Lucid increased ROAS by 52%, lowered engineering time by 12.5 hours, and increased new users by 37%
Lucid uses Hightouch to improve ROAS, increase new users, and lower engineering time.
Lucid now has a data-driven marketing tech stack built on Snowflake Data Cloud, dbt, and Hightouch.
With dbt and Snowflake, transformations that used to take hours can be done in minutes.
Using Hightouch and Snowflake, Lucid achieved a 52% increase in ROAS in Google and a 37% increase in new users.
Since adopting this Hightouch and Snowflake, Lucid’s engineering team has been able to save an average of 12.5 hours of engineering time per integration.
Due to the increasing number of complexities in a given business, it’s getting harder and harder to collaborate and express complex ideas in real-time. Lucid is a visual collaboration suite that combines virtual whiteboarding, intelligent diagramming, and cloud visualization to help hybrid teams of all sizes innovate faster. Lucid has millions of users across 180 different countries that leverage Lucid in some capacity.
The Challenge: Creating a 360-Degree View of the Customer
With a relatively limited data stack built around AWS Redshift, Lucid had no ability to personalize customer engagements across channels. There was no 360-degree view of the customer and this meant that it was impossible to optimize ad spend/performance or create customized marketing campaigns for different audiences. Transforming the raw data in Redshift was a nightmare, and sending data to various business tools and ad platforms was even more difficult.
The Solution: Building a Modern Data Stack on Snowflake With dbt and Hightouch
Snowflake as a single source of truth
Searching for a robust data platform that could act as both a data lake and a data warehouse, Lucid turned to Snowflake. Snowflake consolidates Lucid’s into a single centralized platform and lets the company ingest data from multiple sources.
Since implementing Snowflake, Lucid has been able to establish a single source of truth for all of its customer data and remove all of the barriers that came with Redshift.
Snowflake’s native separation of storage and compute gives Lucid unparalleled flexibility and makes it really easy to scale up or down as needed. With Snowflake powering analytics, Lucid can finally trust the data.
dbt for transformation and modeling
Once the data is in Snowflake, Lucid still has to transform it from its raw state and build data models so that it can be used not only for analytics but also for data activation. This is exactly where dbt comes into play.
Since implementing dbt, Lucid has been able to build a number of custom data models that are purpose-built for different marketing and analytics use cases. These models include everything from:
Offline conversion LTV valuations for different ad platforms
Custom audience segments for ad platforms and marketing campaigns
Instead of having to write ad-hoc SQL queries and leverage custom code, dbt gives Lucid the ability to standardize, orchestrate, and execute SQL queries directly against Snowflake. Lucid’s Strategy and Analytics Team uses dbt for 95-98% of all data their data transformations.
Hightouch for Data Activation
Before adopting Hightouch for Data Activation, Lucid built several custom data pipelines to send customer data to Marketo. However, this data came in from multiple different sources which meant pipelines were prone to failure. The constant data rate forced Lucid to keep a close eye on API limits and campaign backlogs. In addition to this, far more users were pushed into Marketo than were actually needed which meant Lucid was constantly fighting to keep the user count within the appropriate limit.
Sending data to ad platforms was also a nightmare. A single integration to Google Ads could take upwards of 12-16 hours of engineering time to build and this is not even accounting for the maintenance involved to keep it up and running; and with no built-in alerting it was nearly impossible to know when, where, or why specific failures occurred. Since pipeline breakages could have a huge impact on Lucid’s ad spending efficacy, manual CSV files were adopted instead.
Since implementing Hightouch, Lucid has been able to optimize bidding in Google Ads to achieve a 52% increase in ROAS and a 37% increase in new users. Instead of taking 12-16 hours to launch and test a custom API job, a single integration in Hightouch can be set up in 5 minutes and the most complex data models can be set up in 2-3 hours, saving an average of 12.5 hours. Before Hightouch, Lucid had no ability to create first-party audiences for specific marketing campaigns. Thanks to Hightouch Audiences Lucid can now target high-value customers and launch cross-promotion campaigns for existing customers based on usage.
As a PLG (Product-led-Growth) company driving product usage and accelerating adoption is vitally important to Lucid. With Snowflake, dbt, and Hightouch working in unison, Lucid’s data models will only continue to improve, enabling the data team to address more complex use cases around analytics and data activation to acquire even more customers.
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