Pipedrive

Integrate Mavera with Pipedrive — pipeline voice analysis, activity-based persona scoring, lost deal focus groups, and org-level account research

Overview

These jobs show how to pull data from Pipedrive (Deals, Notes, Activities, Organizations) → analyze with Mavera (Chat, Focus Group, Mave Agent) → get persona-validated insights for sales coaching, pipeline optimization, and account intelligence.

Pipedrive API v2 is the primary API used below. Some endpoints (Notes) still use v1. Authenticate with an OAuth 2.0 token or an API token query parameter.

Detail	Value
Base URL	https://{companydomain}.pipedrive.com/api/v2/
Auth	OAuth 2.0 Bearer token or ?api_token= query param
Rate limits	30,000 base tokens/day (each request costs 1–10 tokens)
Mavera surfaces	Chat, Focus Group, Mave Agent

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Prerequisites

1. Pipedrive credentials

   Generate an API token from Settings → Personal preferences → API, or set up an OAuth 2.0 app.

2. Mavera API key

   Grab your key from app.mavera.io/settings/api.

3. Environment variables

   export PIPEDRIVE_API_TOKEN="pd_tok_..."
   export PIPEDRIVE_DOMAIN="yourcompany"
   export MAVERA_API_KEY="mvr_..."
   
4. Install dependencies

   Python

   pip install requests openai
   

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Jobs

Pipeline Stage Voice Analysis

Analyze deal notes by pipeline stage to find messaging patterns that correlate with wins

Activity-Based Persona Scoring

Map activity patterns (calls, emails, meetings) to buyer personas and discover touchpoint thresholds

Lost Deal Focus Group

Create persona archetypes from lost-deal patterns and run Focus Groups to surface qualitative reasoning

Org-Level Account Research

Use Mave Agent to research organizations and write intelligence briefs back to Pipedrive

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Production Tips

Paginate large datasets

Pipedrive v2 endpoints use cursor pagination. Read additional_data.next_cursor from each response:

cursor = None
all_deals = []
while True:
    params = {"limit": 100}
    if cursor:
        params["cursor"] = cursor
    resp = pd_get("/api/v2/deals", params)
    all_deals.extend(resp.get("data", []) or [])
    cursor = resp.get("additional_data", {}).get("next_cursor")
    if not cursor:
        break

Webhook-driven automation

Use Pipedrive webhooks (Settings → Webhooks) to trigger jobs when deals change stage, are lost, or organizations update. This reduces daily token consumption.

Normalize lost_reason before clustering

Freetext reasons create sparse clusters. Map synonyms before Focus Group:

REASON_MAP = {
    "too expensive": "Pricing", "price": "Pricing", "budget": "Pricing",
    "competitor": "Competitor", "went with": "Competitor",
    "timing": "Timing", "not now": "Timing", "next quarter": "Timing",
}
def normalize(raw):
    for kw, cat in REASON_MAP.items():
        if kw in raw.lower().strip():
            return cat
    return "Other"

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Credits

Mavera surface	Credits/call	Typical usage
Chat	~1–5	Per-stage voice analysis
Focus Group	~10–30	Activity scoring, lost deal analysis
Mave Agent	~5–15	Org research

See Credits for details.

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