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Businesses are losing $62 billion per year through poor customer service (Serial switchers strikes again, NewVoiceMedia, Jan. 2016). This means the new goal must be getting every interaction right.
Forrester Research predicts that by 2020, insights-driven businesses, like Baidu and Netflix will quadruple their revenue from $333 billion to $1.2 trillion, growing eight times faster than global GDP (Top Five Imperatives To Win In The Age Of The Customer, May 23, 2017).
Customer-centric companies like these are a real threat to a lot of businesses who choose to prioritize areas like manufacturing and distribution, instead of better understanding their customer needs and wants and delivering personalized experiences.
To deliver such experiences, you need insights; but to get insights, you need to start using all your data the right way. Once you get to a phase when you no longer have data silos across business systems, it is important to start looking for a good customer, employee, and operational analytics application. And here are the top three reasons why:
No one would argue that customer retention is critical for survival. Your brand and company Net Promoter Score (NPS) is constantly being reevaluated with every interaction handled and socially-shared commentary by your customer base.
Back in the day, a negative customer experience would simply make interesting conversation over coffee. But with the advent of social media, customers that are not able to resolve issues, can blast their complaints to a global audience that will hear about any shortcomings your business may have.
A lot of companies out there focus more on customer acquisition than on customer retention. But did you know that it costs five times as much to attract a new customer than to keep the existing one, and if you only increased your customer retention rates by 5% your profits could increase by 25% to 90% (Customer Acquisition Vs. Retention Costs, Invesp, Dec. 2015).
The best way to increase your customer retention rate is to improve customer experience.
Your front-line agents are also a crucial element to your customer experience. By gaining visibility into your agent interactions you can make better decisions.
But do you really know what is going on? Are you able to easily see the whole picture when it comes to your agent performance?
Traditionally, agent behavior analysis has been based on a set of standardized aggregated metrics that were supposed to summarize good agent performance. But to provide good customer service, aggregated metrics just don’t cut it.
Granularity and automation are needed to look for negative behavioral patterns (placing customers immediately on hold, flashing Not Ready while Ready, etc.) in your agent performance and flag them immediately.
The ROI in this case can be simple. As an example, let’s assume a fully loaded agent cost of $65K. That translates to $280/day/agent. If we manage to identify 15 mins of lost time for every agent day and assume a 300-agent contact center. It translates to $2700/day which over the course of 220 work days in a year is just under $600K!
And that is not even considering the impact a negative behavior may have on the customer experience or revenue opportunities.
Most firms are swimming in data, but they’re only using about a third of it. Worse, only 29% say they are good at translating the result of data and analytics into measurable business outcomes (Top Five Imperatives To Win In The Age Of The Customer, May 23, 2017).
As a matter of fact, the top two challenges preventing organizations from making use of analytics are “ensuring data quality from a variety of sources” and “accessing data from a variety of sources” (Pick A Powerful Pilot To Propagate Customer Analytics, July 19, 2017).
Speed of issue resolution carries a significant impact. The quicker issues can be resolved, the less chance there would be of repeating poor customer experiences, thus minimizing the impacts to your brand. Outages that critically impact service delivery are a ticking money bomb. Financial impacts increase exponentially the longer you are unable to service customers. One of the largest banks in Canada implemented Aria’s Visualizer (business and support analytics) and improved support response times by 75%. Such analytics applications cannot be underestimated.
Systems that deliver customer interaction analytics in an efficient and accessible manner empower lower tiered or less senior support staff to extract necessary system information required for issue resolution. This can help focus the energy of senior technical staff on critical and future-facing initiatives.
Business analytics resources can also leverage data on agent and system behaviors to make better-operating decisions.
Lack of proper visibility into these three areas: customer experience and retention, employee behavior, and support issues – translates into a significant financial impact. Analytics applications like Aria’s Visualizer allow for an improved unified approach to visualizing interactions level data, strategic support approach and behavioral performance analysis which can help you provide top-rated customer service.
This blog post was co-authored by Chris Theriault, Product Marketing Manager at Aria Solutions. Chris has over 15 years of experience helping mid-large size contact centers with systems analysis, design, integration, technical support, architecture and solution engineering. He has been working at Aria Solutions since 2004, on over 50 customer engagement projects, transforming operations and successfully achieving project goals.
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