Why You Need To Measure Success Differently
The cornerstone of Glia’s Unified Interactions Report is a new guided benchmarking index designed exclusively for use by banks, credit unions, and insurance companies. It’s called the Unified Interactions Index and it is markedly different from other customer experience metrics. It measures the full breadth of the value created by the interactions between financial institutions (FIs) and their customers.
In this piece, we will explore exactly what is being measured, why the specific elements of the Index were chosen, and how this more evolved approach to measurement will enable your organization to create greater economic results.
The Index benchmarks your company’s performance against over 500 other FIs, on an overall scale from 0-100 points, based on 14 different metrics in three categories.
Let’s break them down:
Category 1: Efficiency/Cost Reduction
- Average handle time (AHT)
- Average speed of answer (ASA)
These first two are traditional metrics that have been around since the earliest call centers. They are important, but they are only part of how companies should be measuring efficiency.
- % of first contact resolution (FCR)
Most companies measure this incorrectly by simply asking customers, “Have we fully resolved your issue?” and if the answer is “yes” it is assumed that FCR has been achieved. But companies should be checking how many customers initiated a second interaction about the same issue within a given period (typically seven days). If they have, then FCR was not achieved.
- Ratio of digital interactions to phone calls
This is a metric most companies can easily calculate, and they often find the ratio is still weighted far too heavily toward phone calls. To be truly excellent in efficiency, at least 60% of all interactions should be digital.
- Automated post-interaction wrap-up?
This is an easy one: Every company should use agent-facing AI to provide their frontline employees with a pre-filled form based on the customer’s issue type (or wrap code) and with the pertinent details about the interaction. If the bot got everything 100% accurately, all the agent has to do is click “submit.” If it’s not quite right, they can make any changes or additions in seconds. This typically cuts down post-interaction time by about a minute per customer.
- Maximum efficiency
This final metric in the category is a new one, but it’s simple to calculate. It allows companies to determine the maximum number of interactions an agent could handle within the span of an average hour if they are experiencing constant demand. The formula is 60 minutes ÷ AHT x 1.3 (assuming that at least some agents are multi-engaging).
Category 2: Effectiveness/Revenue Generation
- % of digital interactions completed by bot
Since so many customer needs can now be completely resolved by bots, companies should be calculating how many customers who visited their digital properties were able to fully resolve their issue without additional live assistance. The goal here is to get to about 80%, so that only the most complex needs should require a live agent.
- Abandonment rate
This is the % of customers who leave before an agent can begin a problem-solving or revenue-generating interaction. This number should be very low: The best companies have an abandonment rate of less than 2%.
- Satisfaction with conversion
This is the only totally subjective metric within the Index and is prompted by the question, “How satisfied was your organization over the past year in increasing your customer base, converting more loans and increasing overall AUM?” To achieve an excellent rating in this metric, the ideal answer is “We are very satisfied. We exceeded all our revenue and growth goals.”
- % of customers who accepted an invitation to chat with a live agent
This is another metric that will be new to many companies but is a marker for overall revenue generation. Companies should start measuring how often they are proactively offering a customer a chance to interact with a live agent in any revenue-generating situation, like considering opening a new account or applying for a loan, credit card, or any other new product or promotion.
Category 3: Experience
- Customer Satisfaction (CSAT)
- Net Promoter Score (NPS)
Again, like AHT and ASA, these are traditional customer service metrics and they’re still important. But also like those others, they are insufficient in and of themselves to provide a true picture of the value of interactions.
- % of customers who transitioned from chat to OnScreen Voice/Video (OSV)
Companies should begin setting targets for the use of OSV, which should be proactively offered to customers whose need is complex or requires human connection and reassurance. A good target goal is to rise above 10% on the way to an excellent rating of 20%.
- % of interactions involving CoBrowsing
CoBrowsing isn’t right for all interactions–not even close–but in “teaching moment” situations where a customer can be shown how to conduct certain interactions in the future without the need for additional live assistance, it is the perfect tool. Helping a higher percentage of customers become more digitally self-sufficient should be the goal of every FI.
Conclusion
Only by measuring the combined impact of the three categories of Efficiency, Effectiveness, and Experience can companies begin to get an accurate handle on the overall value of the interactions they’re conducting with customers every day.
Over time, as your organization tracks these metrics through the Index, it will become clear that as you see improvement in one category you will see upward movement in many others as well. And when that happens, you and your team will be able to reap the full credit you deserve for managing your interactions in the optimal way.
