Customer Success | 4 minute read

The Three Tiers of Customer-Facing Data

Charts displayed on a laptop

The customer success world thrives off of data. You define what drives value for your customers, unlock ways of achieving that value, and then track the added value over time. This is done through data, and customers do the same thing to understand the realized value and potential value of their software subscriptions. But not all data is created equally.

We will look at three different tiers of data, how they can be used, and the cost/benefit tradeoff of exposing that type of data to customers.

Tier 1: Metrics

Metrics are numbers that gauge performance. Generally, we know that a metric is valuable and is accurate at tracking a particular concern. For example, a number that tracks "how many qualified leads are we receiving from this campaign?" is going to measure the exact performance of our campaign—there is nothing unknown about it.

Metrics are tracked on some recurring frequency: daily, weekly, monthly, etc. Metrics are charted over time to see how realized value has increased or decreased over that period. Charts can also serve as benchmarks when compared over past periods of time.

Some metrics are universally important to all customers, while some metrics are uniquely important to specific customers. It can be difficult to understand the best metrics when they become specific to a single customer. Luckily, the next tier of data can bridge the gap for us.

Tier 2: Analytics

Analytics are data that customers need to occasionally review to discover trends and new insights. Customers use analytics to identify what is important, and ultimately to help inform their decisions on value and success.

If we take our previous example of qualified leads from a campaign, we might define a set of analytics that reveals traffic source, time on site, and conversion rate. We don't have a specific metric that we're looking for here, but we can discover insights like "the majority of our traffic is coming from our media campaign, resulting in 7% higher conversions." This insight can inform a decision that we should double-down on our media campaign due to its success.

Customers will turn analytics into metrics—this is a good thing. It means that they have identified a way to track value, even if it's not formally supported as an official metric. Take note when this happens, as there may be an opportunity to extract a new metric that adds values to many customers.

Tier 3: Export Data

Export data is the raw data that powers the higher tiers. In the case of our campaign example, this would consist of the website visits, source attribution, campaign cost, conversion rates, and more. This is a lot of data to keep track of!

The power of export data is that it allows customers to define their own metrics and analytics. They can even do this across platforms in a way that product analytics would not be able to. This becomes especially important when we consider up-market customers that have dedicated data teams and complex needs. These customers can use the raw data to power valuable analytics and metrics that are custom to them.

Details create trust

Trust in data increases from metrics -> analytics -> export data. For example, if a customer calculates a metric on their own and it does not match your metric, they are not going to be happy. If you can show the analytics and raw data that backs the metric, then it increases trust that the calculation is actually correct.

Increase the level of detail available to your customers in order to deepen the trust they have in your data.

What to prioritize for your customers

There are a lot of options when it comes to what data to prioritize. That isn't necessarily a good thing, because more options means more effort from a product organization. You're going to have to make cuts.

Customers will primarily use tier 1 metrics to decide if they are receiving value from your product. This will carry into renewal conversations. Happy, successful customers with a positive ROI will probably not churn. You can do a few things to maximize the likelihood of this:

  • Understand the value that a customer expects to get from your product.
  • Determine which metrics track this value. Confirm the determination with your customer at the beginning of the relationship.
  • Display these key metrics, including their progress and trends, so that customers can view and track them on a daily / weekly / monthly basis.

Because detail creates trust, it's also a good idea to make raw data exports available to customers when possible. However, this is difficult to do when large amounts of data get created. Export data increases the likelihood that customer-success managers or customers can create their own reports in Excel in a worst case scenario.

How can Clove Help?

Clove unifies your customer success tools into a single experience for your customers. Our completely brandable and customizable hubs give customers all of the information and processes they need—all in a single pane of glass.

Clove allows you to place both universal and custom key-value metrics, from any analytics source, directly in front of customers.

Want to learn more?
Talk to us.