Skip to content

Outlook for Interaction Analytics

October, 2022
By Donna Fluss

Interaction (speech and text) analytics is celebrating its 20th year in the commercial market. Given this important milestone, I thought it would be interesting to consider the future outlook for this mission-critical solution.

While we talk a great deal about interaction analytics, the majority of “interaction” analytics used in contact centers today is still just speech analytics. Most companies know (and acknowledge) that they should be applying both speech and text analytics, given the large (and growing) volume of digital interactions being processed in recent years, but they are slow to adopt text analytics because it’s expensive. DMG estimates it will take another 4 – 6 years before there is a balance in the number of voice and text-based interactions being analyzed by interaction analytics solutions. This may happen primarily because the number of voice-based transactions is decreasing, giving an opportunity and incentive for companies to add in analysis of more of their digital interactions. The change will benefit businesses in having a more accurate view of why customers are reaching out to them.

A second major upside may be driven by an expansion of the categories of users within an enterprise that use IA. The contact center has traditionally been the main consumer of IA because they are the source of the input: call recordings, SMS, chat, email, etc. However, since contact centers handle issues and inquiries about most everything that happens in a company, this department is positioned to capture insights concerning the entire enterprise. This alone is a good argument to justify using IA as an company-wide business intelligence (BI) solution. To make it happen, companies need to alter their perspective. The companies that have applied IA broadly have realized much greater benefits and a more rapid return on investment (ROI) than those that have applied it primarily to improving and optimizing their contact center. 

The third significant opportunity for IA, and one that has picked up momentum during the past few years, is to embed an interaction analytics engine or a more complete application within a third-party solution such as call tracking, sales, marketing, collections, and more. Interaction analytics technology is highly valuable by itself because it can surface the underlying reasons why customers, prospects, and partners reach out to a company. However, when it is included as a core component of other solutions, it provides insights that substantially improve the outputs and benefits of these applications. 

A fourth and increasing use of IA is providing real-time guidance (RTG) to agents, supervisors, and other customer-facing employees. The cloud is an important enabler of RTG, as it can supply the processing power to operate IA in real time, cost effectively. The objective of these real-time solutions is to give agents the information or guidance they need to resolve an issue accurately, or successfully overcome objections and close a sale or collect overdue funds during the first contact. RTG solutions have been in the market for over 10 years, but this segment of the IA market is just coming into its own and is expected to realize very rapid growth as these applications are enhanced.

A fifth use of IA, which is also picking up momentum, is to perform analytics-enabled quality management (AQM). This is one of the earlier use cases of IA, even though adoption was slow due to its high cost. Organizations that purchased an IA suite were opposed to paying an additional (and often large) fee to use it for AQM. Now, as market for AQM solutions has become increasingly competitive, the cost of these applications has decreased at the same time as their functional capabilities have improved. AQM can be a very cost-effective approach for monitoring up to 100% of the voice and digital interactions received by companies. While AQM cannot accurately address all aspects of interactions, these solutions deliver better results and findings than manual QM environments, since contact centers typically do not have the resources to evaluate more than a few interactions per agent/month. AQM is also highly valuable because it provides a continuous stream of feedback to agents, enabling them to self-improve. 

Final Thoughts

As IA is embedded into more contact center and enterprise solutions, its uses will broaden throughout companies. New use cases for IA are constantly emerging as it is a highly practical solution that is effective by itself and generally more valuable when integrated into other applications and processes. In the last two years, transcription, an output from IA, has become standard, and after-contact summarization is one of the new capabilities that has captured the attention of the market. While this IT segment has reached an important milestone in its maturity, the opportunities and uses for it are just getting started.