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The start of a new year often means it’s time to talk about resolutions. Most people make resolutions to improve or change in some way—lose weight, eat healthier, eliminate a bad habit. Some people even make their resolutions specific to a goal from work (yes, I am that person). If that’s you, too – and your goal is centered around improving your customers’ experience thru an analytic strategy, then this is the blog for you!
Now we’ve all heard that resolutions are hard to keep, but this is an important goal – here are four tips to help you achieve and stick to your analytics strategy resolution and avoid the trap of resolution disillusion.
1. Focus on one thing.
Keep your focus on customer satisfaction and aim to solve just one thing: make customer inquiries effortless for customers and employees. Despite emerging technologies, communication channels and tools, we know the customer should come first, however sometimes it doesn’t happen. Reduce the effort it takes for them to engage with you—whether it’s for sales, marketing or a service request. Whether you have multiple stand-alone channels, or fully integrated omnichannel, aim to solve your customers’ issues the first time they contact you, in their channel of choice. Then find the best trained and skilled employee to help them – handling something where personal traits and professional competencies align is a surefire way to happy and effective staff.
2. Take setbacks in stride.
With the best technological solutions in place, you still deal with human individuals who will behave in random and unexpected ways. For example,. I understand technically how callback works and have used it successfully in the past. Yet, recently I found myself holding for seven minutes with my airline because I wanted to stay focused on that specific task. Your customers will do the same; be prepared for anything and iterate until you get maximum results.
3. Take small steps.
Even if an ideal customer behaves as expected, your solution might only work for 80% of them. Be ready to address the remaining 20% using a strategy that specifically and effectively targets their preferred channel. Performing A/B tests with alternative solutions should be a standard for all projects.
Use analytics to make it even better
Let’s use my call to the airline’s call center as another example of how to use analytics to improve the customer experience and first call resolution. The airline could have used customer interaction and outcome data like this: “We’ve received eight calls in the last six months, with seven of those calls related to flying to the same destination with a single child and seven other calls asking to add an infant to the booking.” Knowing I had an existing booking, the airline would determine that my intent for the call likely was the same as previous calls.
Using this data to find the optimal agent for that intent and profile is simple. And if the airline used prescriptive analytics, they could have sent an SMS asking, “Would you like to add infant to your booking?” This process maximizes resources and reduces calls—all while making a customer advocate in the process. While the airline did achieve first contact resolution, they could have increased customer satisfaction even further and reduced their costs by avoiding a call to an agent.
From a customer perspective, the only thing better than FCR is not having to call an agent at all.
4. Reward yourself for what you have achieved.
Which brings me to my final point: If you get great results, don’t forget to communicate outwards and upwards as you achieve your analytics goals throughout the year – including identifying the lessons learned from what didn’t work when appropriate. All too often stakeholders simply don’t know what happens with the data they create, the platforms that use it and the results it brings – it’s our responsibility to make sure that happens.
Use Customer Satisfaction Metrics in your Routing
Contact center managers often struggle to determine which metric to optimize and how to engage their employees, all while meeting their stakeholders’ changing needs. Many don’t know where to start and become frustrated after focusing on one operational metric, such as lowering the abandon rate, only to discover unintended consequences, such as a drop in customer satisfaction.
Predictive analytics allows a myriad of data to be added to the decision criteria for every interaction – things like journey stage, hometown, channel preference or customer satisfaction data. At Genesys, we use this data in Predictive Routing to help deliver great personalized customer experiences and focus on customer satisfaction as a way to increase wallet share, improve conversion rates and provide seamless customer and agent experiences.
Even through FCR doesn’t have an industry standard, it typically follows the same general principles: Examine the number of repeat inquiries over both a short period of time and a longer period. For example, you could track the number of repeat contacts over seven days and 31 days. And while some organizations look for the same contact reason over repeat calls, others look for any reason the customer might have called. Both strategies typically are great predictors.
Overall, it’s good practice to ensure that the feedback loop is complete and the customer is satisfied. Tracking these factors and continuing to reduce customer effort and repeat contacts allows you to pay attention to something else, such as a new product launch or an upcoming marketing campaign.
Focus On a Familiar Metric
If you’re looking to execute some technology or process improvements, it’s important to remember that in a contact center, each change can have multiple outcomes. For example, focusing on FCR could increase handle time slightly in the short term, but eliminating repeat interactions will reduce the transfer rate – which should improve employee satisfaction (more satisfied interactions) and increase your Net Promotor Score (NPS).
Using an understood and familiar metric such as NPS helps the entire organization discover new processes and technologies in a way that guarantees optimal outcomes for stakeholders as well as employee engagement.
Co-Authors for Blog Post: Stephanie Grey, Product Marketing Manager – Analytics and Graeme Provan, Global Solution Director – Analytics
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