Leveraging first party data is a must for marketers — it’s the key to orchestrating tailored customer journeys. And with third party cookies disappearing, the question of whether to leverage first party data is not if, but how.
Two customer platforms have emerged in this first party data solution space: the traditional marketing cloud and the packaged customer data platform (CDP).
This guide will explain the ecosystem of traditional marketing clouds and CDPs and why the data gap is unsustainable as you scale. We’ll introduce you to GrowthLoop’s composable CDP on BigQuery, unpack the features of the self-serve platform, and share success stories from customers like Mercari and the Boston Red Sox.
The customer platform ecosystem
As first party data and digital channels have exploded, marketers have relied on two types of solutions to build audiences and launch campaigns: the traditional marketing cloud and the packaged CDP.
What is a marketing cloud?
Marketing clouds were one of the earlier players in the customer platform space. Marketing and business teams use the suite of tools in a marketing cloud to manage campaigns and nurture customer relationships.
These systems typically offer tools for content creation, social media sharing, advertising, and more. They operate on a data set from a source like the data warehouse or, in some cases, other inputs like web data. Two of the more popular marketing clouds are Adobe Experience Cloud and Salesforce Marketing Cloud.
What is a packaged CDP?
In the mid-2010s, CDPs joined the market to address the explosion of social media channels. CDPs compile customer interaction data from websites and mobile applications to rebuild a partial customer profile. Marketing teams access this profile to activate campaigns to various end destinations — ads, emails, SMS, and more.
Like marketing clouds, packaged CDPs require a copy or transfer of data. That means it doesn’t capture data from web or app sources, like your CRM, loyalty program, or in-store transactional data.
The list of CDPs on the market is extensive. The CDP institute reported in July 2022 that over 160 defined vendors were in the space. Some of the more well-known CDPs are Segment, Tealium, and mParticle.
The data gap
Marketing clouds and CDPs can be powerful tools for nurturing customer relationships, but they share a fundamental weakness. Because they came about before the full maturation of the data cloud, they require an additional copy of customer data from your data cloud — usually hosted on a third-party platform. Marketing teams leverage the data only once the data is in the marketing cloud or CDP system.
Challenges of the data gap
As data sources and volume grow, the data and engineering teams must devote increasing time and resources to bridge the gap between the data cloud and the customer platform. Marketing teams who lack dedicated engineering resources struggle to maintain their CDPs.
When marketers can’t self-serve their data, it creates several challenges:
- Moving data piecemeal from the data cloud to the customer platform means marketers can’t work from a single source truth.
- Because marketing must ask the data team to generate customer lists to input into the CDP, segmenting audiences and launching a campaign can take weeks, if not months.
- Because of the data gap, marketing must focus more on troubleshooting than experimentation, iteration, and growth.
So, what if we could close the gap between the data cloud and the customer platform, allowing marketers to focus on marketing again?
Introducing the GrowthLoop composable CDP on BigQuery
This closed-loop solution ensures your company maintains the integrity of your single source of truth around customer data. Its design allows your marketing team to build a sustained growth engine efficiently and effectively from your company's data.
Because GrowthLoop sits on top of your data cloud, it won’t take months to integrate with your data and engineering teams. If you already have your data in BigQuery, you can set up the GrowthLoop composable CDP in five minutes.
How the composable CDP on BigQuery works
The GrowthLoop no-code interface allows marketers to easily create and segment audiences inside BigQuery for sales and marketing campaigns.
You then activate those audiences to end destinations, and all audience data is available in the data warehouse for measurement and analysis.
What used to take months of set-up and hours of back-and-forth with the engineering team can be done in minutes, with no SQL required.
Building audiences with GrowthLoop and BigQuery
With GrowthLoop, analytics and activation live in one place, making audience creation a five-minute exercise. GrowthLoop’s Audience Builder provides marketing teams with a visual segmentation interface straight from the data cloud.
The platform also leverages AI and predictive models. For example, the Boston Red Sox used GrowthLoop’s platform to deploy a fan avidity score model trained on BigQuery data to target outreach more efficiently.
Whether you’re focusing on acquisition, churn winback, or cross-selling, GrowthLoop’s cross-channel journey builder allows you to orchestrate targeted journeys at each phase of the customer lifecycle with mass channel coverage.
Measurement and experimentation
Since GrowthLoop writes all audience data back to BigQuery, analytics teams can conduct performance analysis on metrics from revenue to retention. You can measure the business impact of your experiments on revenue or any metric defined in your data warehouse.
How Mercari uses the GrowthLoop composable CDP on BigQuery
In 2018, the peer-to-peer marketplace Mercari engaged GrowthLoop to transform their marketing technology and combat churn. Despite the team’s robust data science capabilities and investments in a data warehouse in BigQuery, launching a single campaign took up to three months.
GrowthLoop's audience platform connected directly to Mercari’s predictive model's results in BigQuery, allowing the marketing team to launch and sync audiences across all of Mercari's major marketing channels, including Braze, Google Ads, and Facebook. In addition to self-serve audience-building and activation, Mercari’s marketers had access to view incremental lift on any key metric — right within the GrowthLoop platform.
Mercari was also able to fight churn thanks to their ability to build customer lists that leveraged their predictive models — without continuous support from data engineers and business intelligence analysts.
“GrowthLoop brings a very fundamental way of thinking about problems, including experimentation...The ability to organize experiments and results was key. The number of variables is too high for most people without good organization.” –Masumi Nakamura, VP of Engineering at Mercari
How the Boston Red Sox use the GrowthLoop composable CDP on BigQuery
In 2020, the Boston Red Sox were determined to bounce back after COVID and kickstart a new strategy for fan acquisition using data analytics. The Red Sox engaged GrowthLoop to help build a robust fan acquisition and engagement capability for the business.
Using predictive models on the GrowthLoop platform, the Red Sox sales team took machine learning models off the shelf and put them into action to intelligently hone in on audiences most likely to purchase through targeted outreach.
With GrowthLoop's audience data written back to BigQuery, the analytics team could measure results centrally for their sales and marketing efforts and deliver more effective and engaging communications with their fans. By harnessing the power of data analytics, the Red Sox could make informed decisions about their marketing strategies and better engage with their fans.
“We went from spending all of our time answering data requests to a self-service model with scalable data democratization via GrowthLoop, which allows our team to be more proactive vs reactive.” –Jon Hay, Vice President Data, Intelligence & Analytics, Boston Red Sox.
Where do I start?
GrowthLoop’s self-serve platform allows you to leverage your own data architecture to reach your customers. With its self-serve solution, your marketing team can stop troubleshooting and start focusing on what matters: experimentation, iteration, and driving growth.
If you’re curious about our solution and wondering where to start, book a collaborative workshop assessment with our team. Together, we can assess your data maturity and evaluate your specific business needs. You will come away with an action plan for your specific use cases — at no cost to you.