Post-Sales Use Cases
Make no doubt, customer service is the reason a customer decides to stay with your business or look for a new solution. After the sales cycle is complete and the service organization has finished its delivery, the face of a company to its customers is the customer support team. The level of support provided is how customers measure the value of a company to them, not by the solutions alone. Customer service is one of the few groups that can single-handedly define a positive or negative Net Promoter Score (NPS), which, in a growing competitive global economy, can make or break a business all on its own. In addition to affecting NPS, the data collected by a customer service team can have other profound impacts on a business.
In this post, we’ll focus on how chatbots can help customer service teams collect important data on customers while significantly improving service and satisfaction.
Many leaders overlook the significance of the valuable insights they can gain from their customer service teams. Think about it: When someone calls into a customer service center, the CSR can learn a wealth of information about that person and about the solutions he or she uses:
- What parts of a solution are and are not being used
- What the customer finds easy or difficult to use or understand
- How well the solution was or was not installed
- How well the customer was or was not trained to use the solution
Let’s not forget about opportunities to educate, upsell, resell, retain, and upgrade those customers!
A lot can be learned from what customers say when they call into a customer service center, but only if their information can be tracked, counted, analyzed and reported on a regular basis. Traditional call centers often miss this opportunity and do not capture why customers are calling, because the system relies on employees to accurately record and categorize each call. The other issue is that call center employee success is almost never measured on the data they collect, but rather on the number of calls they answer and close in a specific period of time.
“Press 1 to leave a message, or hold and your call will be answered in the order in which it was received.”
How many of us have heard this recording at some point in the past 5 days, and how many of us have given a negative score on a customer service satisfaction survey because of it? Call centers are becoming more of a nuisance, both for a company and its customers. Often, call centers are a huge cost due to the sheer number of personnel required to achieve short hold times and global coverage, and they usually don’t improve NPS.
Specialized resource availability and scheduling is a constant headache, and the right person seems to never be available to help a customer when he or she calls. So, a message is taken, and the customer is told the following: “We will call you back when the right person is available.” But, the customer needs help now!
There is another issue here: The organization has completely lost track of that customer, what the customer needed, and why the customer called, leaving it blind to their needs. Combine that one customer with the needs of all other customers that call, and major opportunities are missed.
We live in a world where we instantly access global information in the palms of our hands, have same-day shipping and online check depositing. It’s no surprise that as customers, we expect immediate, self-service access to the tools we need to get things done now. In addition, organizations are realizing how much they are missing by not capturing and tracking information about each support call and interaction. Because of these trends, chatbots are becoming a more permanent fixture in the realm of customer service.
Where are chatbots used in customer support?
Voice and chatbot use cases are expanding rapidly in the areas of online, in-app help systems and level 1 customer support. Customer support departments are using chatbots to either completely answer a customer’s question or to gather all of the appropriate information from a customer and pass on that information to an appropriate level 2 support technician.
How do I reset my password? How do I use this feature? How do I complete, change, and/or check the status of my order?
These sorts of direct inquiries are the best use for a chatbot, especially when they make up 80% of a call center’s call volume. A chatbot can instantly answer these questions with more clear, consistent, and complete responses than a call center agent:
“I see you want to understand how to use feature ABC, so here is a video in your local language that can help.”
“I see you are trying to figure out how to print, so here are a few knowledge base articles and discussion threads that have helped others with the same question.”
What’s even better? The chatbot can ask customers if the solutions provided worked. If not, customers can choose to use the chatbot again, or to be transferred to a human (complete with the initial inquiry) to continue a real-time troubleshooting online chat session. Some chatbots even connect to backend systems and can perform certain tasks for a customer, such as resetting passwords, unlocking accounts, or creating a service request or work order.
From the customers’ perspective, the whole point is being able to ask for and get help in real time 24×7, instead of waiting for the call center to open, sit through a decision tree, only to be put on hold for an available service rep who doesn’t know how to help them anyway. From an organizational and NPS perspective, a major added benefit is that each chatbot exchange can be logged, analyzed, and recorded. When analytics and machine learning are applied to this transactional data, you can gain many insights on your customers’ habits, needs and challenges.
Chatbots can provide a wealth of knowledge to a wide range of teams within a business that call centers simply cannot. Consider teams like sales, marketing, product management, engineering, and user experience. These teams can benefit greatly from the insights chatbots obtain through the data they collect. Sales and marketing can use this information to aid in product positioning. Perhaps a product was intended to solve problem x, but customers are using it to solve problem y. You constantly should evaluate and adjust your value propositions, understanding that the problems your customers ask you to solve also can assist in homing in on the perfect wording.
Product management organizations benefit in a huge way from the insights they gain from chatbots collecting conversations with customers.
“Why can’t I find a report I need?”
“Does the system allow me to perform this function?”
“How can I use the system to complete this task?”
These questions are music to product managers’ ears, because they can use these questions to help them define and prioritize their ever-growing backlog of feature requests and defect fixes. Questions like these also can provide intelligence on what your competition is doing that your solution may not be doing.
When thinking about improving user experience, chatbots can be extremely helpful in providing insights. If customers constantly are asking how to complete a task or where to find a feature, it might be time to look at the UX surrounding those questions. Perhaps there is a confusing workflow, or a feature is hidden deep inside a menu or web page. Perhaps a new defect was introduced in the last release that is causing heartburn for a specific group of users performing a specific task. The engineering team can monitor for this situation and proactively release fixes for the defect before customers get too frustrated.
Customer service is the key to high customer retention, NPS scores, and ultimately revenue and EBIT. In a world where instant gratification and access to information is expected by all users and customers, a properly implemented chatbot solution is an essential component to enabling this success.
Are you trying to get started on implementing a chatbot solution to optimize your customer support model? Contact us here to set up a time to talk with us about your questions, ideas and interest in implementing chatbots to transform your customer support model.
About the Author
Joel Sarapin has more than 15 years of sales and business development experience in the software engineering industry. Currently, he is OFS’s VP of Sales responsible for new client acquisition, and he also manages several key strategic accounts around the United States. Joel holds a Bachelor of Arts degree from the University of Massachusetts (Amherst).