DATA MANAGEMENT
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-itand-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.
ONCE YOUR ORGANIZATION HAS SOLID DATA MANAGEMENT PRACTICES, IT’ S TIME TO LOOK AT ADDING GENAI CAPABILITIES.
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.
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-theclock 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.
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.
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