Tutorial

How to Build a Marketing Research Agent in 2026

Stitch-free marketing research agent: SERP, Reddit, YouTube under one credit pool. Drops into n8n or Claude Code.

An r/MarketingandAI thread complained that AI marketing agents 'reorganize the same limitations.' The fix is to separate the data layer from the orchestration layer. This tutorial wires Scavio as a marketing research agent's data layer.

Prerequisites

  • Python 3.10+
  • Scavio API key
  • Anthropic or OpenAI key

Walkthrough

Step 1: Define competitor + topic set

5-10 competitors, 5-15 topics.

Python
COMPETITORS = ['firecrawl', 'tavily', 'serper']
TOPICS = ['mcp server', 'ai agent search', 'web scraping 2026']

Step 2: Daily competitor digest

SERP + Reddit + YouTube per competitor.

Python
import requests, os
API_KEY = os.environ['SCAVIO_API_KEY']
H = {'x-api-key': API_KEY}

def competitor_digest(name):
    return {
        'serp': requests.post('https://api.scavio.dev/api/v1/search', headers=H, json={'query': name}).json(),
        'reddit': requests.post('https://api.scavio.dev/api/v1/reddit/search', headers=H, json={'query': name}).json(),
        'youtube': requests.post('https://api.scavio.dev/api/v1/youtube/search', headers=H, json={'query': name}).json(),
    }

Step 3: Topic-level visibility tracking

Where does each competitor show up?

Python
def topic_share(topic):
    r = requests.post('https://api.scavio.dev/api/v1/search', headers=H, json={'query': topic, 'include_ai_overview': True}).json()
    return r

Step 4: LLM brief composition

Claude turns raw data into 200-word brief.

Python
import anthropic
client = anthropic.Anthropic()

def brief(competitor, data):
    msg = client.messages.create(model='claude-sonnet-4-6', max_tokens=400,
        messages=[{'role':'user','content':f'200-word competitor brief on {competitor}: {str(data)[:6000]}'}])
    return msg.content[0].text

Step 5: Schedule weekly

n8n cron or simple crontab.

Bash
# 0 8 * * 1 /usr/bin/python /path/to/marketing.py

Python Example

Python
# Weekly run: 10 competitors × 3 surfaces + 15 topics = 45 credits = $0.19. Negligible at the Project tier.

JavaScript Example

JavaScript
// TS version uses the Anthropic SDK.

Expected Output

JSON
Weekly digest with per-competitor 200-word brief plus topic-level visibility share. Drops into Slack or email.

Related Tutorials

Frequently Asked Questions

Most developers complete this tutorial in 15 to 30 minutes. You will need a Scavio API key (free tier works) and a working Python or JavaScript environment.

Python 3.10+. Scavio API key. Anthropic or OpenAI key. A Scavio API key gives you 500 free credits per month.

Yes. The free tier includes 500 credits per month, which is more than enough to complete this tutorial and prototype a working solution.

Scavio has a native LangChain package (langchain-scavio), an MCP server, and a plain REST API that works with any HTTP client. This tutorial uses the raw REST API, but you can adapt to your framework of choice.

Start Building

Stitch-free marketing research agent: SERP, Reddit, YouTube under one credit pool. Drops into n8n or Claude Code.