We live in a data-driven age where brands want insights, especially customer-related ones. However, many companies hit roadblocks on how to collect intelligence and leverage it to improve the customer experience. Gathering data and mining it into actionable business insights can be timely and expensive – but well worth the effort.
Historical data can help you predict volumes and staffing requirements to ensure you’re prepared for spikes in demand. Reduced hold times and speedy responses generate a vastly superior customer experience.
Data is incredibly helpful when you can look at past performance for peak periods like Cyber Monday, back-to- school, and other promotional events. If you understand how busy you were last year – you can ensure you have personnel in place to answer tickets this year.
The same is true for sales forecasts. How many units are you planning to move over the coming months? Your customer service team must have access to this data to ensure they’re prepared. Experienced support teams can apply sales to contact ratios to predict the number of inquiries sales will drive.
Historical data will also help you understand what time of the day requires the most coverage and how many agents you need, down to 15-minute intervals. This information ensures your limited resources are maximized 24/7.
You can use website data to reduce the number of times customers need support.
Most sites have tools that map a visitor’s journey, allowing you to track where they traveled before reaching out to Customer Service. You can see what specific actions or paths led to a call or email. This is valuable information that can help you identify areas where a process or page needs updating. Likewise, pathing can help identify where self-help widgets and bots on problematic pages might reduce the need for extra assistance. All of this can improve CSAT and minimize servicing costs.
Dissatisfied customers are a treasure trove of data that you can leverage to fix issues.
Delve into DSAT to understand what processes, products, and services drive dissatisfaction and outreach to customer support. That data may uncover opportunities for improvement.
Goodbay supports some of the top gaming companies in the world, and we analyze DSAT’s for our client partners. This data helps identify bugs – or where game elements need reprogramming. We routinely examine what’s driving the highest number of tickets and hone-in on those areas for improvements.
You can even segment dissatisfaction to understand what issues are damaging your bottom line the most. Gaming companies do this all the time with customer tiers. They bucket players by profitability and revenue – and group their issues. This categorization allows them to focus on solving problems that are impacting their most lucrative players first.
70% of your tickets will come from the top 10 issues that drive calls. While an agent needs to be versatile and able to handle all kinds of inquiries, you can use data to make sure that they are pros on delivering solutions for the biggest (top 10) drivers of problems. They should know how to address those issues thoroughly, from their first day on the floor. This expertise will improve response and resolution times – and should lead to happier customers.
Data will help identify processes that are time-consuming, expensive, and inefficient. You can leverage that intelligence to develop new approaches to handling your customers – and reduce response times.
For example, you may find that agents are spending a significant amount of time authenticating accounts with information like date of birth, account numbers, etc. If that’s the case, you may want to invest in an automated IVR system or AI bots that allow customers to authenticate before they get to an agent.
Similarly, you may be using channels that take too long to respond – especially for simple questions. Goodbay recently used data to demonstrate the value of live chat with a new client. The analytics from this test demonstrated that agents were able to increase productivity and handle more tickets with chat. Conversations were more casual (requiring less typing) – agents were able to handle five concurrent interactions. In the end, adding chat enhanced the customer’s experience as tickets were addressed faster with the productivity improvements.
Goodbay would love to leverage our expertise to ensure your success!
Sapan Shahani is the CEO of Goodbay Technologies and is based in Chicago, IL. For close to two decades, he has helped digitally disruptive businesses deliver superior customer care experiences. Sapan was born in Bombay and raised in Hong Kong. He came to the US to study Finance & Entrepreneurship at the Wharton School, University of Pennsylvania. After a successful career in strategy consulting, he left to pursue an idea he discovered in an Economist article that outlined how the world’s best companies were moving their customer support to India.