The enterprise marketing team at Zapier has deployed ChatGPT Work to automate quality assurance and campaign production, aiming to lower lead drop-offs and speed execution, Angela Ferrante, Head of Enterprise Marketing, said.
Automating funnel QA/QC
Zapier identified a high volume of strong inbound leads alongside a significant drop-off rate. Determining where leads were lost required a labor-intensive QA/QC process that previously limited the team’s capacity.
Ferrante said the team built an automated system with ChatGPT Work that performs QA/QC on thousands of leads every month. She estimated that manually reviewing a single dropped lead took about 35 to 45 minutes; the automated workflow now identifies lead problems, patches issues, and quantifies impact.
According to Ferrante, the project produces a seven-figure value in pipeline that the marketing team hands off to sales each month. The system also generates an executive dashboard that highlights recurring issues and shows weekly trends.
Campaign production and reporting
Beyond lead triage, Ferrante said ChatGPT Work can build campaign assets and integrate with the systems the team uses to create and deploy campaigns. “Within minutes, we have actual campaign assets ready to review and push out,” she stated.
The automated processes have also been applied to reporting. Ferrante reported that the team has dialed in reporting workflows so staff spend more time on strategic work and less time analyzing results, allowing demand generation and other teams to move faster from ideation to execution.
Next steps and scope
Ferrante described further ambitions to expand automation beyond prompt-driven tasks into always-on loops. The long-term goal is a “shared brain” that draws context from meetings, call recordings, customers, and market insights so routine work can run autonomously while humans focus on selection and quality.
The team continues to operate the system within current workflows and to supply sales with the pipeline and dashboards produced by these automated processes.
Original source: OpenAI News