Building a Data Driven Customer Success Team

Defining the Metrics and Key Performance Indicators of the Customer SuccessTeam at Beamery

Last week we continued with our new blog series Building a Data Driven Organisation at Beamery with how we built a data driven marketing team. In this weeks post we intend to present — in the same manner — the culmination of our research from both external sources and internal interviews to give an extensive and detailed list of the metrics and KPIs of interest to a customer success team.

A High-Level Overview of Customer Success Metrics and KPIs

To generalise, the metrics and KPIs requested by the customer success team generally fall into two categories.

The first, Operations Metrics, involves viewing customer success from an operations perspective. These metrics revolve primarily around Conversation Metrics between the customers and the customer success representatives and the Response Metrics which follow from those conversations. The response metrics are generally defined as the customer success team’s ability to liaise with the relevant Beamery team and facilitate solutions to customer problems.

The second, User Metrics, involves leveraging the data within a users account in order to produce informative usage analytics and descriptive statistics of their behaviour(s). These allow the customer success team members to consult effectively on how to use the Beamery application better from a customer perspective and compare customer usage across Beamery. This of course opens the door to potential up-sell, especially if one can quantify that the given feature or increased usage quota etc. within that up-sell will lead to a positive gain for the customer.

Low-Level Descriptions of the Customer Success Metrics and KPIs

Operations Metrics

The Conversations Metrics relate to the scenario whereby a customer has contacted Beamery to discuss the product, usually with an issue that requires resolution. The metrics of importance include:

Total Conversations. These are the total number of conversations initiated by an individual representing one of our customers. Total conversations are often separated further and split-by a secondary dimension. Frequently used secondary dimensions include:

• Total Conversations by Month
• Total Conversations by User
• Total Conversations by Conversation Tag

Time to First Response. The time taken for a Beamery customer success representative to reply to the customer’s message. Whilst Beamery’s customers are predominantly based in the United States of America, we have customers based on every continent. Messages therefore can arrive at any time. We operate a rota system to ensure that the various incoming channels are continuously monitored during the working week and automated responses are in place for the evenings and weekends.

Time to Close. The time taken for a Beamery customer success representative to mark the conversation status as “Closed”, meaning that the issue has been successfully [or adequately] resolved and appropriately logged.

Conversation Rating. Following the closure of the issue, this is the rating given by the customer, this is usually given via an NPS score. An NPS score is a survey indexed from -100 to 100 that asks the question “On a scale of 0‒10, how likely are you to recommend [the company] to a friend or colleague?”

The Net Promoter Score classifies respondents who selected any number between 0 ‒ 6 as a “detractor”, any who selected 7 or 8 as “passives”, and any who selected 9 or 10 as “promoters”.

One calculates the NPS score by subtracting the number of Detractors from the number of Promoters and dividing through by the total number of Respondents.

User Metrics

The User Metrics, as touched upon above, relate to the usage of the application itself from the point of view of improving our ability to consult and up-sell. At Beamery, we have built out an advanced suite of recording and tracking tools. These make use of Google Analytics, Heap Analytics, and Segment (Identify calls, Page transitions, and Track events built into the application code-base). The combination of all three tools allows us to understand and report upon our user behaviours and actions. This allows us to build out benchmarks and distributions across industry segments.

Number of Active Users. These are unique individuals who have used the application at least once. These numbers are compared against the number of licences the company has bought. Number of active users is often split further by week to track the changes in active users.

Number of User Sessions. These are the number of unique users who have performed a session within the application, where a session is defined as a single span of time where the user interacts with the application in some way. A session is ended following 30 minutes of inactivity. Number of user sessions is often split further by week to track the changes.

Length of User Sessions. This is the length of time (usually an average) each unique user of the application spends within the application or on a given page.

Usage of Campaigns. Campaigns in Beamery refer to email campaigns. These allow a user to create a template to be sent out to multiple candidates, where the candidates to be contacted may be filtered by their status, their vacancy stage, or any other field (both custom or default) that is available within the Beamery application. Additionally, these can be automated for specific times of day, or in response to specific interactions such as the message having been read but not a replied too.

The Key Dashboard Metrics for the Customer Success Team

The key performance indicators for the customer success team, and the ones that will allow the C-level team to monitor their progress and success are:

• Unique Conversations Created
• Time to First Response of Ticket
• Time to Close of a Ticket
• Customer Satisfaction

The remaining metrics as set out above will be used by the customer success team themselves to monitor their own progress and success on a more granular level.

To Be Continued …

The next post in our series will be defining the metrics and key performance indicators of the product team.

The primary external sources used in our research for the customer success metrics and KPIs were articles posted by GeckoBoard. Some of the definitions have been copied verbatim, where this is the case, every reasonable effort has been made to provide a link to the original source material.