The state of your business, as told by data

Sales data

If your company is using a sales CRM, you’re sitting on a wealth of insight that can be drawn up and turned into actionable insights. If your company isn’t using a sales CRM, it might be high time to liberate yourselves from the spreadsheets and email threads.

Within your sales CRM, there is a certain amount of self-monitoring your agents can do. It’s reasonable to expect an agent to be on top of their own calls and pipeline — and good for their managers to have visibility into their team’s data too. Typically, a sales manager might track the number of calls per day, the pipeline created per week, the number of meetings per week, and the stage of deals. Keeping track of all of this in a spreadsheet sounds daunting, but using a real-time dashboard, or widgets embedded in the CRM make it easier to visualize, track, and share this data.

Sales data, like total sales, funnel, where deals are in your pipeline, which deal sources are successful, and how sales reps are doing, can be analyzed and lined up against company goals. And when it comes to sales data, the more you collect, the better. The largest data set possible will give your team the more accurate insight. Expensify, a Zendesk customer, analyzed millions of data points around their sales activities and quickly found opportunities to improve their sales process.

All about reporting in Sell

Service data

To understand why service data is important, we need to understand what modern self-service looks like. Rather than considering self-service to be its own channel (ie, a knowledge base stocked with articles), it’s helpful to consider the ways self-service intersects with other channels.

Chatbots are an example of self-service in live chat and messaging. A chatbot is often the first point of contact for a person reaching out to customer service. While the customer may want to speak to a person, it’s possible their query can be deflected to a self-service help desk article, or answered by the bot. Answer Bot, which can be programmed into Zendesk’s live chat and messaging solutions, offers up help center articles as a first point of service unless the customer wishes to escalate to an agent. Flow Builder, an out-of-the-box decision tree, can be used to program Answer Bot to make more complex decisions.

Tracking and iterating on data relating to self-service can help companies create a targeted approach to better serve their customers. Why prioritize self-service? It might be better for your business. Since the start of the pandemic, companies of all stripes have seen a surge in tickets, and the most agile of them are prioritizing self service. Over 70% of these agile companies have added new articles to keep pace with evolving customer needs, and at least 1 in 5 have increased the number of dedicated agents.

To track service data in Zendesk, users can access and share numerous dashboards. For example, a dashboard showing bot answers and resolutions by date to find out where bots can step in, or where to build out conversational flows that lead to resolution. A dashboard that shows resolution and click-through rates by date might show when customers are uninterested in self-service and prefer real-time conversations — which could be further reflected in a dashboard showing agent-assisted versus unassisted bot resolutions. And to see which helpdesk articles need to stay updated, users can table Answer Bot activity by article. If certain articles are getting the bulk of attention, the data might be able to help you figure out what it is about your product or service that could be improved.

The guide to optimizing self-service with the right metrics

Customer data

Customer data can be broken down into two categories: Data about the customer, and KPIs from your customer base.

Data about the customer, like their name, their conversation history, preferred channels, or previous purchases, are relevant to your agents because it provides the context needed to create personalized and efficient customer experiences, as well as more personalized and engaging interactions. A customer who starts a conversation with a bot, for example, shouldn’t have to repeat themselves when an agent takes over. A customer who starts a conversation via chat before getting a follow up email shouldn’t have to repeat themselves either. Highlighting and displaying relevant information for agents — while keeping customer data secure — is key to eliminating common CX roadblocks.

Customer service KPIs, like CSAT (customer satisfaction), ATR (average time to resolution), or FRT (first response time) tell you a lot about how your support team is doing. Different channels have different average response times. Different channels have different average CSAT scores — and so do different rated tickets. Zendesk users can access dashboards that show CSAT scores alongside rated tickets by date to get an impression of how their support team is handling customer requests. These dashboards can be sliced by channel or priority to see which are doing well and which need improvement. Insights gleaned from these dashboards can affect the customer experience directly, especially if your team decides to add more channels.

6 customer service KPIs you need to track