CallMiner and Amazon Connect: A Perfect Match for your Contact Center

By Allen Shapiro, Ronald Mueller

CallMiner and Amazon Connect: A Perfect Match for your Contact Center

This paper highlights the key functionalities of the CallMiner conversational analysis platform and explains why it works perfectly with Amazon Connect, a leading cloud contact center solution offered by Amazon Web Services (AWS). Whether you are an existing customer of Amazon Connect or someone who wants to launch (or re-engineer) your contact center from scratch, this paper can give you insights into why these two tools are a great fit and how Macrosoft can help you along the way.

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Background

As a leading-edge technology and services provider, Macrosoft maintains long-term partnerships with select industry leaders and technology specialty companies. These partnerships allow us to bring the best-in-class thinking and development services to our clients. We are active partners of both CallMiner and Amazon Web Services. Macrosoft has dedicated and certified teams to help build your contact center using the best technology of both toolsets.

Introduce CallMiner to your Amazon Connect Solution

CallMiner Eureka is a cloud-based customer engagement analytics platform that uses artificial intelligence (AI) to transform your Amazon Connect voice conversations into structured data and analyzes that data to uncover powerful business insights about your customers, your products and services, and contact center performance.

AWS and CallMiner

This integration enables Amazon Connect to send customer interaction data (recordings and call metadata) to Eureka for analysis, using an Amazon Kinesis data stream. Eureka automatically transcribes, categorizes, and scores those customer interactions to create intelligence at a scale that leads to better customer experience, improved contact center efficiency, and reduced regulatory, compliance, and legal risks. 

CallMiner and Amazon Connect work perfectly together

CallMiner and Amazon Connect are a perfect match because of many reasons. Here are some of the key points:

  • Easy integration

With AWS Kinesis data stream, you can transfer call recordings and metadata to Call Miner’s cloud platform with just a few simple steps in the Amazon Connect UI. No integration development is needed.

  • Speed to Insight

Easy integration leads to rapid actionable insights. Working with Amazon Connect and CallMiner, all calls are recorded in Amazon Connect, and calls are transferred to CallMiner for transcription and analysis. Actionable insights come the next day.

  • Comprehensive Metadata List

Amazon Connect captures a comprehensive metadata list on all calls, including information on the call itself, the customer and the agent(s) that assisted on the call. Amazon Connect also keeps the entire contact flow and routing profile as metadata, which is very helpful for CallMiner to use in its analytics.

  • Contact flow: contact flow defines every step (and the timestamp of each step) that a customer takes after they dial your number. Metadata records of contact flow include the options a customer selects within the Interactive voice response (IVR) system and waiting for queue information. CallMiner can take in these data to create automatic scoring such as customer satisfaction scores, as well as calculating first call resolution.
    • Routing profile: routing profile defines all agent operations in your contact center. It keeps a hierarchy of agent management within the contact center, along with real-time records of an agent’s team assignment, availability, work schedule, assigned duties and queues as well as post-call activity records. CallMiner can utilize this data to create contact center efficiency and agent quality scores.

These two capabilities within Amazon Connect are extremely valuable to the analyses done within Call Miner to assess and understand customer satisfaction, customer effort, and customer experience as well as to assess call center efficiency and productivity. Having Amazon Connect pass these two forms of metadata to Call Miner on a call-by-call basis makes Call Miner results a lot more unsightly and actionable.

What does CallMiner have to offer you – so much more than just call transcription

More and more companies are realizing their call recordings are a very valuable company asset. With other AWS services such as Amazon Transcribe, users can get transcriptions of calls and then do text analysis on them. However, such a pipeline misses a key part of customer engagement analysis: the acoustic measures of the speech such as tone, agitation, and sentiment. Just looking at transcriptions and test analysis from the transcriptions loses all the valuable acoustic measures, which is why we recommend a CallMiner subscription along with your Amazon Connect contact center as a best-practices combination.

Among many other things, CallMiner offers:

  • The searchable and playable transcript allows the user to search any phrase in a call and jump directly to where it happened so you can locate your keywords without listening to the whole call. Silence periods are also captured and are searchable.
  • Omni-channel analysis. In addition to call recordings, Amazon Connect also provides the capability to record chat interactions and these can also be provided to the CallMiner client. (Call Miner can also accept many other interaction channels including: text messages; emails; Twitter; surveys and others.)
CallMiner Omni Channel Analysis
  • Automated call categorization and scoring to achieve QA automation and create actionable insights.
Call Categorization
  • Customer Journey mapping: the omnichannel journey mapping reveals the true customer journey across all communication channels.
Customer Journey Mapping
  • Agent performance analysis and data visualization. CallMiner provides a built-in easy-to-use dashboard. It can also be integrated seamlessly with Tableau for advanced data visualization
Agent Performance
  • Easy and fast integration: It only takes a few steps and as quickly as two business days for the implementation of speech analytics to go live if you are an existing Amazon Connect customer. Compare that to implementations of speech analytics with other contact center software platforms where the implementation can take weeks or even months.

Engage with Macrosoft today for efficient implementation and excellent ongoing support

Macrosoft proudly presents itself as an APN partner of Amazon Web Services and a strategic partner of CallMiner. We have technicians certified in both services to help get your contact center up and running with actionable insights from CallMiner’s conversational analytics. Get a quote from Macrosoft today and see how we can help take your customer engagement practices to a new level.

Download as PDF

Download the entire paper as a PDF document for free and refer this in future

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By Allen Shapiro, Ronald Mueller | September 30th, 2021 | CallMiner

About the Author

Allen Shapiro, Director – CCM Practice

Allen Shapiro

Allen brings more than 25 years of diverse experience in Marketing and Vendor Management to Macrosoft Inc. As the Managing Director of our Customer Communications Management (CCM) practice, Allen leads the Onshore and Off-shore CCM development teams. Additionally, Allen oversees pre-sales activities and is responsible for managing the relationship with our CCM software provider Quadient.

Dr. Ronald Mueller Chairman and Founder of Macrosoft

Ronald Mueller

Ron is the Chairman and Founder of Macrosoft, Inc. He heads up all company strategic activities and directs day-to-day work of the Leadership Team at Macrosoft. As Macrosoft’s Chief Scientist, Ron defines and structures Macrosoft’s path forward. Ron's focus on new technologies and products, such as Cloud, Big Data, and AI/ML/WFP. Ron has a Ph.D. in Theoretical Physics from New York University and worked in physics for over a decade at Yale University, The Fusion Energy Institute in Princeton, New Jersey, and at Argonne National Laboratory.

Ron also worked at Bell Laboratories in Murray Hill, New Jersey., where he managed a group on Big Data. Ron's work focused around the early work on neural networks. Ron has a career-long passion in ultra-large-scale data processing and analysis including predictive analytics, data mining, machine learning and deep learning.

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