a lot of the resources get allocated to get consistent value.
• Ema: To remove this manual process, Ema automatically identifies gaps, generates knowledge articles and improves itself

How long does it take to implement AI customer support?

Implementation timelines can vary widely depending on the complexity of your needs and the chosen solution. Typically, you can expect:

• Basic chatbot implementation: 2-4 weeks
• Advanced agent assistants: 2-6 months
• Comprehensive AI customer support system: 3-9 months

Unlike most GenAI tools for customer service, Ema takes just a couple of hours to onboard and set up so your team starts seeing benefits in a couple of days, rather than months.

What are the common challenges in AI customer support onboarding? How does Ema overcome them?

1. Muted Agent Adoption: Involve agents early in the implementation process and provide comprehensive training. Ema’s conversational language and user-friendly setup make this transition smoother.

2. Poor Response Quality: Select a solution with high accuracy and coverage. Ema surpasses human agent accuracy after just three weeks of deployment.

3. Integration Complexities: Choose AI tools with robust integration capabilities. Ema offers over 200 pre-built integrations, saving your team time and resources.

How do I measure the success of AI customer support implementation?

The following KPIs are important to define and track post the implementation:

1. Response time: Measuring average time to the first response

2. Customer satisfaction: Using surveys or NPS to gauge response quality

3. Resolution rate: Measuring the percentage of issues resolved without human intervention

4. Cost per interaction: Measuring change the average cost of each customer support interaction

5. Agent productivity: Measure improvements in human agent efficiency

In conclusion, while the potential of GenAI in customer support is tremendous, it’s essential to choose the right tools that are easy to implement and deliver on key metrics.

Ema has been designed to boost productivity tenfold across customer support and deliver value in days. Leading enterprises like Envoy, Truelayer and Moneyview are using Ema’s customer support solution to supercharge their customer support operations.

Ema is compliant with SOC 2, ISO 27001, HIPAA, NIST and GDPR. Thus making Ema the most performance and trusted Agentic AI platform to revolutionize your customer support.

Ready to elevate your customer service? Hire Ema today.