“Hi John, I see that you have an upcoming reservation on July 29th. Is that what you are calling about?” Wouldn’t it be nice if that is what we heard when we called into a contact center? Instead, how many of us have called a contact center and been asked a multitude of questions, such as your name and account number, only to get transferred to an agent and the agent asks you the exact same questions you just got through answering? This is an all too common experience. Not to mention a very frustrating one.
For first time callers this does not make a good impression, and for return callers this is aggravating. This is just one example of bad experiences that plague Contact Centers. The root cause is most likely lack of information at the system level and at the agent level. What can be done? The solution may be as easy as using one of your most precious assets: data.
Organizations capture data at all stages of a customer life cycle. There are three phases in a customer’s life cycle where we have the ability to capture data:
1. Shopping phase – As they scroll through your website you should understand what actions they are taking, what products they are viewing, what products get the most attention, and what products get the least attention.
2. Purchase phase – Whether the purchase is done on the website or over the phone, we collect information to complete the sale. This usually includes name, phone number, email address, home address, membership id, the product purchased, date of sale, etc.
3. Post purchase phase – Activity after the sale or the completion of a service. This can come from a call to your customer service department, an email, a survey, or a post on social media.
All of this data gets captured and stored. But before we nose dive into the data it is imperative to know where you stand and what you are solving for. To begin, make sure that you understand your organization’s current call metrics, such as first call resolution percentage and your average handle time. First call resolution helps an organization to measure the interaction and the outcome of that interaction. We measure an agent’s efficiency using average handle time. An agent’s time is valuable and we want to ensure that the agent has everything they need to accomplish their task. At the end of the customer call we want to know:
- Hear – Did the customer feel that we heard them?
- Help – Did we help the customer?
- Resolve – Did we successfully answer the customer’s question or resolve their issue?
- Efficient – How efficient was the agent in handling the interaction?
Data is your gateway to success
These and other metrics will be valuable in helping to measure the before and after effects of bringing data into the overall solution and where we continue to make improvements. Industry analysts state that between 40% and 92% of calls are resolved the first time, and that the industry average is around 74%.* Meaning that, on average we are able to answer or resolve three out of four customer issues or questions. I remember back in school that a 70 to a 75 on my test meant sure I passed, but it also meant I was closer to failing than I was to showing success. No smiley face for me. This could be translated as 1 out of every 4 customers did not get their issued resolved or their question answered.
Let’s put this into context. If a contact center handles a hundred thousand calls per day, that means on average, twenty-five thousand will not get resolved. Could a good number of those twenty five thousand calls have been resolved? The short answer is ‘Yes.’ Sure, some issues are harder to resolve than others. Those customers that did not get their concern or issue resolved now have to decide whether they call back. Any time a customer has to call you back they become slightly more agitated then the previous time. Some will not waste their time on a second call. The frustration they feel simply does not support spending any more of their time or money on your product. The end result is you may have lost a loyal customer to a competitor, regardless of any price or cost savings
Next, meet with your agents to understand what types of calls they take and what information is needed to complete calls successfully. Catalog these calls.
- What are the most frequent calls?
- What are the most difficult calls?
- What are the easiest calls?
- What is needed to complete the call successfully?
Now, ask yourself what data can help the agent resolve these calls? And what did we do right to make the easy calls easy? Learn from these scenarios. At the same time, an analysis of the contact center system may reveal more. Such as:
- Where do we incur the most abandons?
- Where in the system do most callers request to go to an agent?
- Where in the system is the caller forced to go to an agent and why?
- Which calls drive the longest handle time?
- Which calls are handled in the system and seldom go to an agent?
Prioritize these opportunities. You may be surprised to find some low hanging fruit. There may be opportunity based on your findings to provide new self-service options, improve on existing self-service options, or capture information before going to an agent.
Let data drive the conversation
So, how can we take advantage of the data and make it available to the contact center platform and the agents? We need to figure out what data we have and where it is. This is the foundation for creating a better customer experience as well as a better agent experience. When a customer engages your organization, allow your data to drive the conversation. Use an identifying marker such as an ANI (automated number identification) or membership number to retrieve their customer profile. If you are able to, match a profile then bring their customer information, purchase history and contact history into the system. This small step into the data starts to paint a picture that the system can use to better serve the customer. Take advantage of what you know and start to direct the conversation. For example, your system can start with the opening line, “Hi John, I see that you have a reservation for Friday July 29th, is this why you are calling?”
Based on the data, the system is making an educated guess on why the customer is calling. And how do we know this is why they might be calling? Because based on our previous analysis we have determined that a majority of our customers call us about an existing purchase or booking. If the customer confirms this as the intent of their call, we can provide a follow up question to continue our service: “Great- and how can we help you today?” The customer may respond with an opportunity for the system to resolve without an agent. In this scenario, the customer may say “cancel my reservation.” This could be a straightforward task that the system can handle without an agent. But, prior to taking the requested action, the system can confirm the identity of the person against the customer data retrieved, perhaps by asking the caller to verify their membership number and date of birth. When the customer answers these questions correctly, the contact center platform can update the backend system and take steps to process the cancellation request.
Share the data with other applications
Once cancelled, the system can present the caller with the cancellation and other relevant information such as the amount refunded. As a follow up, the system may even send a receipt in the form of an email containing the information presented to the caller. If the system is unable to verify the caller, the system can transfer them to an agent. Along with the transfer to the agent, the system can pass any information collected, such as the customer profile, the reservation information, and the intent of the call. Taken a step further, the system could pop this information into the company’s booking application for immediate display to the agent receiving the call. Upon receiving the call, the agent would know the intent is to cancel a reservation and the reservation application would be populated with the customer information. Data collected in the system can be made available to other applications on the agent’s machine, so that those applications can use this data as input to serve up information to the agent. CRM applications may be able to provide previous case history. Knowledge base applications can provide the agent with product information.
As an example, a customer may be calling about their warranty. In this situation, the system could send the customer information, the product information, and the purchase information to the agent’s machine, allowing a knowledge base to use the data as input and ultimately to serve up information. All this information is now at the agent’s fingertips, and they are ready to service the caller. What seems like a simple task can be repeated for other scenarios like modifying an existing booking, retrieving a booking status, or checking a membership status. It is important that we recognize that not every solution is easy and some may not warrant the investment. When using your metrics, it is important to understand the return on your investment should you choose to make enhancements.
Where many organizations go wrong is investing in a new tool instead of solving for their current issues. For a lot of contact centers, that might mean implementing a new channel such as chat. How many times have we heard the following: “Yeah! We are now omni-channel! This will solve all our problems! Our customers can now contact us on their preferred channel. Interact with us wherever and whenever they want.” It may indeed provide some customer experience improvement or a convenient channel of communication. But what inevitably occurs is we move our problems from one channel to another. Now instead of being unable to help our customers on one channel, we are faced with the reality of being unable to resolve issues on multiple channels.
It is easy to add a new tool or a new channel. That does not always guarantee success. It also does not solve the system issues you may have today. This may very well include no access or limited access to data. No self-service, limited or incomplete self-service. An uninformed or unequipped agent is a less efficient agent. Do not frustrate your customer with a new channel or a new tool if you bring your existing issues into it. Rather acknowledge, identify and improve what is already there.
Reaching the finish line
Understanding what you are trying to solve for is a step in the right direction. To reach the finish line, it is imperative that you understand your challenges and what data is available to support these new opportunities. It is good to know the data and services landscape within your organization. Meeting with your data and enterprise architects will help you to know what data exists and what data makes sense to be leveraged by the contact center platform. Prioritize your identified opportunities with your organization’s data. Work with your architects to build a data roadmap and begin laying the foundation for new data and new services. Data and access to data can be your gateway to success.
Jeff Grant will be participating in the Surprising Lessons From My Digital Transformation Journey panel discussion at our 18th Annual Customer Contact West: A Frost & Sullivan Executive MindXchange in Tucson, Arizona on October 16-19, 2022. Join us in-person!
About Jeff Grant:
“My entire 25 year IT career has been centered on improving the customer and employee experience by merging data with current and emerging technologies to achieve a desired outcome. Then measure the outcome in order to improve the experience. It is a journey and there are boarding signs, re-routes, turbulence, delays and sometimes fair weather along the way that we must endure and embrace. I have made plenty of mistakes along the way, but without them I would not understand success. Today I package my experience and knowledge together by joining data with the Enterprise Contact Center platform across the 19 different lines of business that I support.”