Don’t be Fooled by Contact Center Data—Use Data Management and Analytics Instead | Calabrio
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Don’t be Fooled by Contact Center Data—Use Data Management and Analytics Instead

With the emergence of multi-channel communication in today’s contact centers comes an inherent challenge: accessing and understanding all the data created by those various channels.

Having a plan on what to do with the data and with whom to share the information is just as important as access to the data. After all, how else will you truly understand your customers’ motives, needs and satisfaction with your service?

You can bet your competitors are taking steps to understand all of this valuable data. And they likely face some of the same challenges you do:

  • Disconnects between the company’s strategic goals and contact center operations can create constant, unproductive, internal struggles between contact center leaders and executive management.
  • Current, out-of-the-box reports generated by business systems don’t meet custom business requirements and usually don’t integrate with other contact center systems.
  • Data quality and integrity suffers as business rules inevitably change, protocols are reconfigured, and dueling spreadsheets depict different data values and different conclusions.
  • A replacement, upgrade or reconfiguration of any component of the contact center operational system environment might change the way underlying operational data is logged, with ripple effects on all dependent reports.

It’s easy to understand why many contact center leaders find it difficult to integrate all of their multi-channel data—much of it generated by and stored in separate business systems—in order to leverage it to its full advantage. The rewards are well worth it, though, and they’re growing in value every day.

Constant innovation in contact center reporting and analytics solutions, for instance, more easily make critical customer insights available to other departments, and they can surface the true intent of a customer’s words. Let’s look at each one of these use cases.

Customer Insights can Drive Smarter Marketing

For instance, marketing teams benefit greatly from the insights gained during customer interactions, but historically they’ve not received ready access to them. According to Forrester, marketing teams can use customer insights derived from contact center analytics to:1

  1. Identify and fix common root causes of customer problems. Customer insights can help product teams more quickly uncover detailed information about product issues causing customer problems.
  2. Identify opportunities for new products and/or services. By resolving customer issues, product teams might spot a recurring topic indicating a prevalent market need for a new product, feature or service.
  3. Drive changes to marketing messages. Marketers can use customer insights to understand which marketing messages aren’t working, then can modify the messages as needed before investing more money into the existing campaign.
  4. Optimize marketing messages through instant customer evaluation. Marketers can use analytics-driven customer insights to test which messages resonate most strongly with target buyers.

Sentiment Analysis Reaches Beyond Words, to Give You Meaning

Beyond basic contact center reporting and analytics, today’s more innovative solutions actually can determine a caller’s “sentiment,” or what they mean, rather than just what they say.

For instance, Calabrio ONE automatically delivers a sentiment score for every voice-transcribed customer interaction. With it, contact center, marketing and customer experience decision-makers can access reliable customer sentiment data in order to quickly uncover the root causes of customer discontent while driving key business decisions.

As modern contact center reporting and analytics solutions evolve at a dizzying pace, the gap between them and the contact center leaders reluctant to adopt them continues to widen. If you’re one of these leaders, you can’t afford to wait any more.

1 Forrester, “Maximize Customer Data with Analytics.” May 2017.

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