Automating Small Tasks in Contact Centres

In today’s fast-paced contact centre environments, even small inefficiencies can add up to significant time losses. Automating simple, repetitive tasks can dramatically boost productivity, reduce human error, and allow operators to focus on delivering a better customer experience. This blog explores just one example of automation doing what it does best – detecting and extracting key data, and updating your systems automatically.

Finding Data Automatically with Text Detection

One of the simplest and most effective automations involves using workflows to detect and extract relevant data from inbound messages. Consider an example where customers frequently provide reference numbers, order IDs, or tracking numbers within their inquiries. Instead of manually searching for and copying these details, automation can handle this task using straightforward text detection.

With the Find Text action in Gnatta workflow, you can search for specific patterns of text using regular expressions (regex). This allows for precise detection of relevant strings, such as:

• Order numbers: ORD\d{6}
• Tracking numbers: TRK\w{10}

When a message is received, the workflow scans the content and captures the specified patterns, significantly reducing the need for manual scanning by operators.

For detailed steps on setting up text detection workflows, see our guide: Detecting & Extracting Data

Updating Data Fields Automatically

Once data is extracted, the next logical step is to update relevant fields within your system. Imagine a scenario where the detected order number needs to be added to the customer’s case or interaction record. Instead of requiring manual input, automation can populate these fields using the output from the Find Text action.

By leveraging workflows to update data fields, operators avoid repetitive data entry, freeing up their time for more complex and value-added tasks. This automation improves efficiency and accuracy while ensuring that important details are captured without delay.

Learn more about automating data field updates in our guide: Updating Data Fields.

Going Beyond: Triggering External Checks

Automation doesn’t need to stop at finding and updating data within a single system. A powerful next step is integrating external systems to further enhance the operator’s experience. Suppose an order number is detected in a customer message—a workflow could automatically trigger a request to an Order Management System (OMS) to check the status of that order. The result could then be returned and displayed for the operator, eliminating the need for them to look it up manually.

This kind of automation reduces handle time, minimises context switching, and streamlines the customer support process. Here’s a simple example of how this could flow:

1. Text detection: Extract the order number from the inbound message.
2. Field update: Automatically populate the case record with the order number.
3. External system query: Trigger an API call to the OMS to fetch the order status.
4. Information display: Present the order status directly to the operator.

The Bottom Line: Clicks Saved, Efficiency Gained

Small automations, such as text detection and field updates, are the building blocks of a more efficient contact centre. By reducing manual tasks and integrating additional workflows, operators can work smarter, not harder—delivering faster and more accurate responses to customers. The possibilities for streamlining tasks are vast, and starting with these simple steps can pave the way for more advanced automations in the future.