表紙
市場調查報告書

互動分析產品市場(2020-2021)

2020 - 2021 Interaction Analytics Product and Market Report

出版商 DMG Consulting LLC 商品編碼 950704
出版日期 內容資訊 英文
商品交期: 最快1-2個工作天內
價格
互動分析產品市場(2020-2021) 2020 - 2021 Interaction Analytics Product and Market Report
出版日期: 2020年07月23日內容資訊: 英文
簡介

COVID-19大流行刺激了交互分析(IA)市場,世界各地的公司開始欣賞到交互分析解決方案的好處。這些解決方案可以近乎實時地基於歷史記錄來捕獲和分析語音和數位交易,以洞悉客戶的需求和願望以及客戶的情緒。在COVID-19大流行期間,IA通常是瞭解公司情況,公司經營狀況以及客戶如何看待品牌的唯一方法。做到了。由於有如此多的勞動力被迫搬家,公司可以利用IA解決方案快速識別客戶問題,準備代理商和自助服務解決方案,並處理他們正在經歷的大量互動。 IA解決方案還用作監視工具,以追蹤在家工作的員工的績效。一些具有實時IA功能的公司可以在COVID-19大流行期間提供出色的服務。

樣品圖

該報告《交互分析產品市場》是DMG Consulting語音分析領域的年度報告的第15版。我們正在調查聯絡中心和與服務相關的交互(語音和文本)分析,以提供市場預測,趨勢和挑戰,價格,競爭格局以及關鍵參與者的概況。

內容

第1章執行摘要

第2章簡介

第3章DMG諮詢研究方法

第4章定義的互動分析

  • 交互分析應用程序構建塊
  • 高級功能概述

第5章IA企業趨勢和挑戰

  • IA企業趨勢
  • IA企業的挑戰

第6章IA市場創新

  • 新功能
  • 新功能

第7章語音分析的演進

  • AI和IA:更智能的交互分析

第8章公司IA

    IA作為企業戰略工具

第9章IA運營:擴大IA運營的優勢

  • 解碼VoC和CX
  • 情感檢測和情感分析
  • AQM:自動化且準確的恆定運行

第10章DMG對交互分析的未來的預測

第11章IA市場活動分析

第12章IA市場的採用

第13章IA市場預測

第14章IA競爭情況

  • 感興趣的供應商
  • 公司快照
  • 產品信息

第15章實施IA和ROI分析

  • 系統管理
  • 安全性和合規性
  • 商業智能,報告,儀表板
    • KPI

第16章IA價格

  • IA前提定價
  • IA基於雲端的定價

第17章IA滿意度調查和分析

  • 調查結果和分析摘要:供應商類別
  • 調查結果和分析摘要:產品功能
  • 調查結果和分析摘要:產品有效性
  • 客戶背景和見解
    • 使用IA的業務部門
    • IA的優勢
    • 實施Insight之前最需要的東西
    • 所需的增強功能/附加功能
    • 其他評論

第18章公司簡介

  • Calabrio
  • CallMiner, Inc.
  • Clarabridge
  • NICE
  • OnviSource
  • Sestek
  • Verint Systems
  • Xdroid

附錄:IA供應商目錄

目錄

This is DMG Consulting's 15th annual report on the speech analytics sector. The 2020-2021 edition has been renamed as the Interaction Analytics Product and Market Report to include the increasing number of solutions that provide integrated speech and text functionality to address voice and digital interactions. The focus of the Report is contact center and service-related uses of interaction (speech and text) analytics. The Report also explores the broader uses of interaction analytics throughout enterprises.

The COVID-19 pandemic has reinvigorated the interaction analytics (IA) market. Enterprises around the world have come to appreciate the advantages of these solutions, which capture and analyze voice and digital transactions on a historical, near-real-time and real-time basis. IA solutions provide insights into customer needs and wants, as well as their emotions and sentiment. During the coronavirus crisis, IA was often the only means for companies to know what was happening in their company, how well they were performing, and how customers perceived their brand.

As much of the workforce was forced to relocate to their homes, companies have relied on IA solutions to rapidly identify customer issues so that agents and self-service solutions could be prepared to handle the high volumes of interactions that they were receiving. IA solutions are also being used as oversight tools to keep track of employees' performance while they are working at home. A few companies with real-time IA capabilities have even been able to "take the pulse" of their customers and employees on an ongoing basis, which has allowed them to provide outstanding service during this unprecedented crisis.

Interaction analytics solutions give companies access to the unfiltered voice of the customer (VoC) and voice of the employee (VoE). IA provides a balanced view of what is happening with their customers across all channels, departments and media. These solutions can help reveal what is trending in each channel and on an overall basis, so companies can respond rapidly and accurately. Organizations can collect customer feedback passively, on a continuous basis. This can help companies achieve the goal of measuring the customer experience and sharing the data on a timely basis so that necessary changes can be made throughout the enterprise to optimize the overall customer journey, not just the quality of the service in the contact center.

Vendors are continuing to invest heavily in research and development (R&D) initiatives for IA solutions. The primary area of investment for the next few years will be in artificial intelligence (AI). Innovations in AI will be used to improve the accuracy and relevance of IA findings, to more fully automate the quality management (QM) and coaching process, to improve the effectiveness of gamification, and to generate the models required to apply predictive analytics to many functions, including customer and employee retention.

The 2020-2021 Interaction Analytics Product and Market Report provides an in-depth analysis of the IA market, the competitive landscape, product innovation, as well business and servicing trends and challenges. It closely examines market activity and presents 5-year market projections. The Report is intended to help leaders and managers in contact centers, back offices, IT departments and the executive suite select the best IA solution and vendor to meet their organization's current and future needs. The Report also examines customer satisfaction with vendors, products and pricing, and offers implementation best practices to help users succeed with their IA initiatives.


The Report features 7 leading and contending vendors who offer IA as a part of a broader workforce optimization (WFO) offering or as a best-of-breed solution. The 7 vendors are: Calabrio, Clarabridge, NICE, OnviSource, Sestek, Verint and Xdroid. An eighth vendor, CallMiner, is covered at a higher level.


Key Elements of this Report:

  • IA defined: how it works, and a high-level overview of the key functional capabilities in the 7 featured IA solutions
  • Current market trends and challenges that are driving vendor innovation and enterprise investments
  • Vendor research and development (R&D): recent feature and functionality enhancements and near-term updates planned for the next 12 - 18 months
  • Examination of how AI-enabled technologies are making significant contributions and improvements to interaction analytics
  • A look at how IA is being leveraged as a strategic tool across the enterprise, extending its benefits
  • The essential role of IA in understanding the customer journey and operationalizing the VoC, the CX and quality management, by providing a data-driven approach to identifying the best course of action for each transaction
  • Market activity and market share analysis, adoption rate and 5-year projections
  • Analysis of the IA competitive landscape, including a discussion of the changing dynamics, expanding use cases, new and emerging competitors, and a high-level overview of the 7 vendors and product offerings featured in this analysis
  • IA implementation analysis, including vendor implementation methodology and best practices, maintenance and support, workshops, training and professional services
  • Pricing comparison and analysis for on-premise and cloud-based implementations
  • Comprehensive vendor satisfaction survey results that measure and rank vendor approval ratings across 10 vendor categories, 10 product capabilities and 5 product effectiveness categories
  • Detailed company reports for the 8 vendors covered in this Report, including product functionality and future product development plans
  • IA Vendor Directory

Report Highlights:

  • IA solutions have proven their value during the coronavirus pandemic: IA solutions have been instrumental in facilitating the transition of the contact center workforce to work-at-home (WAH) employees. Interaction analytics give companies invaluable insights into customer and employee needs, in their own unfiltered "voices," so that employees and self-service can be prepared to address emerging issues.
  • Interaction analytics is essential in the world of virtual commerce: As the digital transformation has accelerated and omni-channel service becomes the norm, companies need insight into what is occurring in all media. Interaction analytics gives a complete view of activity in all channels across the enterprise and on an overall basis. This allows companies to identify issues and respond quickly. It also helps businesses fully appreciate all aspects of the customer journey.
  • IA solutions can passively capture customer feedback: Interaction analytics can be used to measure all aspects of the service experience. Sharing the findings from IA with all customer-facing departments helps organizations deliver an outstanding customer experience, cost effectively.
  • Artificial intelligence capabilities are mission-critical for the future of IA: Artificial intelligence will be used to improve company performance and the customer experience (CX) in all channels and touchpoints. Enterprises that want to succeed in the "new normal" must invest in automation, analytics and artificial intelligence to establish a technology framework to support their new business models.

SAMPLE FIGURE

Table of Contents

1. Executive Summary

2. Introduction

3. DMG Consulting Research Methodology

  • 3.1 Report Participation Criteria

4. Interaction Analytics Defined

  • 4.1 Interaction Analytics Application Building Blocks
  • 4.2 High-Level Functional Summary

5. IA Enterprise Trends and Challenges

  • 5.1 IA Enterprise Trends
  • 5.2 IA Enterprise Challenges

6. IA Market Innovation

  • 6.1 New Features
  • 6.2 Emerging Capabilities

7. The Evolution of Speech Analytics

  • 7.1 AI and IA: Interaction Analytics Gets Smarter

8. IA for the Enterprise

  • 8.1 IA as a Strategic Tool for the Enterprise

9. Putting IA to Work: Operationalizing IA Extends its Benefits

  • 9.1 Deciphering the VoC and the CX
  • 9.2 Emotion Detection and Sentiment Analysis
  • 9.3 AQM: Automated, Accurate, and Always On

10. DMG's Projections for the Future of Interaction Analytics

11. IA Market Activity Analysis

12. IA Market Adoption

13. IA Market Projections

14. IA Competitive Landscape

  • 14.1 Vendors of Interest
  • 14.2 Company Snapshot
  • 14.3 Product Information

15. IA Implementation and ROI Analysis

  • 15.1 System Administration
  • 15.2 Security and Compliance
  • 15.3 Business Intelligence, Reporting and Dashboards
    • 15.3.1 KPIs

16. IA Pricing

  • 16.1 IA Premise-Based Pricing
  • 16.2 IA Cloud-Based Pricing

17. IA Satisfaction Survey and Analysis

  • 17.1 Summary of Survey Findings and Analysis: Vendor Categories
    • 17.1.1 Vendor Satisfaction by Category and Customer
  • 17.2 Summary of Survey Findings and Analysis: Product Capabilities
    • 17.2.1 Product Capabilities Satisfaction Ratings, by Category and Customer
  • 17.3 Summary of Survey Findings and Analysis: Product Effectiveness
    • 17.3.1 Product Effectiveness Satisfaction, by Category and Customer
  • 17.4 Customer Background and Insights
    • 17.4.1 Business Units Using IA
    • 17.4.2 Top 3 - 5 Strengths of IA
    • 17.4.3 Top 3 - 5 Most Wished for Insights Pre-Implementation
    • 17.4.4 Desired Enhancements/Additional Capabilities
    • 17.4.5 Additional Comments

18. Company Reports

  • 18.1 Calabrio
  • 18.2 CallMiner, Inc.
  • 18.3 Clarabridge
  • 18.4 NICE
  • 18.5 OnviSource
  • 18.6 Sestek
  • 18.7 Verint Systems
  • 18.8 Xdroid

Appendix: IA Vendor Directory

TABLE OF FIGURES

  • Figure 1: What is Interaction Analytics?
  • Figure 2: Interaction Analytics Technology Building Blocks
  • Figure 3.1: High-Level Functional Summary
  • Figure 3.2: High-Level Functional Summary
  • Figure 4: 2020 Enterprise IA Trends
  • Figure 5: Enterprise IA Challenges in 2020
  • Figure 6: New Product Features, by Vendor
  • Figure 7: Future Enhancements, by Category
  • Figure 8: Speech Analytics Maturity Model
  • Figure 9.1: Artificial Intelligence, Machine Learning and Automation
  • Figure 9.2: Artificial Intelligence, Machine Learning and Automation
  • Figure 10: Enterprise IA
  • Figure 11.1: IA for the Enterprise
  • Figure 11.2: IA for the Enterprise
  • Figure 12.1: Strategic IA Opportunities
  • Figure 12.2: Strategic IA Opportunities
  • Figure 13.1: Operationalizing IA
  • Figure 13.2: Operationalizing IA
  • Figure 14.1: Using Interaction Analytics to Analyze the Voice of the Customer/CX
  • Figure 14.2: Using Interaction Analytics to Analyze the Voice of the Customer/CX
  • Figure 15.1: Emotion Detection and Sentiment Analysis
  • Figure 15.2: Emotion Detection and Sentiment Analysis
  • Figure 16: Analytics-Enabled Quality Management
  • Figure 17: AI and Machine Learning Enhance the QM Process
  • Figure 18.1: AQM
  • Figure 18.2: AQM
  • Figure 19: IA Market Activity, as of March 31, 2020
  • Figure 20: Interaction Analytics Market Share Based on Seats, as of March 2020
  • Figure 21: Interaction Analytics Customers and Seats by Vendor, 2019 vs. 2018
  • Figure 22: Interaction Analytics Customer Trends by Vendor, 2013 - 2019
  • Figure 23: Interaction Analytics Customer Trends by Vendor, 2013 - 2019
  • Figure 24: Interaction Analytics Seat Trends by Vendor, 2013 - 2019
  • Figure 25: Interaction Analytics Seat Trends by Vendor, 2013 - 2019
  • Figure 26: Interaction Analytics Contact Center Adoption Rate, 2008 - 2019
  • Figure 27: Interaction Analytics Market Growth Rate Projections Based on Seats, 2020 - 2024
  • Figure 28: IA Competitive Landscape
  • Figure 29.1: Company Information, as of March 2020
  • Figure 29.2: Company Information, as of March 2020
  • Figure 30: Product Information
  • Figure 31.1: Implementation and ROI Analysis
  • Figure 31.2: Implementation and ROI Analysis
  • Figure 32.1: Administration/Design and Content Development Environment
  • Figure 32.2: Administration/Design and Content Development Environment
  • Figure 33.1: Security and Compliance
  • Figure 33.2: Security and Compliance
  • Figure 34.1: Business Intelligence, Reporting and Dashboards
  • Figure 34.2: Business Intelligence, Reporting and Dashboards
  • Figure 35.1: KPIs
  • Figure 35.2: KPIs
  • Figure 36: Pricing for a 250-Seat Premise-Based IA Solution
  • Figure 37: Pricing for a 250-Seat Cloud-Based IA Solution
  • Figure 38: Customer Survey Rating Categories
  • Figure 39: Average Vendor Satisfaction Ratings, by Category
  • Figure 40: Current Product Satisfaction Ratings, by Customer
  • Figure 41: Implementation Satisfaction Ratings, by Customer
  • Figure 42: Training/Workshops Satisfaction Ratings, by Customer
  • Figure 43: Ongoing Service and Support Satisfaction Ratings, by Customer
  • Figure 44: Professional Services Satisfaction Ratings, by Customer
  • Figure 45: Product Innovation Satisfaction Ratings, by Customer
  • Figure 46: Responsiveness to Product Enhancement Requests Satisfaction Ratings, by Customer
  • Figure 47: Vendor Communication Satisfaction Ratings, by Customer
  • Figure 48: Pricing Satisfaction Ratings, by Customer
  • Figure 49: Overall Vendor Satisfaction Ratings, by Customer
  • Figure 50: Product Capabilities Satisfaction Ratings, by Category
  • Figure 51: Omni-Channel Capabilities Satisfaction Ratings, by Customer
  • Figure 52: Artificial Intelligence and Machine Learning Capabilities Satisfaction Ratings, by Customer
  • Figure 53: Accuracy and Tuning Capabilities Satisfaction Ratings, by Customer
  • Figure 54: Automated Discovery of Issues that have not been Pre-Defined Satisfaction Ratings, by Customer
  • Figure 55: Correlation of Disparate but Related Issues/Topics Satisfaction Ratings, by Customer
  • Figure 56: Automated Root Cause Analysis Satisfaction Ratings, by Customer
  • Figure 57: Analytics-Enabled Quality Management Capabilities Satisfaction Ratings, by Customer
  • Figure 58: Emotion Detection Satisfaction Ratings, by Customer
  • Figure 59: Sentiment Analysis Satisfaction Ratings, by Customer
  • Figure 60: Ease of Configuration, Use and Maintenance Satisfaction Ratings, by Customer
  • Figure 61: Product Effectiveness Satisfaction Ratings, by Category
  • Figure 62: Ability to Understand the Omni-Channel Customer Experience Satisfaction Ratings, by Customer
  • Figure 63: Ability to Understand the Voice of the Customer and Customer Preferences Satisfaction Ratings, by Customer
  • Figure 64: Ability to Provide Agents with Contextual Real-Time Guidance/ Next-Best-Action Recommendations Satisfaction Ratings, by Customer
  • Figure 65: Ability to Predict/Anticipate Customer Behaviors Satisfaction Ratings, by Customer
  • Figure 66: Ability to Identify Relevant and Actionable Data Satisfaction Ratings, by Customer
  • Figure 67: What business units are using the output/insights results from interaction analytics?
  • Figure 68: What are the top 3 - 5 strengths of your IA solution?
  • Figure 69: Based on your experience, what are the top 3 - 5 things you wish you had known prior to implementing an interaction analytics solution?
  • Figure 70: What product enhancements/additional capabilities would you like to see?
  • Figure 71: Additional comments about your experience with the vendor and/or solution.