Build customized reports using multiple instances of Google Analytics

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It is challenging to build a complete and accurate view of your customers. It requires you to collect and standardize data from every single customer interaction, and move it to a unified place where your team can start analyzing it. While Segment streamlines this process for you, companies that support multiple teams, business units, or geographies experience an added layer of complexity.

In addition to the complete customer view that you’ll naturally want to build, you’ll also need to provide each business unit of your company with real-time data dashboards, so execs and other decision-makers can make decisions based on timely and relevant data. 

Say, for example, you have separate teams managing North America, Europe, Latin America, and APAC. While the head office will want to see information about the health of the collective business, each of those regions would benefit most from reports that are specific to their region. 

This is easy to accomplish using Segment’s Multi-Instance Destinations. With it, you can send different data to different instances of your analytics destination (in this recipe, we’ll use Google Analytics), so each regional executive team can easily access the slice of the company’s customer data that’s most relevant to them.

Step 1: Add your Google Analytics destination

This recipe assumes you have Segment installed, and that you’re tracking events. If not, check out our documentation here.

The first step is to ensure the data you’re tracking with Segment is flowing to your analytics tool of choice (as mentioned above, we’re using Google Analytics in this example).

1. From your Segment Destinations page, click “Add Destination”.
2. Search for “Google Analytics” within the Destinations Catalog and confirm you’d like to connect.
3. Give your destination instance a name. Use a name that’s descriptive and will make sense to other people on your team. In this example, we’re creating separate instances for each geographic region of our business, so we’ll call this instance Google Analytics North America. You can edit the names of your destination instances anytime, to reflect changes in org structure. 
4. Drop in your Tracking ID. The ID you use will depend on what source you’re using for your data. In this example, you’re sending data from a website using Segment’s new Javascript library, Analytics.js 2.0, so drop in your Website Tracking ID  (you, can find it in the Tracking Info tab on the Admin Page of Google Analytics). Configure other relevant settings, as described in Segment’s Google Analytics Destination Documentation. We recommend fully configuring one destination instance, so you can copy these settings when you create your other destination instances.

Step 2: Add additional Google Analytics destination instances

1. From your Segment Destinations page, click “Add Destination”.
2. Search for “Google Analytics” in the Destination Catalog again, and confirm you’d like to connect.
3. Give your new instance a name (here we’re calling it Google Analytics APAC, because it’s for the execs in our Asia-Pacific region). You can either fill in the settings manually, or copy settings from an existing Google Analytics destination instance. This makes it easy to set up new instances. You can update the settings of each destination instance independently.
4. Drop your credentials into this destination instance, as before. 

Step 3: Set up destination filters for each Google Analytics destination instance

1. Set up a destination filter for your first Google Analytics destination instance. Open a Google Analytics destination instance, click “Filters” in the top menu, and then click “New Filter”. You’ll need to add filters to each of your Google Analytics destination instances to ensure that only the relevant data goes to each Google Analytics destination instance.
2. Configure your filter. You can choose whether you want to exclude particular events, exclude particular fields, or only send particular events to your destination instance. For this example, we are only sending events to the North America destination instance when the value of the region  property is north_america. 

Step 4: Build reports in each Google Analytics property 

The last step in the process is to build reports in each Google Analytics property. In this example, we have separate Google Analytics properties for each geographic region. Each region has unique products and different sales targets, so it’s important to provide each regional group of execs with a dashboard that answers their region-specific questions. 

We used Google Analytics in this example, but you can create multiple instances of any analytics destination and send different data to each destination. 

For example, you could:

• Use multiple analytics accounts to provide each business unit with relevant reports — and use a separate analytics account to provide execs with data from all business units.
• If you’re working with channel sales partners, give each partner access to analytics about their customers — not the customers of other sales partners.
• Send data to different Amazon Kinesis destination instances, to power multiple real-time dashboards and machine learning applications.
• Send data to multiple analytics accounts during a migration.

Wrapping up

Here’s what we’ve achieved in this recipe:

• Configured multiple Google Analytics destination instances—one for each regional business unit—using Multi-Instance Destinations
• Set up unique destination filters for each Google Analytics instance to ensure that only the right set of data made it to the each instance of the Destination.