Close to Google Data Studio

This page provides you with instructions on how to extract data from Close and analyze it in Google Data Studio. (If the mechanics of extracting data from Close seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Close?

Close provides an inside sales SaaS and CRM platform that bundles calling, SMS, and email in a single platform. Users can make and receive calls and take business notes without getting on a phone or leaving the application. The software provides a single automated sales workflow system.

What is Google Data Studio?

Google Data Studio is a simple dashboard and reporting tool. It's free and easy to use, but it lacks the sophisticated features of higher-end reporting software. Many of the connectors it supports are for Google products, but third parties have written partner connectors to a wide variety of data sources. Its drag-and-drop report editor lets users create about 15 types of charts.

Getting data out of Close

You can use Close's REST API to get data about contacts, leads, opportunities, and many more objects into your data warehouse. For example, to get a lead, you could GET /lead/{id}/.

Sample Close data

Here's an example of the kind of response you might see when querying a lead.

{
    "status_id": "stat_1ZdiZqcSIkoGVnNOyxiEY58eTGQmFNG3LPlEVQ4V7Nk",
    "status_label": "Potential",
    "tasks": [],
    "display_name": "Wayne Enterprises (Sample Lead)",
    "addresses": [],
    "name": "Wayne Enterprises (Sample Lead)",
    "contacts": [
        {
            "name": "Bruce Wayne",
            "title": "The Dark Knight",
            "date_updated": "2019-01-06T20:53:01.954000+00:00",
            "phones": [
                {
                    "phone": "+16503334444",
                    "phone_formatted": "+1 650-333-4444",
                    "type": "office"
                }
            ],
            "created_by": null,
            "id": "cont_o0kP3Nqyq0wxr5DLWIEm8mVr6ZpI0AhonKLDG0V5Qjh",
            "organization_id": "orga_bwwWG475zqWiQGur0thQshwVXo8rIYecQHDWFanqhen",
            "date_created": "2019-01-01T00:54:51.331000+00:00",
            "emails": [
                {
                    "type": "office",
                    "email_lower": "thedarkknight@close.io",
                    "email": "thedarkknight@close.io"
                }
            ],
            "updated_by": "user_04EJPREurd0b3KDozVFqXSRbt2uBjw3QfeYa7ZaGTwI"
        }
    ],
    "custom.lcf_ORxgoOQ5YH1p7lDQzFJ88b4z0j7PLLTRaG66m8bmcKv": "Website contact form",
    "date_updated": "2019-01-06T20:53:01.977000+00:00",
    "html_url": "https://app.close.io/lead/lead_IIDHIStmFcFQZZP0BRe99V1MCoXWz2PGCm6EDmR9v2O/",
    "created_by": null,
    "organization_id": "orga_bwwWG475zqWiQGur0thQshwVXo8rIYecQHDWFanqhen",
    "url": null,
    "opportunities": [
        {
            "status_id": "stat_4ZdiZqcSIkoGVnNOyxiEY58eTGQmFNG3LPlEVQ4V7Nk",
            "status_label": "Active",
            "status_type": "active",
            "date_won": null,
            "confidence": 75,
            "user_id": "user_scOgjLAQD6aBSJYBVhIeNr6FJDp8iDTug8Mv6VqYoFn",
            "contact_id": null,
            "updated_by": null,
            "date_updated": "2019-01-01T00:54:51.337000+00:00",
            "value_period": "one_time",
            "created_by": null,
            "note": "Bruce needs new software for the Bat Cave.",
            "value": 50000,
            "value_formatted": "$500",
            "value_currency": "USD",
            "lead_name": "Wayne Enterprises (Sample Lead)",
            "organization_id": "orga_bwwWG475zqWiQGur0thQshwVXo8rIYecQHDWFanqhen",
            "date_created": "2019-01-01T00:54:51.337000+00:00",
            "user_name": "P F",
            "id": "oppo_8eB77gAdf8FMy6GsNHEy84f7uoeEWv55slvUjKQZpJt",
            "lead_id": "lead_IIDHIStmFcFQZZP0BRe99V1MCoXWz2PGCm6EDmR9v2O"
        },
        {
            "id": "oppo_klajsdflf8FMy6GsNHEy84f7uoeEWv55slvUjKQZpJt",
            "organization_id": "orga_bwwWG475zqWiQGur0thQshwVXo8rIYecQHDWFanqhen",
            "lead_id": "lead_IIDHIStmFcFQZZP0BRe99V1MCoXWz2PGCm6EDmR9v2O",
            "lead_name": "Wayne Enterprises (Sample Lead)",
            "status_id": "stat_4ZdiZqcSIkoGVnNOyxiEY58eTGQmFNG3LPlEVQ4V7Nk",
            "status_label": "Active",
            "status_type": "active",
            "value": 5000,
            "value_period": "monthly",
            "value_formatted": "$50 monthly",
            "value_currency": "USD",
            "date_won": null,
            "confidence": 75,
            "note": "Bat Cave monthly maintenance cost",
            "user_id": "user_scOgjLAQD6aBSJYBVhIeNr6FJDp8iDTug8Mv6VqYoFn",
            "user_name": "P F",
            "contact_id": null,
            "created_by": null,
            "updated_by": null,
            "date_created": "2019-01-01T00:54:51.337000+00:00",
            "date_updated": "2019-01-01T00:54:51.337000+00:00"
        }
    ],
    "updated_by": "user_04EJPREurd0b3KDozVFqXSRbt2uBjw3QfeYa7ZaGTwI",
    "date_created": "2019-01-01T00:54:51.333000+00:00",
    "id": "lead_IIDHIStmFcFQZZP0BRe99V1MCoXWz2PGCm6EDmR9v2O",
    "description": ""
}

Loading data into Google Data Studio

Google Data Studio uses what it calls "connectors" to gain access to data. Data Studio comes bundled with 17 connectors, mostly to pull in data from other Google products. It also supports connectors to MySQL and PostgreSQL databases, and offers 200 connectors to other data sources built and supported by partners.

Using data in Google Data Studio

Google Data Studio provides a graphical canvas onto which users drag and drop datasets. Users can set dimensions and metrics, specify sorting and filtering, and tailor the way reports and charts are displayed.

Keeping Close data up to data

Now what? You've built a script that pulls data from Close and loads it into your data warehouse, but what happens tomorrow when you have new transactions?

The key is to build your script in such a way that it can identify incremental updates to your data. Thankfully, Close's API results include fields like date_created that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've take new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.

From Close to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Close data in Google Data Studio is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Close to Redshift, Close to BigQuery, Close to Azure Synapse Analytics, Close to PostgreSQL, Close to Panoply, and Close to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Close with Google Data Studio. With just a few clicks, Stitch starts extracting your Close data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Google Data Studio.