Demo Series: Mobilize Your Customer Data with Snowflake and Blueshift

Demo Series Transcript: Mobilize Your Customer Data with Snowflake and Blueshift

Speakers:

• Kristen Session, Product Marketing Manager, Blueshift
• Eric Gordon, Senior Solutions Consultant, Blueshift

How the Blueshift-Snowflake Integration Gives Marketers Direct Access to Rich Data

Kristen Session: Welcome everyone, and thanks for joining us for another session in our demo series. I’m Kristen Session, Product Marketing Manager at Blueshift. Today we’re talking about the Blueshift-Snowflake integration and how it empowers marketers with direct access to customer data. I’m joined by Eric Gordon, Senior Solutions Consultant at Blueshift.

Eric Gordon: Thanks, Kristen. The Blueshift-Snowflake integration makes it possible for marketers to access customer, event, and product-level data already stored in Snowflake—and merge it with the behavioral and engagement data Blueshift collects across your touchpoints.

Setting it up is simple. You create an adapter, input your Snowflake credentials, and have your database admin run a few scripts. From there, marketers can import tables or views and control the fields, mapping, and scheduling without needing IT support.

Self-Serve Imports: How Marketers Can Pull Snowflake Data into Blueshift

Let’s walk through an example. In the import job setup:

• You select the table or view
• Choose and map fields
• Decide whether it’s a full or incremental import
• Schedule the sync and set up alerts if anything goes wrong

If your data changes or your team adds new fields in Snowflake, you can update the import settings yourself—no engineering help required.

Enhancing the Customer Profile with External and Offline Data

Once your Snowflake data is in, it enriches every customer profile. Let’s take one example:

• Before the integration, Blueshift captured profile info and site/app activity (e.g. location, likes, views)
• After importing Snowflake data, the profile now includes:
  • NPS scores from CX tools
  • Segmentation data from third-party enrichments
  • In-store purchase events

For one customer with both an online and in-store presence, this revealed that some users browsed online but only purchased in-store. That insight enabled them to tailor messaging and drive more in-store visits with personalized offers.

Feeding Snowflake Data Into Predictive Models

Blueshift’s Predictive Studio gives marketers access to models like purchase intent, churn likelihood, and content affinity. These models constantly update—but now you can enhance them with Snowflake data.

Let’s say you want to modify a purchase intent model:

• Add in-store purchases as an additional event input
• Include NPS scores as a new attribute
• Save and let the model retrain overnight

Marketers can test hypotheses by tweaking model inputs, see performance changes, and adjust campaigns accordingly.

Segmenting with Multi-Dimensional Data—No SQL Required

With Snowflake data available in Blueshift’s segment builder, marketers can:

• Filter based on in-store purchases
• Use NPS scores or appended third-party segments
• Combine online + offline behavior for high-value, unengaged users

No SQL or technical support needed—just drag and drop logic in the visual interface.

Orchestrating Journeys Across Channels with Unified Data

The final benefit is activation. Let’s say you build a segment of high-value but unengaged customers:

• Add them to a re-engagement flow in the campaign builder
• Use conditions to branch journeys:
  • Store-shoppers get SMS with in-store-only discounts
  • Online shoppers receive app-exclusive offers

All engagement data feeds back into Snowflake via bi-directional sync, so your analytics and BI teams can tap into it too.

Customer Success Story: How Malwarebytes Scaled Personalization with Snowflake + Blueshift

Malwarebytes had a wealth of data in Snowflake—subscription info, transactions, NPS, support tickets—but marketing couldn’t use it.

After integrating with Blueshift:

• They extended their welcome series from 4 touches to 7
• Messages adapted based on subscription type and app behavior
• Personalized upsell paths were introduced

The result? A more tailored experience powered by unified data, and a team that could operate independently without waiting on IT.

Final Takeaways

Kristen Session: Thanks, Eric. As you saw, the Snowflake integration makes it easy to:

• Access the freshest customer data
• Enrich profiles with offline and third-party attributes
• Build smarter segments and models
• Orchestrate data-driven journeys across every channel

To learn more, visit blueshift.com/contact-us or reach out to your CSM to enable the Snowflake integration.

Thanks again for joining!