The Ultimate Customer Service Dashboard


  • A good customer service dashboard focuses on the most essential role-based key performance indicators (KPI), prioritizes KPIs based on importance or timing, and brings real-time visibility to progress and variances.
  • A great customer service dashboard is interactive, permits data manipulation such as What-If analysis and supplements metrics with industry benchmarks for context. It displays forward looking analytics and shows the financial impact of both action and inaction.
  • The best customer service dashboards align customer support activities with company priorities, permit real-time predictive modeling to show how changes in any area cascade through the contact center and company, and link KPI results to recommended actions such as a Playbook so the findings advance from descriptive reporting to prescriptive recommendations. It's this level of reporting that shifts information value from delivering bad news too late, to delivering the foresight that prevents bad news. It's this level where data becomes the contact centers most valuable asset.
Johnny Grow Revenue Growth Consulting

Dashboards are a top delivery tool to get the right information to the right person at the right time.

Unfortunately, the bad news is that most contact and call center dashboards are visually appealing but don't gain adoption. Agents and managers say they are not useful or a waste of time. They display information that is not relevant, not helpful, confusing or already known. The top problem is that the information is somewhat interesting but not actionable.

The good news is that these problems are remediable. For example, we know information must advance from being merely interesting to inducing action for analytics to be effective. We also know the six ways to make data actionable are to make the metrics highly visual and interactive, align call center metrics with the most important company outcomes, shift from lagging to leading indicators, show KPIs alongside budgets or industry benchmarks for context, allow the data to be interrogated, manipulated and used for predictive analytics, and link the data findings to recommended actions such as a Playbook.

The Most Important Customer Service Dashboard Best Practices

Here are the seven most important dashboard best practices we use to gain wide scale user adoption and turn data into outcomes.

See the 6 ways to make contact and call center dashboards more actionable and the 7 most effective best practices to gain wide scale user adoption and turn data into outcomes.

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Customer Service Agent Performance Dashboard

Start with the Essential Questions to be Answered

When we work with a client do create a high impact dashboard, we start by identifying the most important questions that need to be answered. The first answer to really important questions is seldom the final answer, so it's important that the answers are measurable and extensible. Below are some examples.

  • [Shift Left modeling] For every 1 percent of calls rerouted to lower cost (case concurrency) channels such as webchat or social support, how much is total cost reduced?
  • [Call deflection] For every 1 percent of calls routed to customer self-service channels, how much is my agent labor cost reduced?
  • [Productivity] If I improve agent productivity by 1 percent, how much cost is removed?
  • [Scale] For every 1 percent increase in call volume, how much do agent labor and total costs go up?
  • [Preventative] How much inbound call volume is reduced if I implement proactive customer support? Or, how much inbound call volume is reduced if I increase root cause analysis (and resolve cases at their source)?
  • [Segmentation] What 15 percent of customers deliver 60 percent of company margins?
  • [Segmentation] What 5-10 percent of customers contribute negative profit?
  • [Retention] Which customers are about to churn?

Unless dashboards answer important questions that cannot be answered elsewhere, they will be ignored and become digital paperweights.


Measure What Matters

The right metrics will be role-based, relevant, personalized and insightful. That may sound easy but it's not. There are 3 challenges that get in the way of measuring what matters.

Customer Service Dashboard Metrics Hierarchy

First, most call center dashboards display data that by itself is without meaning. The best metrics deliver insights. Insights are not data, facts or statistics; these are all knowledge. Insights are the reasons, behaviors or learning behind the data, facts or statistics. The dictionary defines an insight as seeing below the surface. Call Center insights deliver new learning and something that teaches and induces action. If you are not delivering insights, you are probably not inducing action.

Second, they often display what is easy instead of what is important. For example, they display indirect and lagging measures rather than the leading indicators that forecast the most important results. This is common in dashboards that display internal process measures rather than customer measures which are more linked to business outcomes such as revenue performance.

This often occurs because the customer and business outcome measures don't exist in the CRM system. Customer metrics such as customer satisfaction (CSAT), customer engagement, customer lifetime value (CLV), customer retention, voice of the customer (VOC), customer sentiment, customer insights, RFM (recency, frequency, monetary), customer loyalty, customer health scores are many more are either not implemented or not available in the out of the box CRM application.

Unless CRM software implementors add essential measures, the CRM dashboard displays what is easy but not what matters.

Third, in what can feel like an ill-advised attempt to make up for the first two deficiencies, dashboards become crowded with marginalized information.

Recognize that fewer, higher impact measures outperform a broad collection of clouded metrics. Too many measures bury the signals among the noise and make information delivery unproductive. Customer support analytics work when they direct the users' attention to the highest priorities.

When implementing CRM software for customer support organizations, I often get asked how many metrics should be included on a dashboard. The answer is always the same, as many as will get acted upon.

The takeaway here is to keep your eye on the prize and recognize that less is more when it comes information design. In a different article, we identified the most important contact center metrics, so we won't repeat that here.


Prioritize Performance Metrics

A good contact center dashboard aids time management and staff productivity by showing what should be done first, next and so on.

They rank and sequentially display key performance indicators to prioritize action. KPIs are not all equal and should not be acted upon in random order.

To facilitate prioritization, metrics are organized and displayed in a progressive sequence from Headline KPIs to secondary and then tertiary KPIs. For example, headline KPIs generally display customer and revenue metrics.

When you prioritize KPIs by impact or time-based urgency, information shifts from being equal in importance to emphasizing what needs to be done first. Ranking KPIs aids prioritization, increases ease of use, creates routine, saves users time and makes information more actionable.

Customer Service Dashboard

Align to Stakeholder Outcomes

Stakeholders include agents, customers and the company so it's essential that performance metrics deliver line of sight to each of these constituent's most important outcomes.

Business leaders must seek out those top stakeholder outcomes and then work backwards to demonstrate how they will be realized, something we call the data maturation chain. Because this information frequently miss visibility to the company's priorities, I've included the below example.

Customer Service Dashboard Data Chain

As illustrated above, the data maturation chain shows stakeholder objectives, how they are measured, how they are achieved and the target measures that define success. Only with this type of holistic view can end to end progress be accurately forecast and measured.

If agent or departmental metrics don't directly roll up to demonstrate financial impact to the company, they will not be considered relevant outside the department. And if the call center dashboard does not include company priorities, then you have to ask yourself who outside the department cares?

To be clear, the contact center's revenue or profit contribution is the top metric. If leaders cannot show the company a return on its investment, then their existence is not considered strategic, executive support will wane, the organization will become a cost center and the company's objective for customer support shifts from revenue maximization to cost minimalization. It's a downward spiral that should be avoided.


Put Data in Context

Performance metrics become much more actionable when put into context. KPI results should display alongside budget or target goals for real-time performance measurement. They should show trends for directional progress and display peer-based benchmarks for industry context. Knowing where your performance stands compared to your direct competitors provides the most revealing perspective.

When designing information presentation with clients we generally display the industry benchmarks next to the company's actual performance. This does 3 things. First, the company recognizes where they stand and most need to improve.

Second, it enables predictive analytics. Many leaders like to apply predictive models to show how a 1 percent improvement in any KPI impacts customer satisfaction, lifetime value or retention as well as financial measures such as total revenues or margins. Other clients with KPIs below the industry median often prefer to see the customer and financial impact by improving their performance to the median level.

Third, knowing the financial upside impact allows managers to know how much they should invest to achieve that upside.

Inbound Call Cost Benchmark

KPIs without relative context obscure an understanding of materiality, lack insights, limit visibility and come across as arbitrary.


Make Data Interactive and Predictive

These instrument boards are fantastic tools to enable predictive analytics. They deliver their greatest value when they advance from statistics to insights, KPIs to KFIs (key future indicators) and static to interactive.

When users can perform pro forma or what-if modeling they can compare tradeoffs and better rank alternatives. Decision making shifts from hindsight to foresight and the data becomes much more actionable.

Most KPIs deliver historical performance. KFIs predict future performance. KPIs are equivalent to looking in the rearview mirror while KFIs are more like looking through the windshield. Predicting customer churn or implementing proactive customer support are examples of KFIs.

Projecting the financial impact of improved customer retention is another example. The below predictive analytic uses company data and industry benchmarks to forecast the financial uplift of improved retention. It answers the question of how much should be invested to achieve that benefit. In this client example, improving this company's annual retention from 85 percent to the industry median benchmark of 91 percent delivers a $594K annual revenue increase.

Customer Retention Predictive Analytics

At a more macro level, a customer service predictive analytic, such as the one below, shows the real-time impact of making changes to any one of several influential contact center drivers and seeing how the results cascade in other areas.

Customer Service Predictive Analytics

Good performance measures are neither standalone nor exist in a vacuum. Business outcomes are the result of a value chain derived from many activities. Modeling that value chain creates the most direct path to proactively driving the results that most matter.

The predictive pyramid shows the linkage from activities to tactics to slated outcomes. It's not just predictive, it's interactive to support dynamic modeling and What-If scenarios. Activities and tactics are not random figures or unsupported wishful thinking but based on company data and industry benchmarks.


Make Information Prescriptive

Lastly, make the information actionable with real-time alert notifications, next-best-action recommendations and links to Playbook Plays or recommended Methods.

Information that just shows agents or managers where they fall short is not that helpful. Better to show them where they should be via call center industry benchmarks and progress calculations, and then show how to get there using links to Playbook Plays or Evidence-based Best Practices.

For example, if customer retention is not on track, link that metric to customer segmentation, account health scores, customer churn prediction analytics or any one of several other methods that improve this imperative. Remember, KPIs are generally not the goals. They are mileposts that bring visibility to progress and spur needed actions to achieve the business outcomes.