Technologists often speak about analytics with little regard for those people who live outside the world of technology. There’s almost an expectation that with concepts like analytics, you either get it or you don’t. The reality is that many of these concepts are not hard – including analytics. In fact, everybody uses some form of analytics every day such as “Can I afford to buy that….?” – obviously one of the most common forms. How long it takes you to execute the analytics, in this case, depends on how you end that sentence. If it’s with “new shirt”, then most people would be able to decide quickly. New car, house, plane, yacht, or mid-air refueling tanker can often take longer but they are all decided with analytics.
So, why is this interesting to you as a business person? It’s interesting because businesses that are run well are running on analytics. Tracking and reporting on almost every aspect and function of a business, and not just when accounting says they need an accounting [of what’s going on], but every day and often it’s in “near real time.” Executives from all walks of life are realizing that seeing a drop in revenue while it is happening is far more useful than reading about it at the end of the month, quarter, or, my goodness please no, end of the year. Being informed and staying informed enables the ability to take immediate corrective action. This assists in managing customer relationships as well as revenue. When a customer stops using a product and gets a call from your company that day, one thing is for sure – they know you value their business. You may not win them back, but at least you’ve done the best you can with the information you have. Reading about a customer that has decided not to use your product/service in a quarterly report is almost worthless from a revenue protection perspective. It may help you manage in the future, but wouldn’t it have been great to be able to react back when they cut you off.
As we all know, there are enough metrics to keep us busy analyzing data 24/7. With analytics, we’re able to move forward quickly and decisively – as long as you take the time to create the analytics correctly and use them to create models that are realistic.At Angel we’ve embedded MicroStrategy business intelligence and analytics into our platform to help you create and maintain a Caller First experience for your customers.
Contact center analytics begin to get interesting as you dig into the data. You can learn so much about your customers from how they interact with your company: when they call, what they’re calling about, did they get what they wanted and are they satisfied after they call. One of our most popular post-implementation modifications is to reorganize a voice site based on task analytics in the IVR. Task analytics look at your defined tasks within the IVR and examine things like frequency of use, time and/or day of use, completion rates, incompletion rates and locations where the customer just gives up by hanging up or requesting to speak with an agent.Having this information extracted from the data using Angel’s analytics platform helps our customers run their business better and make smarter decisions.
Analytics is only the first part of the equation. The real power comes with the implementation of dashboards. Dashboards are usually a graphical representation of meaningful, business focused analytics. They can graphically represent atomic level data but the representation of analytics based on that data is almost always more powerful and hence the way forward. Graphics work wonders in terms of speed in identifying both areas of success and areas of concern. For example, when you drive up to an intersection you have a graphical representation that says “there’s a 98.6% chance that you can go through this intersection without getting hit by another car.” Could you imagine if you had to read all that as you were driving to the corner instead of looking at a traffic light? Dashboards are the keys that unlock decision scalability in ways spreadsheets can never accomplish.
So implementing analytics is the first step to figuring out what is and isn’t working. Once you do that, you can then move forward towards improving it – and if you design effective analytics, you could end up fixing 98.6% what isn’t working very quickly.
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