marketing_ops · media · workflow
CLICKFORCE reduces advertising industry analysis from weeks to one hour with Amazon Bedrock Agents
CLICKFORCE's industry analysis process took two to six weeks due to labor-intensive manual stages and disconnected tools, while LLMs produced generic rather than actionable industry-specific insights and lacked integration with internal datasets.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User query via chatbot
End-users interact with a chatbot interface running on Amazon ECS, developed with Streamlit and fronted by an Application Load Balancer.
Tools used
Amazon BedrockAmazon Bedrock AgentsAmazon SageMaker AIAmazon OpenSearchAWS GlueAmazon ECSStreamlitAWS LambdaAmazon Bedrock Knowledge BasesAmazon S3MLflow
Outcome
Industry analysis time dropped from two to six weeks to under one hour, and operational costs fell by 47 percent, while brand owners, agencies, analysts, and media partners can now independently generate insights without waiting for centralized analyst teams.
What failed first
Generic LLM outputs lacked actionable, industry-specific intelligence, and foundation models used for Text-to-SQL translation were inflexible and often inaccurate, prompting CLICKFORCE to build a fine-tuned, grounded solution.
Results
Time savedunder one hour (previously two to six weeks)
Cost replaced47 percent
Grounding & classification
Source type: platform led case
33 fields verified against source quotes.
agentic workflowconversational aidata extractionragsummarizationknowledge basefailure mode describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedmediacost reductionemployee productivitytime savedplatform led casemarketing opsagentic task executionrag answering