Make the Most of Your Snapchat Data in BigQuery

Snapchat and BigQuery are a natural fit for data modeling, business intelligence and data activation – especially for retail brands interested in optimizing their overall business performance, acquisition and retention marketing programs, and merchandising and fulfillment operations decisions.

Snapchat is a multimedia messaging app where users can send photos and videos that disappear after being viewed. It features Stories, a format for sharing temporary content with friends, and Discover, a platform for content creators and publishers. Snapchat is known for its unique filters, lenses, and a focus on ephemeral, visual communication. BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data. Use built-in ML/AI and BI for insights at scale. Together, the software application and cloud data tooling provide business and data practitioners with an opportunity to analyze and optimize digital marketing, social and paid media channels to drive profitable growth.

Connect to Snapchat

The first step toward useful, modeled Snapchat data in BigQuery is to connect the source and destination systems. There are many legacy tools available in market that handle the ETL or ELT transfer of Snapchat data to BigQuery, and there are emerging tools that accomplish this transfer while providing value-added services like local data logging, and semantic data labeling and mapping along the way – making Snapchat data modeling, analytics and activation easier once the data is landed in BigQuery.

To connect to Snapchat, follow these easy steps

• Open SoundCommerce in any browser. Open the “Intelligent Pipeline” application from the top right navigation menu. Select “Sources” from the left navigation menu. Choose “Add New Source” from within the Sources pane to open the data source library.

• Search or browse to find “Snapchat” within the data source library.

• Complete the “Connection Setup” form with your credentials and token to securely connect to Snapchat and begin collecting source data.

Log Snapchat Data for Flexible Modeling in BigQuery

There are a few more considerations to address along the way. First, what happens if Snapchat is unavailable for some reason, or the data you’re expecting has been purged by Snapchat? What happens when Snapchat changes their API schemas and data scope? What happens if you need to reinterpret your Snapchat data for a new use case in the future?

You’ll want your Snapchat data immutably logged locally, just upstream of BigQuery to ensure you have the data and data flow flexibility you need to future-proof your Snapchat data and models. SoundCommerce provides permanent logging of Snapchat data upstream of BigQuery to ensure failover and future-proofing. Regardless of how you connect your Snapchat and BigQuery data, you’ll want a data lake or event log in the middle to ensure data integrity and modeling flexibility.

Define and Label Snapchat Data for BigQuery

As new technologies arise and best practices evolve, traditional integration tools like ETL and ELT data pipelines are giving way to intelligent pipelines that help prep data for BigQuery starting at ingest. Simply moving JSON from Snapchat to BigQuery leaves all the work for your data team in BigQuery.

As you onboard your Snapchat data into BigQuery, you’ll want to create semantic labels and metadata that describe the Snapchat data for easier unification and modeling across other systems and data in BigQuery.

There are third-party solutions that will catalog your Snapchat data and generate semantic labels and mappings after you’ve landed it in BigQuery. With SoundCommerce, the Snapchat data is defined and labeled on its way into BigQuery instead, to avoid this costly rework later. You’ll end up with business-ready entities like orders, customers, products and campaigns, making it much easier to model your Snapchat data in BigQuery.

Map Snapchat Entities to BigQuery

Once the raw Snapchat data has been organized into useful entities, it’s time to map the Snapchat data into useful tables in BigQuery.

Why do defined and labeled entities from Snapchat matter so much? The main reason is that Snapchat data needs to be combined with data from other SaaS and on-premise software systems in useful ways. Landing raw Snapchat data in BigQuery without this semantic understanding means data engineering and analyst teams must do all of the heavy lifting regarding the meaning of the Snapchat data and the standardization of the meaning of that Snapchat data from scratch in BigQuery.

Defining, labeling and mapping the Snapchat data on the way in means much less effort once the data is landed in BigQuery.

Materialize Snapchat Data in BigQuery

Next, you’ll establish a secure connection to BigQuery:

• Select “Destinations” from the left navigation menu. Choose “Add New Destination” from within the Destinations pane to open the data destination library.

• Complete the “Connection Setup” form to securely connect to BigQuery to establish a secure destination for your labeled, mapped and modeled data.

That’s it! You now have logged, labeled and mapped data from Snapchat flowing securely to BigQuery.

Model Snapchat Data in BigQuery

Once you have well-formed entities from Snapchat onboarded to BigQuery, it’s time to build useful analytical and behavioral models on the Snapchat data – and combine the Snapchat data with data sets from other systems in BigQuery for more advanced, cross-dimensional analysis.

You can build your own analytical models on the Snapchat data in BigQuery using languages like SQL and Python, organized into model libraries in tools like DBT or Coalesce. With SoundCommerce, you get prebuilt analytical models for Snapchat running in BigQuery, with ready access to the model source code in DBT.

Host the Modeled Snapchat Data in BigQuery for Analytics

BigQuery supports reporting and visualization through a wide variety of analytics tools including Sigma, Tableau, Looker, Power BI and Microstrategy to name a few. You can build your own dashboards, tabular views and graphs in any of these tools to reveal insights about Snapchat in your BigQuery models. SoundCommerce provides pre-built embedded reports in Sigma to reduce the time, cost and risk of BI reporting of Snapchat data out of BigQuery – so you can start making better decisions and taking better action as soon as you’ve connected Snapchat to BigQuery.

Host the Modeled Snapchat Data in BigQuery for Campaign and Customer Activation

Whether your marketing team uses Snapchat for activation – or uses other tools and channels or both to take action on the data – you’ll want to be able to easily move your modeled Snapchat data in BigQuery to your most important marketing applications.

If you’ve followed the steps above to properly onboard and model your Snapchat data in BigQuery, it’s easy to use reverse ETL (rETL) tools like Census or Hightouch to orchestrate the data from there, or use SoundCommerce native orchestrations to push data into common channels and applications like Facebook, Instagram, TikTok, Braze, Klaviyo, Insider or Dynamic Yield to put the Snapchat data in BigQuery to use!

Getting Your Snapchat Data Defined, Labeled, Mapped and Modeled in BigQuery is Easy!

SoundCommerce can automate the steps necessary to bring Snapchat data into BigQuery, addressing the key functions of raw Snapchat data logging, Snapchat semantic definitions and mappings, and pre-built Snapchat data models that are analytics- and activation ready in BigQuery.

Contact us today to get started with Snapchat in BigQuery!

Technical Resources for Integrating
Snapchat Data with BigQuery

More information and technical specifications for data collection from Snapchat is available at:

Snapchat API Documentation

More information and technical specifications for data ingest into BigQuery is available at:

BigQuery API Documentation