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Video Guide: Using Customer Care Data To Reduce Cost

In this 5-minute video guide we’re showing you how to use data to reduce your long-term customer care costs.

May 21st, 2019


Becca Le Blond


If you can't measure it, you can't manage it - the guiding principle to any good strategy. You need the data to be able to identify where it is you are now in order to create a path towards where you want to be.

Now in customer service there's a whole load of data that you could be collecting, so we've listed most of it on the Jargon Dictionary on our website. If I don't happen to mention the specific thing that you're interested in you can probably find the information you're looking for there. But the data you'll want to be collecting will be dependent on your exact objectives.

The objective that I'm going to cover in this video today is one that most customer service teams will have encountered at some point in their journey, and that's cutting costs. So what I'm going to talk about is how we at FM Outsource would identify and take on a cost cutting challenge.


So the first step in taking on a cost cutting challenge is to identify your current position. To develop a baseline the three stats that I'd recommend measuring are contact volumescontacts-per-hour and true cost per full-time equivalent.


First, the volume handled by your customer service team. So that's basically the total number of inbound contacts that are taken on, whether it be email, telephony, social media interactions or any other channel you happen to be covering.

The second stat is CPH or contacts per hour. That's the productivity metric for your team so it's basically how many customers they're able to help in the time that they're working.

The final metric that I'd suggest is cost per FTE. Now that goes beyond paying someone to be on your rota for 40 hours per week. It's the shrinkage - so how much does that advisor cost if they're on holiday or absent. It's things like how much does it cost for them to be in an office, how much does the PC they're using to answer customers cost. That plus a whole range of other overheads is your true cost of an FTE. And knowing what that is, is really important.



Next, you need get a bit more granular with your data so you can understand where the problems are and why they're occurring. Again, three stats here – reason for contact, rate of first contact resolution and average handling time.

So the first stat I would recommend collecting is reason for contact data. So why is it that your customers are contacting you - which issues are causing more volume.

The second piece of data that I'd recommend is rate of first contact resolution. So are there particular channels, issues or operators who are achieving faster first contact resolutions than others? Are there any changes that you can implement to help them to get more?

The final stat that I would recommend is handling time data. So are there any particular queries that are faster to handle than others? Those that have the longest handling time, what can you do to make that shorter?


So, once you've gathered all of that data and you've identified the pain points in your operation - that's when you can start putting together a business case in order to take action. I'll work through an example that we've worked many times here at FM Outsource which is refunds - a big one for the retail world.

Let's say for example that you've looked at your reason for contact data and your handling time data and you've recognised that refunds are responsible for most of your inbound volume and they're taking operators a really long time to handle. Let's say that looks like 500 requests a week, and they're taking operators 5 minutes each time to process. So using those numbers that means they're taking up about 2,500 minutes a week. Which is 41 hours. That's just over 1 full-time equivalent just to handle refunds. Not even taking into account any other issues that advisors might be dealing with.

So what I would recommend doing here is looking at ways to integrate your systems into your communication platform that your operators are using. Can you bring all the data that they need into one screen so it's faster for them to handle? What other systems are they having to use - is the order management system you've got in place a bit slower than you'd like? What other process steps could you cut out just to make it faster?

Let's say you've taken those steps and you've cut handling time down from 5 minutes to 1.5 minutes. That means you're now taking 750 minutes to handle your refunds. That's 12.5 hours or a saving of 0.8 FTE.

So to put that in real terms, that means if we use an industry average of £2,500 per month per FTE, you're now saving £2,000 per month. So what you need to do is weigh up the cost of integrating those systems and creating any process changes against the long-term benefit of saving £2,000 per month. So in order for you to do that we've put together a spreadsheet so you can identify costs and compare them that you can check out on the link below.

And if you have any questions regarding how to collect any of the data we've talked about during this video or any other data we've included in the jargon dictionary on the website please reach out to us on the contact page or on any of our social media channels, or just message one of the team on LinkedIn, we'd love to be in contact with you. Thank you very much!


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