Imagine a dynamic sales department trying to identify the best time to contact a customer. Managers are analyzing data from HubSpot, but something isn't right. There's a lack of context - they don't know if the user visited the website, what ads attracted him or her, and whether the last interaction with customer service was positive. The information is scattered, and thus decisions are less accurate.
The real power of data lies in its synergy. However, when HubSpot data remains isolated from information from Google Analytics, ERP systems or other sources, the opportunity to holistically understand the customer and optimize actions across the entire purchase path is lost. The inability to aggregate and analyze this information in one place results in operational roadblocks - marketing teams can't fully personalize campaigns, and sales operate in a reactive mode instead of a proactive one.
The solution to this problem is to integrate HubSpot with a data warehouse - such as BigQuery. Such a combination eliminates limitations, providing a comprehensive view of the data and enabling advanced analysis. However, before going into the benefits of this integration, it's worth understanding the challenges faced by companies using HubSpot exclusively.
Typical challenges of using HubSpot without integration
Lack of scalability and advanced analytics features
HubSpot does a great job with basic reporting, but when you want to predict future customer activity, or lack thereof, or analyze cross-channel purchase paths, the stairs begin. A modern data warehouse is appropriate for analyzing large sets of data, from a variety of sources.
In BigQuery, analysts can easily explore data, prepare advanced reports and even create predictive models quickly and efficiently.
Synchronization of data in approximately real time
Delays in synchronizing data between systems can lead to incomplete reports and erroneous decisions. For companies that base their operations on precise marketing campaigns or advanced customer segmentation, such delays can mean real losses through suboptimal use of marketing campaign funds.
Third-party tools based on low-code and no-code may initially seem attractive as a solution to a data synchronization problem. Unfortunately, it quickly becomes apparent that they cannot handle the scale of the data or lead to soaring costs. They also often don't offer the full functionality needed to get the most out of your data.
If you are asking yourself the following questions, definitely continue reading this post.
- Is my business not living up to its full potential because I don't have data from HubSpot and other systems (Google Analytics or ERP) in one place?
- Are data delays preventing me from making accurate decisions?
Benefits of integrating HubSpot with BigQuery
Advanced ad targeting
BigQuery is an analytical harvester that fills a major gap in the lack of HubSpot connectivity with other systems in the company. Imagine segments so precise that they hit customer needs with surgical accuracy. These are no longer segments, they are laser-targeted audience groups, ready for your campaigns to finally start delivering spectacular results.
Integration with other data sources
HubSpot in its basic version offers limited integration with other systems. By connecting to BigQuery, organizations can easily collate data from CRM with data from Google Analytics, ERP systems or financial tools. This allows for a more complete understanding of customers and optimization of activities along the entire purchase path.
Access to full data in real time
Thanks to HubSpot's integration with BigQuery, data is available in real time, enabling immediate response to business needs. What's more, organizations not only get access to real-time data, but also data they can trust implicitly. The elimination of uncertainty ensures that decisions are based on reliable information, allowing for instant and accurate responses to market and customer needs.
Organizations can create precise customer segments and run marketing campaigns with even greater accuracy.
Technical aspects of integration
Technology components
Integrating HubSpot with BigQuery requires advanced technologies. In the aforementioned case study at the client company, we applied:
- Serverless GCP components: Cloud Run, for example, was used to containerize applications, and Firestore enabled easy storage of metadata generated by the ELT process. This allowed flexible and efficient processing of large volumes of data while keeping operational costs low.
- ETL process with full data coverage: All of HubSpot's important endpoints for the customer were included, allowing access to full information, including customer, deal, ticket and many other data….
- Real-time monitoring: An automatic monitoring system detected missing data and ensured its completeness before passing it to BigQuery.
Stability and costs
The use of serverless architecture makes the solution scalable, and its maintenance does not generate high costs. In practice, the biggest limitation is the limits of HubSpot's API, not the capabilities of the system itself.
Case study: Hubspot and BigQuery integration optimization for a pharmaceutical client
Initial challenges
Our client, a large brand in the pharmaceutical and dietary supplement industry, already had a HubSpot integration with BigQuery, but it was not properly and efficiently implemented. The system that was used for data transfer could not handle the scale of operations and generated a number of problems.
Key challenges included:
- Lack of data completeness.
- Delays in synchronization.
- Limited scope of endpoints supported.
As a result, managers could not make near real-time decisions and relied on data that was not complete.
Implemented solution
The company decided to optimize the integration process, replacing the legacy solution with a more scalable approach. ETL on GCP was implemented, using tools such as Pub/Sub, BigQuery and Cloud Run Functions, and App Engine to create an interface for configuring and monitoring the system.
The new architecture is designed to not only transfer data, but also to ensure data consistency and integrity at every stage of the process. Batch and incremental processes have made it possible to process large volumes of data quickly, ensuring near real-time availability.
Results
- Immediate access to complete HubSpot data.
- Improved operational efficiency, resulting in decreased churn and increased customer satisfaction.
- Cost optimization by replacing the Hevo system with an in-house solution.
Summary
HubSpot's integration with BigQuery opens up new analytical and operational possibilities, allowing better use of data. Organizations can increase their efficiency, improve process stability and reduce operational costs.
If you feel like you're not using HubSpot to its full potential, it's worth talking to our experts. We can help you design and implement the optimal integration to make your data work for your business, rather than be a barrier to its growth. Contact the experts to learn how such an implementation can help you achieve your business goals, and stay ahead of the competition.
