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Omningage IQ – Reporting and Beyond

The “Cinderella” of contact centre technology

There’s an old joke about a sales rep who tried and failed to sell toilet paper holders to a contact centre manager because he couldn’t explain what reports they produced.



Reporting is often seen as the “Cinderella” of contact centre technology. No one likes it much, but equally, no-one can do without it.


Omningage is staffed by contact centre operations professionals and technology experts who understand the importance of reports.

Omningage IQ (IQ)

This is our current reporting suite. Touqeer Nasir, Omningage’s Head of Product Development and Integrations describes it as a providing a “360-degree view” of everything that happens in the contact centre.


“Our original idea was to provide our customers with the top 10 reports they would need to run their contact centres, which were not already provided on Amazon Connect”.


IQ has gone well beyond that aspiration. IQ now consists of 11 sections containing 22 reports. Each section covers a different aspect of contact centre operations with the main sections covering contacts, queues, SLA and agent performance.


IQ reports, with their quantitative data, complement the more qualitative insights management can get from looking into the content of interactions through the Interaction Explorer page.


Our Wallboards have been so successful that we have spun them off as a separate product in themselves. Touqeer described the latest work being done on wallboards as “exciting”.


Omningage provides users with the ability to design their own wallboards, using a template on which users can put a wide selection of “widgets” that show a variety of data. Users can arrange these on the page in any way that they see fit and select their own theme and colour scheme.


In addition, users will also be able to configure alerts delivered by email based on key parameters and apply settings to show hourly and daily views of data.


Deploying the wallboard reports is very easy, you configure them on your computer, then as you save them, it generates a dedicated URL which you simply put into the browser display on the wall monitor. For managers working from home, they can display their wallboards on a second or third monitor in their home office.


What does the future hold?

Predicting future trends is always difficult, but there are a few developments that look likely.


As speech analytics and sentiment analysis becomes more widely available, reporting will cover it.


Omningage is already working on prototype reporting with a customer that shows average positive / negative customer sentiment by agent, by team, by queue and by language spoken. Further developments of this reporting will include algorithms to estimate what is “normal”, so that users can better evaluate the results that they see. Debtors being called by collections agents are unlikely to be glad to receive a call, so users will need to understand if the results they see are a cause for concern by knowing what a “normal” level of negative sentiment is.


Another coming trend is the use of Artificial Intelligence (AI) to analyse and “curate” the enormous volumes of data that contact centres generate.


AI is very good at looking at large volumes of data and identifying correlations. Here are some probable use cases:

  1. Analysing negative sentiment in customers’ responses to bots. Reporting AI will look at negative sentiment data from customers’ interactions with bots and compare that to incidences of key phrases, so identifying what provoked the negative sentiment. It will also compare combinations of negative sentiment and key phrases with calls where customers either abandoned the interaction or escalated to a human agent. Using this data, bot programmers can adjust the scripting/logic and reduce the escalation/abandon rate.
  1. Analysing negative customer sentiment in comparison with interaction volumes, key phrases, FCR status, how long the customer spent in the queue or aspects of customer history. Once again, by looking at what parameters come up in calls with high levels of negative sentiment vs calls with low levels of negative sentiment, users can uncover the root causes of both negative and positive sentiment. As a result, they can work to eliminate behaviours or processes leading to negative sentiment and reinforce behaviours and processes leading to positive sentiment.
  1. Using negative customer sentiment, speech analytics and wrap up codes, a report could be developed to identify customers needing a call back from a retention team, then output their data in a form that could be loaded into a dialler. The retention team could proactively call back customers likely to stop using their services/products.

Using agent sentiment, an AI-powered report could assess agent performance based on a number of parameters and provide insights to supervisors and coaches where agents might need attention.

Next steps

If you’d like to find out where Omningage is going with Amazon Connect, and what we can do for your contact centre, get in touch with your AWS partner or your local Omningage Sales Director.

To discuss your requirements, arrange a demonstration or ask for a proof of concept, please use the below details.

Contact Us

+44 330 088 3940



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