What are the challenges of measuring customer support metrics in Sales Ops?

What I've learned from my experiences in customer support is that it can be a very unique value proposition to customers if you get it right. Even if your company doesn't have every feature nor is the cheapest offering if your customers feel taken care off, they will stick around. In order to maintain that value however, there need to be metrics to ensure you, your team, and your company are continuing to deliver high value for customer support. High-quality customer support is the vision plan, and thoughtful customer support metrics are the execution plan.

Some of the ones that I like to use are: 1. First Response Time (When its urgent for them, is it urgent for you?) 2. Resolution Time (They don't want to be encumbered, does your priority lie with theirs?) 3. Retention Rate (Customers can only take so many negative experiences, are you giving as much of the good and as little of the bad as possible) 4. Self-Service Resolution Rate - This is often overlooked. Self-service support options are lauded because of availability and fewer resources, but they can come with the cost of ineffectiveness. Too many times we see chatbots and other tools unable to answer even simple questions, so looking at whether automated tools are resolving customer issues is very important.

The biggest challenges are often finding the pain points for customers, which is normally something more microscopic and hard to spot. E.g. A company's Customer Retention Rate is 10%, less than their target of 15%. You may have that number, but what is causing that number? In software, maybe users are experiencing too many crashes? In hardware, maybe its too many mechanical failures? The micro-metrics often are the real story and it's critical to pay attention to them.

While sales team might focus on numbers, in literal terms, quantity, Customer support focuses on resolution of issues, customer experience, customer satisfaction. In essence the sales team will out their energy into increasing numbers (quality) while the customer support team will be focused on quality metrics. Data standardization and processes might be different. Different techniques, tech products used and directives might results in conflict of data and results. Ensuring data consistency and collection is also a challenge.

QUANTIFYING QUALITATIVE DATA: Much of customer support involves qualitative data, such as customer feedback or the nature of support interactions. Turning this qualitative data into quantifiable metrics that can be tracked and analyzed over time can be challenging. One possible solution: Implement a tagging system in your CRM where support agents can tag calls or support tickets with specific themes or issues (e.g., product-related, billing issues, technical support). This allows for quantifying the frequency and nature of various types of support interaction.

The key way in my mind to overcome the challenges of measuring customer support metrics is to syllogistically understand the workflows/use cases customers go through end-to-end, and understand where there is a breakdown. For example, for a new software feature, you could create a 'metrics funnel', and track how many people are making it through a workflow for a new feature. By having retention metrics along each step of the workflow, and looking for abnormalities, you can gain insight on where problems may exist. If 90% of users using a new feature experience a crash during it, there will likely be a dropoff in the percentage of users completing the remaining steps in the workflow, and you now have valuable insight to act upon.

You can learn more about measuring customer support metrics via external methods like media, classes, etc, but one of the first questions to ask is what metrics are valued by your organization. Assuming you aren't the head of whatever entity you are trying to measure customer support metrics, understanding the macro-metrics your org cares about, and then in your role defining what the micro-metrics that define the macro metrics, you can effectively provide the story and insights for your org to create positive change for customers.