How much time and effort does your team spend on basic CX tasks, like, answering repetitive customer queries, gathering data from different platforms to optimize customer journeys, or staying on top of internal CX processes? What if you could use the right technology to significantly reduce workload, save time, and get better results?
There has been increased publicity and interest in generative AI, with several applications released in 2022 and 2023. According to a Gartner poll, 70% of organizations surveyed are currently in “investigation and exploration” mode with this technology. The primary focus of generative AI investment is customer experience, with nearly 40% of survey respondents naming this as their main area of investment.
However, every new technology comes with its challenges. You’ll need to fit the technology into the existing tech stack, encourage employees to use it, and measure its ROI and effectiveness—this process can take quite some time to complete. Organizations need an effective strategy for introducing AI into their company’s CX efforts.
Read on for some key tips on how to best leverage this exciting new technology:
Four essential building blocks to implementing AI in CX
1. Obtain relevant data to train the AI
For your AI implementation to be effective, you’ll need to train it on the right data, namely LLM (Large language model), and different types of data models, ranging from generic to account-specific customer service use cases.
You can simplify this process by partnering with customer service vendors who have prior experience working with AI.
2. Analyze the customer journey to understand where and how to plug in AI
If your company is thinking about using generative AI to improve your CX processes, you’ll want to identify which types of AI tools would be most appropriate for your organization’s needs. To do this, you’ll need to understand the customer journey, so you can identify pain points and opportunities for AI to help.
To get started with understanding your customer journey, it can be helpful to build out a customer journey map. A customer journey map is a visual representation that will allow you to understand how customers interact with your products, the journey they take on your website, and their path to conversion. This helps to identify any issues they might be facing during the buying journey.
Journey mapping helps teams develop empathy for the end user, and come up with more effective solutions. It will allow you to get the best possible ROI, as you will understand where customers may most benefit from AI assistance.
In addition, you will also want to do some user testing with the customer service reps who will be using the tool. This will help ensure that the AI tool is adopted and help streamline the implementation process.
Adoption is crucial for any new IT investment, and those who successfully execute a digital transformation can expect to see a myriad of benefits. These include increased productivity, greater customer and employee engagement, and higher levels of profitability, according to Deloitte.
3. Security and AI
Of course, like any other technology, generative AI comes with its own set of benefits and security risks. But, nearly 70% of executives believe the benefits of generative AI outweigh the risks, with just 5% believing the opposite, according to Gartner.
Businesses can take to increase the security by:
- Creating systems to minimize the risk of data loss: Organizations can try creating a custom front-end layer for an existing application, creating a sandbox where data is isolated, or otherwise keeping sensitive data in a trusted environment.
- Training their employees on proper use of generative AI: Employees should have a comprehensive training session to let them know which AI tools are available for their use, instructions and best practices for using these tools, and any rules or guidelines they should follow.
- Training models on clean, unbiased data: Using irrelevant or biased data can lead to incorrect responses and broken customer experiences. It’s best to be transparent about the data and model being used when deploying generative AI.
- Learn about cybersecurity best practices for AI: Is your cybersecurity team up-to-speed on the latest best practices for generative AI? For example, do they know which types of malicious attacks are most likely to occur? Are they equipped to deal with these sorts of attacks if they occur?
Consumers are very concerned about data privacy, with nearly 80% of Americans worried about how companies are using their data, according to Pew Research. If AI tools will have access to sensitive data, it’s important to make sure that data is protected. While evaluating vendors, it is crucial to select AI-powered tools with enterprise-grade security.
4. Find the right partner & choose a tool that offers the integrations you need
Using generative AI to optimize your CX processes can seem like a big task. However, by partnering with the right software vendors, supercharging your CX can become considerably easy.
You’ll want to choose an AI tool that will easily integrate with your existing tech stack as well. This way, you won’t have to worry about switching back and forth between tools.
To facilitate the process, you can look for an AI tool that comes built within an existing software solution required for your business. One example is Freshworks’ Freddy AI. Predictive and assistive generative AI capabilities are embedded directly within the Freshworks customer service suite platform. It is designed for customer service teams to improve CX using:
- Automated self-service and chatbots to give customers quick responses
- Generative AI-powered features to boost agent productivity
- AI-enabled reports for measuring and optimizing CX effectiveness
To learn more about how CX teams can benefit from generative AI, check out this playbook from Freshworks, and learn more about FreddyAI’s new generative AI capabilities here.