Gorgias Improves Account Insight and ROI Attribution with Hull

Results Summary

• Improve ROI attribution and intelligently measure channel performance by cleaning up marketing lead source data
• Prioritize visibility and transparency throughout the company with data-driven dashboards and account-level insight
• Simplify reporting and analysis through data standardization

Gorgias offers a helpdesk solution for ecommerce stores that’s designed to help merchants use support as a lever to increase sales.

Improving Account-Level Insight for Marketing

Gorgias offers a multi-channel helpdesk solution for ecommerce stores that allows merchants to manage all their support from one place by providing a unified view of customers. Ultimately, the company’s goal is to help merchants increase sales by providing outstanding support.

Data plays a significant role in the culture at Gorgias. The company makes decisions based solely on data, so if a team wants to submit a new idea to implement, the hypotheses need to be backed by data to take on the project. However, this data-driven approach was starting to prove difficult for the Gorgias growth teams given the number of technologies in their stack.

While Gorgias had a best-in-class marketing stack comprised of tools like Segment, HubSpot, Zapier and Periscope, the number of solutions made it difficult for the team to compile an account-level view of their data in order to better understand channel performance and account penetration.

In an effort to gain that account-level view and improve ROI attribution and confidence in marketing data as a result, Gorgias set out to find a new solution to bring together its existing martech stack.

Searching for the Right Technology

Axelle Heems, who leads Growth Operations at Gorgias, took on the challenge of finding a solution to better connect data from across the martech stack and provide the team with an account-level view.

As one of the few tools that provide both user-level and account-level data aggregation, Hull quickly made it to the shortlist.

Trying out Hull proved successful, as it provided Axelle with a lot of features, which ultimately enabled her to connect all of the data points to provide the growth team with the insights into their prospect accounts. Gorgias was particularly drawn to Hull for two features:

• The HubSpot Connector, which gives the growth team control over what data gets sent to HubSpot so that only the cleanest data goes through. Reciprocally, it enables them to choose which properties to import from HubSpot into Hull.
• The Data Processor, which allows Gorgias to maintain data cleanliness. Gorgias is able to easily standardize and compute new traits based on existing data, ultimately simplifying database queries for analysis.

Improving Confidence in Marketing Data and ROI Attribution

Since implementing Hull, Gorgias has been able to view complex and aggregated prospect data at the account level. In turn, this view has increased confidence in data, simplified reporting for more actionable insights and improved ROI attribution.

Now, the growth team uses Hull to automate the source attribution on accounts directly within the Processor and send the computed data to HubSpot through Hull’s HubSpot Connector. This automation improves data standardization by eliminating errors that come with manual data entry. In turn, this approach results in better data management and greater trust in the data across the organization.

The account-level view has also provided valuable, actionable insights for Gorgias. Many B2B SaaS companies offer a self-service trial for smaller companies and a more involved demo for larger enterprises. But having access to aggregated data at the account level helped Gorgias analyze the impact of giving demos to new trials for smaller companies, which led them to find that 73% of those deals that get a demo close. This finding led them to focus on booking demos for smaller and larger companies alike.

Finally, the automation made possible by Hull has also helped keep data clean by standardizing values that had been computed in the stack since the early stages of the company (which means that sometimes the data had gotten a little messy due to improvements over time). With this standardization in place, the marketing team has more accurate data for lead source reporting and ROI attribution, which allows them to make smarter investments.

For instance, Gorgias can now confidently determine which channels convert leads best (and which ones don’t work as well). Critically, that insight has led the team to divert money from non-converting to converting channels to improve performance. Axelle shares the Gorgias team was fully confident in this move because having clean historical performance data through Hull has enabled them to accurately predict and track expected monthly ARR per channel.