Pipeline Stage Voice Analysis

Analyze deal notes by Pipedrive pipeline stage to find messaging patterns that correlate with wins — and coach reps on what to use or avoid

Scenario

Your sales team writes deal notes at every pipeline stage. Each stage has a different conversational texture. You want to know which messaging patterns correlate with wins at each stage so you can coach reps.

Architecture

Code

Python

import os, requests
from collections import defaultdict
from openai import OpenAI

DOMAIN = os.environ["PIPEDRIVE_DOMAIN"]
PD_TOKEN = os.environ["PIPEDRIVE_API_TOKEN"]
PD_BASE = f"https://{DOMAIN}.pipedrive.com"

def pd_get(path, params=None):
    params = params or {}
    params["api_token"] = PD_TOKEN
    r = requests.get(f"{PD_BASE}{path}", params=params)
    r.raise_for_status()
    return r.json()

# 1. Pull deals for a pipeline, group by stage
deals = pd_get("/api/v2/deals", {"pipeline_id": 1, "limit": 100}).get("data", [])
stage_deals = defaultdict(list)
for d in deals:
    stage_deals[d["stage_id"]].append(d["id"])

# 2. Pull notes per deal, bucket by stage
stage_notes = defaultdict(list)
for stage_id, deal_ids in stage_deals.items():
    for deal_id in deal_ids:
        notes = pd_get("/api/v1/notes", {"deal_id": deal_id, "limit": 50}).get("data", []) or []
        for note in notes:
            if note.get("content"):
                stage_notes[stage_id].append(note["content"][:500])

# 3. Analyze each stage with Mavera Chat
mavera = OpenAI(api_key=os.environ["MAVERA_API_KEY"], base_url="https://app.mavera.io/api/v1")
stage_names = {1: "Prospecting", 2: "Proposal", 3: "Negotiation", 4: "Closed Won"}

for stage_id, notes in stage_notes.items():
    combined = "\n---\n".join(notes[:30])
    response = mavera.responses.create(
        model="mavera-1",
        input=[{
            "role": "user",
            "content": (
                f"You are a senior sales coach. Below are deal notes from the "
                f"'{stage_names.get(stage_id, stage_id)}' stage.\n\n"
                f"Analyze language patterns. What messaging resonates at this stage? "
                f"What should reps use or avoid?\n\n{combined}"
            ),
        }],
    )
    print(f"\n=== {stage_names.get(stage_id, stage_id)} ===")
    print(response.output[0].content[0].text[:600])

Example Output

=== Prospecting ===
Notes that led to advancement use open-ended discovery questions
("What does your current workflow look like?") rather than feature-dumps.
Avoid: "Just checking in" and "circling back" — these correlate with stalls.

=== Negotiation ===
Winning notes reference the prospect's own language ("as you mentioned,
speed-to-deploy is critical") rather than internal jargon. Avoid premature
discounting. Use value-anchoring ("the ROI model we built shows…").

Error Handling

Error	Cause	Fix
401 Unauthorized	Expired API token	Regenerate in Pipedrive settings or refresh OAuth token
429 Too Many Requests	Exceeded 30,000 daily tokens	Batch requests across days; implement backoff
Empty notes list	Deals with no notes	Filter out stages with < 3 notes before analysis