5 Ways to Define What Enterprise-Ready Means for Speech Analytics

When Forrester Research published its Wave on speech analytics solutions they identified CallMiner as the solution with “most advanced, enterprise-ready speech analytics functionality.”   That’s a great description, but what does “enterprise-ready” really mean?   After all, doesn’t every “enterprise” have their own set of objectives and requirements?

The answer is of course “yes”, but there are a significant range of features and benefits within speech analytics software solutions that should be considered as common or even baseline for virtually any organization.  A core speech analytics value proposition is deriving insight from calls by converting unstructured contact center conversations into structured intelligence.  That’s making big data actionable!  But there are several speech analytics solution components to consider in order to separate an enterprise-ready analytics application from what can amount to as an “IT science experiment”.

Following are five of these considerations:

1. API or Application Complete
2. Time to Insight
3. Self-Service
4. Security
5. Multichannel

The above considerations are just a few examples to think about when deploying a speech analytics solution that’s ready for your enterprise.  Core speech-to-text technology is certainly important, but it does not stand alone as a value point.  How a capable speech analytics solution is packaged with features that support rapid deployment, immediate insight and ease of use contribute significantly to what will be considered an enterprise-ready speech analytics solution.

Following are some specific speech analytics solution components to look for beyond the previously mentioned to ensure you are on the enterprise-ready track for a speech analytics solution:

• Application Scalability – Do not overlook the importance of how speech analytics can (or cannot) scale for your organization beyond the basics of Software as a Service. For example, methods for data retention with indexing enable trend comparison over time with search and find speed.   Presentation of that data is also critical without bogging down due to multiple simultaneous users.  For enterprise-ready confidence look for speech analytics solutions that deliver scalability tested and proven for large numbers of simultaneous users.
• Speaker Separation – Make sure you can identify customer and agent speakers in categorized transcription. Additionally, look for categories that apply to agent behaviors such as ownership and empathy help provide insight into how employees encourage customer experience values.
• Packaged Categorization – Look for speech analytics solutions that help you get started with packaged categorization. Bundled key words and phrases, acoustic measures, outliers (such as excessive silence) and search criteria along with scoring will get you jumpstarted.
• Automated Scoring – Users can easily focus on interactions where attention is needed, or kudos are in order if automated scoring is available within an easy to use interface. Customization with category tailoring and score weighting in a self-service model when available will allow tuning for specific requirements.
• Organic Discovery – Look for a speech analytics solution that can bring attention to the unexpected. Visualization that identifies trending topics spoken by customers or agents can be invaluable in driving to a root cause.

Discover how you can you use speech analytics to optimize your customer experience, improve agent performance and ensure your contact center remains compliant with important telephony-based requirements.   To get started review the CallMiner Eureka and Amazon Connect Solutions Space here.