Customers have increased posting frequency from three to 12 posts per week, and subsequently, enhanced audience engagement as well as outreach. Their marketing teams' productivity has increased by 33% on average, with administration workloads reduced by 50% through AI automation. 

"By generating high-quality personalized text and images, Gemini enables us to build a powerful generative AI marketing tool that supports time-efficient, impactful marketing campaigns across industries," notes Karen Leung, Chief Business Officer, Hotmob. "Our marketer users can swiftly produce the content they need, execute their campaigns, and achieve better results."

For the past 10 years, Hotmob has been using BigQuery as its primary data warehouse and established a centralized data pipeline around it. The company leverages Cloud Storage to store its raw data, which are then transformed into aggregated datasets through Dataflow. The datasets are transferred in BigQuery for advanced analytics, while data visualization is seamlessly realized by connecting BigQuery directly to Looker Studio, which reduces Hotmob's workload on report generation coding development.

Prior to Google Cloud, Hotmob relied on manual coding to generate daily or monthly reports for analysis, resulting in a great number of data pipelines and fragmented data. However, as its data volume and dimensions grew, the Hotmob team needed a more scalable tool to accommodate its expanding analytical needs.

Chow notes that the data pipeline centered around BigQuery has greatly enhanced the productivity of Hotmob's data team, as well as the company's decision-making efficiency and effectiveness. The high scalability and query performance supported by BigQuery allow Hotmob's data scientists to perform dynamic and complex analyses quickly, generating deeper insights for more informed data-driven decision-making. On top of that, with the ability to partition queries, BigQuery further enhances query performance to facilitate ad hoc analyses.