Since generative AI (GenAI) made its explosive debut at the end of 2022, every business function has felt pressure to deploy GenAI-powered tools in some way, including in the contact center.
However, without the right data infrastructure, simply layering an AI tool runs the risk of further complicating what is often already a delicate tech stack. It could even result in biased or even simply incorrect responses to customers. Good outcomes rely on good data.
Despite rapid advancements in conversation intelligence software and AI-driven tools, many contact centers still struggle with fragmented data management practices. Is your contact center truly optimizing your data?
Let’s look at some of the emerging and persistent challenges — from siloed systems to AI integration — facing contact centers today. We’ll also share best practices for building a data strategy that can help you deliver both a better customer experience (CX) and business impact.
Diving Into Data in the Contact Center
For most organizations, the contact center is a wealth of untapped data. But many organizations view contact centers as a necessary hassle within their business. They see it as a department that is essential but costly and often a customer satisfaction hazard because of long hold times or ineffective responses that often cycle through multiple agents.
...simply layering an AI tool runs the risk of further complicating what is often already a delicate tech stack.
Contact center technology has, unfortunately, contributed to the poor reputation of many centers. A traditional multichannel approach to the contact center leaves information trapped in different systems that are unable to talk to each other. This results in customers repeating their information every time they interact with a new agent. This is another source of contact center-related customer frustration.
The solution to all these woes? Not AI, but improved data management practices.
Good data management begins with good data infrastructure, and good data infrastructure relies on clean, relevant, and connected data. If your foundational data is good, adding additional data and tech tools — including GenAI tools — should be a seamless, relatively easy process that culminates in more streamlined workflows and improved overall efficiency.
Here are some tips and points to help you begin improving your data management:
- Establish processes early on to regularly clean and validate data, including customer information, to remove duplicates and correct errors.
- Data management is not a “set-it-and-forget-it” process; it must be kept up-to-date and accurate.
- Plan for periodic data audits to keep everything current and identify any areas for opportunity within your data management practices.
Optimizing for Omnichannel
According to Salesforce research, 79% of customers expect consistent interactions across all departments within a business. That means if they start their search online and then pivot to a phone call, the experience should be unified.
If the experience is disjointed or requires them to keep repeating the same information, the underlying message is that customers’ time (and issues) just aren’t that important. For many customers, this is enough reason to hang up and never call back.
To avoid these mistakes, the most forward-thinking call centers are implementing improved systems and call routing: steps that are far easier to implement when you have good data management. With these features in place, agents can track caller history and inputs, allowing them to seamlessly pick up where the last agent left off.
A cohesive call center experience like this is the difference between truly integrated omnichannel support and disjointed multichannel support. It’s integration versus isolation.
Multichannel support just means customers have multiple ways to contact you, and the results often feel fragmented. Omnichannel support means those channels are all communicating with each other, so no matter when or how a customer reaches out, they get the same level of service, branding, and responsiveness.
Once your organization has solid data management practices, it’s time to look at adding GenAI capabilities.
Successful omnichannel support and good data management go hand in hand. Going from multichannel to omnichannel support isn’t just about upgrading technology: it requires a shift in strategy. Organizations often simply add new channels without aligning teams, messaging, and systems, including the underlying data infrastructure. In these cases, customers’ experiences remain siloed and inconsistent.
For a seamless omnichannel experience, organizations must synchronize messaging and workflows between departments, adopt integrated tech solutions that unify communications, and train agents to handle interactions across platforms.
Establishing a comprehensive view of customer information and conversation records is central to omnichannel success because it allows representatives to see the full customer story and background: regardless of which touchpoint the customer started at. This comprehensive visibility is foundational to the omnichannel approach.
Adding in AI
Once your organization has solid data management practices, it’s time to look at adding GenAI capabilities. GenAI is a game-changer when it comes to ensuring that customers have a smooth omnichannel experience. It can help bridge the gap between channels and deliver the on-demand service modern customers expect.
GenAI tools also enable round-the-clock automated assistance, predictive support, and tailored suggestions across touchpoints, be it a direct message (DM) or a social post or live chat or any other channel. This means less waiting, more targeted solutions, and an enhanced user journey overall.
Good data enables faster AI implementation and deployment by eliminating extensive data preparation...
On the agent side, GenAI functions as an intelligent assistant that can summarize conversation records, suggest replies, analyze sentiment, and highlight priority cases. GenAI-powered agents can answer many common questions, freeing up human agents to focus on more sensitive issues that require a human touch and problem-solving skills.
Advanced AI capabilities can further enhance operations by helping maintain the uniform communication style and voice that is critical when providing omnichannel support. AI can also assist with crafting social media responses, creating follow-up correspondence and so much more, ensuring brand alignment across touchpoints and speeding up response delivery.
No matter the current state of your contact center, focusing on data fundamentals can improve your operations overall. Establishing sound data management practices in the contact center will improve operations and experiences overall, contribute to a true omnichannel experience, and make integrating new tech like GenAI tools much easier.
Improving data fundamentals enables organizations to achieve the promised benefits of GenAI and agentic AI tools because AI is only as intelligent as the data it can access and trust.
Good data enables faster AI implementation and deployment by eliminating extensive data preparation phases while well-structured data reduces the risk of hallucinations. Organizations that invest in data fundamentals will create the conditions needed for AI to deliver transformational rather than just incremental operational improvements.
Modern business relies on good, current data, and perfecting data management practices now will set you up for sustained success in the future. Data is one of the most valuable assets in any business, so isn’t it time you started treating it as such?