A Content Marketing Agency in Delhi

01.The Challenge

Strategists were manually researching keywords, competitor content, and structure for every brief, which didn't scale as client volume grew ( even with traditional LLM chatbots ). For Content Marketing Agency's marketing team specifically, it wasn't a new problem — it had just never been anyone's clear responsibility to fix, so it kept getting worked around instead of solved.

02.The Solution

Built a tool that pulls competitor and keyword data automatically and drafts a structured brief for a strategist to review and refine ( via data scaping). The approach leaned on Content Marketing Agency's existing data rather than requiring a separate data-collection effort, which kept the timeline realistic.

03.How It Went

1. 1Started with a short discovery phase to map out exactly where Content Marketing Agency was losing time, and what a realistic win would look like within 5 weeks ( result took around 3 months to show clearly).
2. 2Development for Content Marketing Agency centered on Python, LangChain, with an early working version ready well before the full feature set was finished.
3. 3Rolled out to a smaller pilot group within Content Marketing Agency first, then expanded once the early numbers held up under real usage.
4. 4Left Content Marketing Agency with a working system plus a short list of natural next steps, in case they wanted to extend it later.

04.Results

• Cut brief creation time from 90 minutes to 15 per article
• Freed up strategists to focus on higher-level content strategy and other marketing stufs.
• Adopted across the agency's entire content team
• Handed off to Content Marketing Agency with clear documentation so their internal team could maintain and extend it going forward