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Making Speech Analytics Findings Actionable

Making Speech Analytics Findings Actionable

The speech analytics technology sector continues to grow rapidly. Despite the recession, the number of seats grew by 48% between 2008 and 2009, and the momentum in 2010 has been very strong. Many companies that started with small pilots in 2007 and 2008 have added additional seats during the last 12 months. Senior executives are starting to “get it,” and appreciate that speech analytics solutions can provide valuable insights into the reasons why customers and prospects call their organization.

There are many other uses of speech analytics, including: increasing first contact resolution, reducing average handle time, script adherence, identifying competitive situations, reducing customer attrition, identifying “at-risk” customers, improving the customer experience, identifying new revenue opportunities and new product ideas, and fraud prevention. While these are currently the most common uses of speech analytics, new ones are emerging on a daily basis.

The Current Market Challenge

The majority of speech analytics users are large organizations with a lot to gain from the insights these solutions can provide. Yet, despite the great potential and proven successes, a large number of companies are not realizing the benefits of speech analytics. This is because they are not able to apply their findings on a timely basis to address identified issues.

I’ve spoken to and worked with many organizations that have wonderful processes set up to identify the underlying reasons why customers call. Each month, they compile a package of reports that reflect the top call reasons. In some enterprises, this information is shared with the president, and in others just with contact center management. The problem is that while it’s interesting to identify call trends, it’s much more valuable to have an inter-departmental team set up to resolve the underlying issues or take advantage of the opportunities identified by the system.

Although the adoption of speech analytics has been rapid, best practices have not kept up with the technology. Enterprises that want to monetize their speech analytics investment need to use it as a change agent instead of as a reporting tool. This means that many organizations need to alter their approach to speech analytics because the findings themselves are valuable, but what is even more important are the actions taken based on identified insights.

Speech Analytics Hits a Critical Juncture

Few technologies break into the market without hiccups, and speech analytics is no exception. The question is what vendors will do to help their customers overcome these challenges and realize benefits. On the one hand, all the vendors really want to do is sell more software, as margins on software are much greater than those for professional services. On the other hand, if they don’t help build and share speech analytics best practices to improve the success rates of implementations, market interest and the adoption rate will wane.

It’s Time to Reset Expectations

It’s time for the speech analytics vendors to invest in making their solutions and implementations more actionable. While this remains a challenge, the vendors are making progress. The vendors are delivering more packaged offerings that come with libraries and reports.

Speech analytics is one of those solutions that require constant care and attention – clients who know how to use the systems will always be able to improve search results. Before making a purchase, end users need to understand that speech analytics requires dedicated staff with the analytical abilities to use the application and the political clout to effect change. And vendors need to deliver cost effective services that end users can afford to get them through the learning curve.

Ask the Experts


About 6 months ago we had a reduction in our supervisory staff. We’re now seeing the impact with high burnout of the supervisors we still have on staff. This has impacted our agent morale and productivity, which in turn, is impacting our customer satisfaction. We have 140 agents, 3 shifts (80 agents during day shift, 40 and 20 on the other two shifts). Our day shift is where the pain is most significant because we now only have 3 supervisors. The other two shifts have less call volume and they haven’t experienced any significant changes in productivity. What would be your recommendation for the number of supervisors for 80 agents? Can you please offer ideas on how to present to our management team the benefits of hiring 2 additional supervisors for the day shift?


Supervisors play many rolls in call centers. Typically, they are responsible for many administrative functions, including coaching agents, and also aid their team members by handling customers who demand or need higher-level assistance. The supervisor-to-agent ratio varies by call center. It generally ranges from a ratio of 1 supervisor to 10 agents to 1 supervisor for every 20 agents. Once call centers exceed the 1:20 supervisor to agent ratio it becomes very difficult for a supervisor to have any time to coach agents or handle escalated customer calls. This creates a cycle of stress that can negatively impact the first call resolution rate, overall customer satisfaction and quality scores, and agent satisfaction. When supervisors no longer have time to help agents, it compels agents to handle inquiries that they are not qualified to resolve. This hurts agent morale and results in much higher agent attrition rates, which are costly challenges for an organization.

Management increases the agent- to-supervisor ratio to save money; they may believe that this is better than cutting agents when budgets are tight. While this is true, it puts an additional burden on the call center when there is insufficient supervisory staff to support their agents. Agents are then told to do everything they can not to escalate calls to supervisors.
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DMG Consulting LLC is a leading independent research, advisory and consulting firm specializing in unified communications, contact centers, back-office and real-time analytics. Learn more at