Building Customer Support Analytics infrastructure in minutes

Why anyone needs customer support analytics? Because things break usually.

How you fix them varies. But analyzing and measuring your customer support metrics is equally important to all the rest of a company’s departments.

In my life as an engineer, when I needed to buy something I wanted to be technically impressive and always to have great support. Either that was a laptop or my kid’s little toy. Here at Blendo, we are engineers at heart. We have our Customer Support analytics and value all responses for that same reason. You are looking for a solution with great support.

Currently, we use Intercom to help our customers. But as we grow our customer’s needs are growing too. Our needs for more advanced customer support analytics grow with them. In fact, they have to scale even faster.

But they say to eat your own dog food right?

Today we’re sharing how we built a customer support analytics infrastructure in minutes instead of weeks or months that can support a growing company and can quickly scale with it.

We gather data and take into account data sources from:

• Customer Success services
• Customer Support services
• Project Management and Software development tools
• Billing data

into one data warehouse where we run all our customer support analytics and metrics.

Although the number of data sources you may use can vary, I would like you to follow through the process. I want to show you how building such an infrastructure is simpler than it sounds.

If you are in a hurry to tell me that yes, these cloud services offer APIs to extract data, so building and maintaining these integrations is easy, then you are right!

I will not disagree with you.

It is doable.

But with what cost in resources, time and people?

So let’s start. But first things first.

Load your data into a data warehouse

Currently, we push all our data in a PostgreSQL instance in AWS. As we are proud Amazon Web Services Partners, we could use an awesome Amazon Redshift cluster, but we resisted the urge 🙂

Customer Success services

Last time we talked about Customer Success and how we track our customer success metrics. Intercom is a very popular customer support platform. Although they have an analytics dashboard in their app, it does not fit in all the complex scenarios and use cases.

Building a data pipeline that will extract data from Intercom will get you a rich amount of data. If we take a look at the kind of data from Intercom you can get into your data warehouse, you will quickly find out that there are a lot of customer support questions you may answer.

Integrate data from Intercom

How long do you think you will need to integrate Intercom and sync your data into your data warehouse? It is actually two steps.

One… Connect Intercom as data source.

Two… Sync your Intercom data

There you go. Integrating Intercom and loading all your data into your data warehouse is a matter of minutes.

For more details read this guide on how to setup an Intercom integration.

Customer Support services

Customer Support cloud services have super valuable data. If you drill down to your tickets and customers, you may find out how support affects sales or retention.

Having such data you can measure customer support performance, ticket response and resolution time or how all of these affect your customer retention. Or even find out if the clients who pay more create more support tickets or not.

Integrate data from Zendesk

There goes 2 out of 4 data sources.

Done!

For more details read this guide on how to setup a Zendesk integration.

Project Management and Software development tools

There is an extensive list of Project management/task related and software development tools. Usually, their data are not that many, but they are context sensitive. If they are enriched with data from support and software development they can prove gold. You may combine data from tools like Gitlab, Pivotal Tracker or Jira and see how response and development time of a support ticket affects your customers.

We will make use of webhooks that provide event data as they happen and giving you almost immediate incremental updates to your data warehouse.

Integrate data from Pivotal Tracker

We will need to setup a webhook in Blendo.

and then add it in Pivotal

Done!

For more details read this guide on how to setup a Pivotal Tracker integration.

Integrate data from Gitlab

Again let’s add a new webhook in Blendo and then just add it in Gitlab.

3 down, 1 to go.

For more details read this guide on how to setup a Gitlab integration.

Billing data

This is the most no-brainer here. How can I even know who pays or not? What amount he pays and which tier he is.

Having my customer support data enriched with my billing data from Xero or Stripe will provide an entirely different dynamic in my customer support analytics view.

Integrate data from Xero

Getting started importing data from Xero is easy. We will need to connect Xero as a Data Source and Blendo will import your Xero data and load it into your data warehouse.

For more details read this guide on how to setup a Xero integration.