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How to Use Real-Time Analytics in Customer Service
A guide to improving the customer experience with real-time analytics.

March 27th, 2017

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Becca Le Blond



Real-time analytics is the use of data - or the capacity to use data - as soon as it becomes available. At FM, we use real-time analytics as a quick measuring tool of the performance of our operators in the previous hour. Sounds pretty useful, right? And it is; our analytics team is the backbone of our customer service (CS) department.

How do we do it? It's all about integration: between our analytics and CS teams, and our analytics and CS software. We're going to talk about the data we gather and how we use it to make sure our operators are the best they can be.

How can I use real-time analytics in customer service?

If you have the facility to capture the data, real-time analytics could measure anything: how much money was spent on your site in the last hour, how many customer contacts you received in the same period, how many you could receive, and how many were caught in a queue. The possibilities are numerous. So before implementing an analysis plan, you need to determine exactly what data would be useful to your CS team. We use the data we gather to monitor our operators' response times, abandoned chats, and contacts per hour (CPH).

CPH

If you don't notice an operator's low CPH until days or weeks later, the opportunity to mitigate its effect on the customer experience (CX) you're offering will already have passed. Keeping up with operators' CPH in real-time enables our supervisors to identify who needs a bit more encouragement to work harder (we've found the occasional confidence boost can work wonders). And the best and hardest workers get regular recognition, creating a little healthy competition within the team. Doing the same with your CS teams will create a positive, productive environment for your operators.

Reacting to changes in CPH in the moment enables our clients to only pay for the resources they need. We cross-train our operators so that we can react to low CPH in real-time; by moving the operator onto a busier team, we're able to save clients money and help our operators smash their targets. Being ready to do the same with your teams may require a time and money investment that, at first, looks daunting. But, the long-term benefit will be worth it.

Response time

Response time monitoring is another tool in our supervisors' arsenal for investigating any low productivity they may notice in the team. If an operator’s average response time is fast but they still have a low CPH, then it’s clear that they’ve been caught up in conversations that are longer than usual. Supervisors can then delve into the detail of their interactions to see if they can help the operator deal with similar situations faster in the future. Given  47% of customers said they'd take their business to a competitor within a day of experiencing poor customer service, our proactive approach prevents our clients from losing customers.

Slow responses on webchat cause frustration to most customers. Think about it – if you were having a face-to-face conversation with someone and they didn’t respond to your question for a couple of minutes, you wouldn’t be impressed. We’re proud to be able to boast an average response time of 36 seconds.

Abandoned chats

Measuring the number of chats abandoned an hour is a great way for us to iron out any creases in the customer experience we're offering. Customers expect a fast response when they connect to your business via webchat, and measuring how often they aren't able to connect to you is essential to optimising your customer experience. Chats can be abandoned in a few different ways, both technical and operational, so it's important to make sure you can spot the difference.

47% of customers would go elsewhere within a day of experiencing poor customer service

If customers are getting frustrated by the queue and leave, we can assign more operators to the team so we can start taking more chats. Once frustration has been ruled out as a factor, we can then proactively resolve any technical issues with our client’s website and continue to chat to customers without disruption. Doing the same in your business will enable you to identify whether it's issues with your website's functionality or the number of chats you're able to take that's having a negative affect on your CX. Working out the cause is essential because different causes require different paths to reach a resolution.

Once you've decided what metrics you'd like to measure, the next step is making sure your supervisors receive the training needed to interpret the data (and reports) generated.

How real-time analytics helps team management

The ready availability of data makes the path to progression transparent to our operators. Got your eye on the next supervisor position? Make sure you're consistently near the top of the leader board. We're big on picking our supervisors from internal staff, and we promote only the most motivated employees. This creates a culture which is able to identify problems quickly and find resolutions even faster, all because of real-time analytics.

Of course, management doesn't stop at promotion. One of the biggest difficulties of real-time analytics is making sure supervisors are trained to be able to identify the potential causes for any data outside of the norm. “The biggest con is [getting the data across to the supervisors]! If the supervisors do not understand what they’re looking at then it can be quite meaningless,” says Peter Chandler, Project Manager at FM. If an operator has a lower than average CPH, is it because they’re fresh out of training and still finding their feet? Or have they been distracted by a particularly difficult interaction? Refresher training and regular updates on the operational status of their teams keeps our supervisors in the know.

Although acting quickly on information is essential for addressing any operational issues in good time, it’s important not to be too hasty. With this type of pressure on a supervisor, there’s room to make a mistake. It’s important to make sure they’re given the support needed to know the action they're taking - based on the evidence in front of them - is accurate. 

It's essential not to make hasty decisions with real-time analytics

If you ensure your supervisors have in-depth training in interpreting the data you’re gathering, you’ll be providing them with the tools for the professional success of themselves and their teams. Peter states the biggest advantage of real-time analytics is, “getting this data across to the people that really do make a difference – the supervisors. As well as getting to know their team much better from an operational point of view, senior management can get a quick overview of what’s happening in the moment. ”  Motivated teams are productive teams who, in turn, offer a better experience to your customers. Win, meet win.

How to go about gathering real-time data

So, we've dedicated a fair bit of time to discussing why you need real-time analytics, but just how do you go about gathering the data? Unfortunately, there isn't a one-size-fits-all solution, and it may take a bit of experimentation for you to find one that covers your needs.

The specific types of data you collect will enable you to optimise your customer experience in different ways, and you’ll first need to decide on which are the best for your business to visualise whether you’re reaching your CX targets. That certainly doesn’t sound straight forward, and it isn’t. But the reward is worth the hard work.

You should have at least one measure of your operators' productivity that you can keep an eye on in real-time. However, we suggest at least two. That additional metric should give context to the first. For example, if you're measuring an operators' CPH, another metric like response time or first call resolutions (FCRs) would make it easier to assess whether an operator is having a slow day or if they've been handling particularly taxing interactions. On the other hand, if an operator has a high CPH and low FCR you'd likely want to investigate the quality of their interactions.

Once you've decided what metric to track, you then need to focus on the 'how?'. Peter said, “to be effective, data needs to be published hourly. No matter what system you use, the data needs to be cleaned first and that causes a delay. Any analyst will tell you that dirty data is a nightmare.” The capabilities of the contact management system (CMS) you're using will likely be the limiting factor here. We have a specially trained team of analysts whose daily priority is taking the data produced and turning it into easily digested reports for our supervisors.

The data we use doesn't necessarily improve specific interactions with customers but, combined with our expert team of analysts, it helps us ensure we're providing a next-level customer experience. Contact us to find out how you can get started.

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About the author

Becca Le Blond
Position of Content Specialist