Contact center analytics is a hot topic among contact center managers. Without analytics of some kind, its almost impossible to create effective strategies for improving business outcomes and performance metrics.
However, contact center analytics is changing, with new technologies and services evolving to meet the needs of call center managers in several different industries.
With this in mind, what does the future hold for contact center analytics? How will these new technologies change as new needs arise?
Heres what we see:
More Automation of Customer and Phone Agent Interaction Analyses
Its a well-known fact that contact centers simply dont have the resources to manually analyze every call made between phone agents and customers. In many cases, a contact center manager might have the time and resources to review one call per phone agent per week, which is often less than 1% of the contact centers total call volume.
This is a woefully insufficient amount of data to perform a thorough analysis of a phone agents performance.
What happens if you only reviewed a phone agents one good (or bad) call? This small data set makes it very difficult to efficiently establish agent trends which are used to make informed business decisions.
To counter this problem and make contact center analytics more useful to managers, some analytics programs are now automating the process of providing an analysis of customer and phone agent interactions. By automating the process, your sample size of analyses goes from 1% to 100%, providing a much clearer picture of performance in a shorter period of time.
Using this approach supervisors can quickly and easily identify the small percentage of call agents who would benefit from additional training, coaching or a performance improvement plan (PIP). The trend of automatic analysis is likely to grow as contact centers continue to focus on driving results and reducing the time needed for phone agent performance analyses.
Predictive Analytics Will Continue to Become More Important to Call Centers
Currently, Many Call center analytics programs focus on transcribing speech to text so that an analyst can review the text for compliance or potential problems. While useful for diagnosing potential issues, such basic review doesnt provide much in the way of predicting what will happen next or how to improve future results.
Newer and more sophisticated analytics programs leverage machine learning to apply behavioral models to their call analyses to predict future outcomes and prescribe the best next actions.
From here, the artificial intelligence program can take that behavioral analysis and use it to create a predictive model of future behaviors for customers. Examples of how contact center could use this information include:
- Predicting future call results.
- Identifying customers who are at risk of leaving the business relationship.
When applied to phone agents, this analysis can be used to improve agent performance.
As analytics programs become more sophisticated, its likely that youll see more companies using predictive contact center analytics programs than simpler business intelligence solutions. Additionally, as the machine learning algorithms that power these solutions continue to aggregate data, theyll likely become more accurate at making predictions.
More Call Centers Will Adopt Analytics Programs as a Key Tool for Improving Business Outcomes
As with any technology, adoption of contact center analytics programs will continue to increase as the technology becomes more familiar to businesses and evidence of positive business outcomes accrues.
Eventually, contact centers that dont leverage the power of predictive voice analytics for their customer interactions will be at a severe competitive disadvantage.
Numerous companies have already begun to use voice analytics software to considerably improve their business outcomes, allowing them to increase their revenue per agent.
History is littered with examples of businesses that have gained a significant advantage over competitors by adopting key technologies faster and being more adaptable to change.
Overall, the future of contact center analytics is looking smarter, more proactive than reactive, and more ubiquitous all the time.