How to Improve First Contact Resolution Rate with Automation
Provide better, faster resolutions with a customer service team supported by automation.
January 8th, 2018
First contact resolutions (FCR's) are exactly what they sound like – those rare queries you solve in the first interaction. They're the gold standard of customer service because they’re so difficult to achieve. But improving your FCR is a tried and true method of improving customer satisfaction, so they can’t be written off as too difficult to achieve and ignored.
Removing barriers to achieving FCR’s with automation will only benefit your team if you’re already working to maximise FCR rate. Per Bill Gates’ famous quote:
…automation applied to an efficient operation will magnify efficiency… automation applied to an inefficient operation will magnify the inefficiency.
We’re going to highlight a few limitations currently standing in the way of achieving a 100% first contact resolution rate, and discuss a few methods you can use to improve your FCR with automation.
What is a FCR?
A first contact resolution is achieved when a customer’s question or query is answered during their first conversation with a customer service operator.
Not all interactions can result in a FCR, and you need to account for these instances. This is the difference between gross FCR and net FCR (stay with us, we're going to stop sounding like your payslip soon). Gross FCR measures the ratio of all contacts you resolved after a customer’s first contact, whereas net FCR is the ratio of all contacts resolved at first contact when an FCR was possible.
Automation can help you improve each of these metrics. This might seem more obviously achievable in the case of net FCR – automation (in the shape of a chatbot) removes the possibility of human error, which can lead to a missed first contact resolution. The great thing (for us) is that improving net FCR naturally leads to an increase in gross FCR.
Automation addresses inherent limitations like non-live interactions and human error, and removes operational hurdles standing in the way of first contact resolutions.
FCR’s are harder on non-live channels
Resolving a query first time is naturally easier when that query has reached you over a real-time conversation channel (for example telephony, or webchat).
Operators can get all the information they need straight away – there's no delay whilst they wait for a customer to reply to their email or social message. If a customer has any follow-up questions they can ask them in the moment, and an operator can be sure they’ve done everything they can to allay a customer’s concerns.
This becomes trickier when a customer sends an email or a social message. The best way to reach FCR’s on these channels is to provide answers that anticipate what a customer’s follow up questions would be. For example, if they're asking how to return an online order, an operator should explain their postage options, how long it would take the return to reach you, and how long a refund would take to reach their account.
Analyse your first contact resolution data to get a better understanding of how it differs by channel. Control how FCR’s on non-live channels affect net FCR by calculating live net FCR and non-live net FCR.
Once you have these measurements you can see how non-live net FCR is affecting your overall net FCR, and take steps to address the issue.
Online agents are asked to cover multiple channels
Online contact centre teams often provide multichannel coverage, and are trained to handle any type of query they may receive. Whilst this removes the need for customers to be transferred from one department to another, it does introduce the potential for a resolution to be missed due to a lack of process-specific training.
The best way to ensure FCR's is with channel-specific processes, but these aren't always possible for multichannel operators. However, efficient customer service relies on multichannel teams, so you need a solution to this problem. Thankfully, automation presents the answer.
Methods for improving FCR with automation
Gather context before the conversation
Automations can gather information on a customer’s history with your business to work out why they’ve started a conversation with you before they’ve said anything. Cookies stored in their browser, their account history, and the page they’re contacting you from can all be used to work out why they’ve messaged you.
Directing customers to an AAQ (ask a question) section on your site as a first port of call for CS provides a natural path for cookie gathering. It also presents an additional win by cutting the volume of customers contacting your CS team (if they’ve already found the answer themselves).
You can then use this information within workflows (check out ‘Route conversations to a specialised team’ below) to direct a customer to the correct team. Being immediately connected with the best operator for the job boosts the likelihood that a customer receives a fast solution, and that your team earns a FCR. This operator will be equipped with the customer information and specialised training they need to provide the best possible solution.
Despite the tech-y sounding title, these are really easy to get in place (if you’re using the right communication platform, that is). If your team is currently using multiple pieces of software when handling a customer’s query, then plugging them all into one interface will help immensely.
If you’re an online retailer, your team is likely to be juggling at least an order management software (OMS), delivery management software (DMS), and payment processing software. All that is on top of the communication platform they need to hold conversations with customers. Integrations remove the need to think of these software as separate entities.
Application programming interfaces (API’s) make it possible for each piece of software to request, and send, snippets of information to each other.
A communication platform integrated to the rest of your team’s software presents operators with all the information they need to know in one interface.
This cuts the time they need to reach a resolution, and removes the potential for details to be missed when flicking between screens.
Route conversations to a specialised team
We know – this isn’t a novel concept. Interactive voice responses (IVR’s) have been used for decades to (try to) direct customers’ calls to the correct team. Contact centres have evolved to handle multiple communication channels, without traditional query-type specialisation. But this means operators may not always recognise the potential for a FCR.
Customers’ queries come with their own nuances, and one may be faster to resolve than another, despite their similar issues. For example, a customer who ordered a product with a known production issue may be able to get a refund faster than the usual process. A team that handles only refunds will know about this issue and handle the query accordingly, whereas a member of a larger, less specialised team may not have received this piece of information and so treat it like a normal refund.
Workflows – a set of rules attached to specific events within a software – can use data collected during context gathering to direct a query to the best team for the job. This means customers connecting via webchat or telephone won’t need to be transferred, and teams handling social media messages and emails will have the in-depth knowledge needed to provide responses that should earn them an FCR.
Customer experiences are becoming ever more optimised thanks to continual development of automation strategies. They’re undeniably the future of customer service. If you’re looking for a CS outsource with experience providing intuitive AI-assisted solutions to large retailers, contact us.