Connect Data from Yext to Looker

You can get your Yext data into Looker to make more informed business decisions. This simple and quick guide gives you easy instructions on how you can extract your data and then analyze it.


Yext is a location data management software that automatically syncs your information across 50+ major local directories and search engines. Yext lets you store, manage, edit, customize, and sync information about your locations across all Yext products, including: Business Name, Address and Phone Number (NAP)


Looker is a popular analytics tool that helps bring data and business teams together by making it quick and easy for everyone to explore and comprehend the data which drives business. Looker Analytics can integrate with any SQL database and data warehouse, like Greenplum and Amazon Redshift. From agile startups to large corporations, savvy companies can easily leverage Looker's amazing analysis capabilities to monitor the overall health of their businesses and also make more data-driven and sound decisions. Looker is great as it lets companies access, describe, control, explore, and visualize all their data across any web browser, on any device. Looker can help companies of all sizes use data to drive their business activities and decisions in the right direction.

Extracting data

Before loading your data into Looker, you will have to prep it first. If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. Google Ecommerce's documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. In these cases you'll likely have to create additional tables to capture the unpredictable cardinality in each record.

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Preparing data

Click Knowledge Graph in the top navigation bar.Select the entities you would like to export. Otherwise, it will default to export your primary entity type.Click on the More Actions button and select Export Entities.Review the Data Format and File Format of your export.To export historical data that was previously stored in the platform, click Edit in the Export Data as of field, select your desired option, and click Save.Note: You can export data up to 30 days after an edit was made. To make other changes, click on the Edit button for the desired setting. Then click Save.Click Continue.(Optional): Select an Export Scheme to export the data in a specific format.This allows you to export data in a specific format so it can easily be uploaded to a third-party platform.Select the checkboxes next to the fields you would like to add to the export.(Optional) To reorder the fields, click Actions next to the desired field, and select Configure. Then drag and drop the fields into your desired order by clicking on the three lines (mceclip0.png).(Optional) To rename the column names, click Actions next to the desired field, and select Configure. Then type in any text into the Column Name textbox.Click Continue to export your entity information.(Optional) To save your export for the future, enter a name for your export in the text box, and click Save Export.

Loading data

Although Looker does not connect directly to an Excel spreadsheet, there is a way to upload data via a derived table. This method works if you have a limited number of columns and rows, such as monthly forecasting data that is not very scalable for large spreadsheets. This data is also static and will not automatically update if the underlying spreadsheet data changes.

Keeping data up to date

If you've made it this far, congrats! You probably have a written a program or script to extract your data and move it into Looker. Now it's time to think about how you will keep this data up-to-date by loading updated or new data. Of course, you can just replicate all your data every time you have updated your records, but that would be extremely manual and time-consuming. Luckily there is a better way. The key is building your script so that it can sense incremental updates made to the data. Thankfully, Yext’s API results include fields so that you can identify those records which are new since the last update you made (or since the most recent record you have copied). Once you have taken new data into consideration, you can easily set your script either as a continuous loop or cron job to pull down new data as soon as it appears. And keep in mind that, as with most codes, once you write it, you will need to maintain it. In case Yext changes its API, or if the API sends a field containing a data type that your code does not recognize, you might have to change the script.

The Easiest And Fastest Way To Do It

If all this sounds a bit overwhelming, don't worry -- there is an easier way to get this done! Thankfully, products like Improvado were developed to move data from Yext to Looker automatically. Using Improvado, you can easily combine the most crucial and relevant data from your ad campaign into a dashboard. You can then connect this data to Looker.