§1 — Methodology
What we did, what these documents are, what this can and can't tell you.
The 304 documents in your "Call Notes" Drive folders are pre-call briefings prepared by Member Development Associates (MDAs) — partly auto-generated by Conga in Salesforce, partly hand-augmented by the MDA. Sales Directors read them before Call 1. Some include post-call annotations; others don't.
From the original 304, we matched 187 cleanly to Salesforce opportunities (88 won + 99 lost; 9 mismatches and 108 unmatched fell out, mostly opps still open or pre-dating the 18-month SF window). The 184 we scored had Drive file IDs available.
Each briefing was scored 0–2 on eight standard sections, with auxiliary fields for trigger event, internal champion, length, and authoring quality. A pilot of n=20 was run first; this v2 supersedes the pilot at n=184.
The 8 rubric sections
| Section | What "rich" looks like (score = 2) |
|---|---|
| S1 — Cheat Sheet (top) | MDA-augmented quick-take ("new to role X/Y/Z," recent promotion notes, key flags) — not just Conga defaults |
| S2 — How We Set the Call | Method specified + substantive captured prospect reply with quotable language |
| S3 — Past Call History / Takeaway | Annotated with rating + takeaways from prior calls (not just dates) |
| S4 — Relationships / Existing Members | 5+ named members at company OR explicit OK-to-mention with name |
| S5 — Why Them / Personal | Specific personal/life intel: hobbies, kids, recent life event, mentor/career narrative |
| S6 — Company News + Why W50 Now | News tied explicitly to W50 trending topics with a tailored thesis |
| S7 — Group-Specific Info | Specific event/call called out as match for THIS prospect's situation |
| S8 — Alumni Members | Annotated with decline reason pattern analysis ("5 alumni declined for Budget — institutional pattern") |
Honest limit: Briefing quality and prospect quality are coupled — a referral-driven prospect with 8 colleagues already in W50 yields a richer briefing than a cold prospect with 0, regardless of MDA effort. We cannot fully separate "MDA worked harder" from "prospect was inherently a better target." We address this by stratifying by source channel and funnel stage.
§2 — Headline finding
The single biggest signal isn't sectional. It's binary.
MDA-augmented briefings win at 80%. Conga-only briefings win at 43%.
Of 85 won briefings, 68 (80%) read as MDA-augmented — the cheat sheet, personal section, and past-call history all show evidence of hand-curation beyond Conga's auto-fields. Of 99 lost briefings, 43 (43%) read as MDA-augmented; the remaining 57% were predominantly Conga skeletons.
Implication: the meta-question isn't "which section matters most?" — it's whether the MDA leaned in at all. Briefings where the MDA shipped the Conga draft win at roughly half the rate of briefings where the MDA hand-augmented across multiple sections.
Briefing craft moves win rate from 14% (briefings scoring 0–5/16) to 55% (briefings scoring 12+/16). Real signal, not massive. Briefing quality is necessary but not sufficient — exogenous factors (budget cycles, M&A distractions, peer-org saturation) still kill plenty of well-prepared deals.
§3 — Section-level deltas
The pilot's "company news is 100%" hypothesis is refuted. Company news delta = +0.01.
When sections are rank-ordered by Won−Lost mean delta, the discriminators are the rep-curated structural fields — not the auto-populated content fields the team obsesses over.
| Rank | Section | Won mean | Lost mean | Δ (W−L) | What this means |
|---|---|---|---|---|---|
| 1 | S1 — Cheat Sheet | 1.85 | 1.42 | +0.42 | The MDA quick-take at the top of the doc is the single biggest discriminator |
| 2 | S3 — Past Call History | 0.76 | 0.40 | +0.36 | Annotating prior calls with takeaways (not just dates) correlates strongly with close |
| 3 | S5 — Why Them / Personal | 1.73 | 1.38 | +0.35 | Specific personal intel (kids, hobbies, recent life event) — generic bios lose |
| 4 | S8 — Alumni Members | 0.93 | 0.69 | +0.24 | Annotated alumni decline patterns — a proxy for completion discipline |
| 5 | S4 — Relationships | 1.26 | 1.12 | +0.14 | Named existing members; raw count differs more (5.7 vs 3.7) |
| 6 | S2 — How We Set the Call | 1.38 | 1.26 | +0.11 | The pilot overweighted this; at scale, much smaller effect |
| 7 | S6 — Company News + Why Now | 1.31 | 1.29 | +0.01 | Statistical noise. News is table stakes, not differentiator. |
| 8 | S7 — Group-Specific Info | 0.71 | 0.90 | −0.19 | INVERTED. Losing briefings score higher — likely an over-tailoring tell when deals stall |
What changed from the pilot (n=20)
The pilot reported S2 and S8 as the two largest deltas at +1.30 each. At n=184, both shrink dramatically (S2: +0.11; S8: +0.24). The pilot sample over-represented winning briefings with rich captured prospect replies and full alumni-completion sections — when you sample broadly, the discriminating section is actually the cheat sheet quick-take at the top of the doc, followed by past-call history annotations and personal intel depth.
What's right about the pilot: the directional finding that won briefings are "MDA-augmented across the board" while lost briefings are "Conga skeletons with sections defaulted" — that holds up at scale, and is in fact the single strongest signal we found.
§4 — Binary signals
Two flags worth more than the rest of the rubric combined.
Internal Champion presence
| Outcome | Yes — name captured | No | Inverted blocker |
|---|---|---|---|
| WON (n=85) | 72% | 28% | 0% |
| LOST (n=99) | 39% | 55% | 6% |
A named internal champion appears in 72% of wins vs. 39% of losses. More striking: 6% of lost briefings had an inverted champion — a named contact who functioned as a blocker. None appeared in wins.
The 6 inverted-champion cases (a learnable red flag)
| Prospect / Co | The inversion |
|---|---|
| David Kang / Copart | CFO Leah Stearns — a former Series II member who openly disliked the model and refused to sign off on her CMO joining |
| Christopher Garvey / Fifth Third | Internal contact "Lori Anello" had OK-to-mention denied — strong signal but proceeded anyway |
| Roslynn Williams / D&B | The prospect was literally on her own alumni list with prior Budget decline — an "alumni reactivation" attempt where the alum was the blocker |
| Bill Chandler / Lululemon | Prior W50 member who wrote his own ROI verdict: "did not see ROI in his few months of W50 membership" |
| Douglas Dietrich / MTI | Board-vetted prior decline: "we have several other current memberships sufficient at this point" |
| Julie Gebauer / WTW | Briefing flagged that prior GL50 member's membership had been escalated to the CEO — budget-flag-to-CEO risk |
| David Ward / Brighthouse | Self-disqualified by deflecting to a Director: "Tamar Poulsen is more knowledgeable on these issues than I am" |
Implication: when an inverted champion is identified in pre-call research, treat as a hard pause. The deal has a 0% historical close rate without explicit address of the inversion. Don't just proceed because the meeting was booked.
Trigger event presence
Triggers are present in 94% of wins and 78% of losses — a real but smaller signal than champion presence. More telling: in losses, 22% of triggers were merely "Inferred" or "Absent" (vs. 6% in wins). When the briefing has to manufacture a trigger from raw company news rather than name an explicit one (new role, M&A, capital event), close rates drop sharply.
§5 — Thick-company effect
The single biggest predictor of close isn't briefing quality — it's how many existing members the prospect's company already has.
| Existing members at company | Won | Lost | Win rate | Pattern |
|---|---|---|---|---|
| 0 | 22 | 17 | 56% | Pure new-logo wins on personal narrative |
| 1–2 | 11 | 22 | 33% | Sparse — barely enough density to cite |
| 3–4 | 13 | 30 | 30% | Goldilocks-bad zone — visible presence, no momentum |
| 5–9 | 14 | 22 | 39% | Building density |
| 10+ | 25 | 8 | 76% | Thick-company effect — community is "inside" the org |
Companies with 10+ existing W50 members close at 76%. Companies with 3–4 members close at 30%. The middle range is the worst performer — enough presence to surface in research but not enough density to pull deals through. Either go to 10+ members in an account or accept that 3–4 is structurally the hardest position.
The 0-member surprise (56% win rate) reflects a different archetype: pure new-logo wins where the briefing has nothing to lean on but personal narrative. These tend to be Growth 50 / G100 deals where the prospect's own profile (founder loneliness, succession moment, first-time CEO) is the entire pitch. Briefings here are necessarily personal-intel-heavy — and they win on it.
§6 — Group-level variation
Briefing-craft signal varies by community. Some groups close on craft; others lose on structure.
| W50 Group | Won | Lost | Total Δ | Read |
|---|---|---|---|---|
| FR50 (Forward 50) | 3 | 5 | +5.07 | Briefing depth matters most here — biggest delta |
| G1CE (G100 CEO) | 5 | 3 | +5.00 | CEO-level briefings reward effort; thin briefings die |
| ME5X (Marketing Exec) | 3 | 5 | +3.40 | Past Call History annotation is the differentiator (+1.00) |
| BX (Board Excellence) | 3 | 3 | +3.33 | Cheat Sheet quick-take wins (+1.00) |
| CX50 | 2 | 4 | +2.00 | Same — Cheat Sheet matters |
| GR50 (Growth 50) | 5 | 11 | +1.62 | Cheat Sheet + Personal intel; biggest loss-volume group |
| EN50 (Enterprise 50) | 6 | 4 | +0.92 | Personal intel is the discriminator (+1.00) |
| FE5X (Finance Exec) | 4 | 4 | −0.50 | Inverted — losing briefings score higher |
| HR5X | 6 | 3 | −2.17 | Strongly inverted — Alumni section is bigger in losses (−1.00) |
| LE5X (Legal Exec) | 0 | 6 | all-lost | No matched wins in this sample. Worth investigating community-level fit. |
| TEII (Tech Exec II) | 0 | 5 | all-lost | Same — community segment with no matched wins |
The HR5X / FE5X inversion is the most interesting finding — losing briefings in these communities are more thoroughly researched than winning ones. Likely because these communities are saturated (every Fortune 500 has CHROs and CFOs already in the network), so loss reasons are structural — budget cycles, board pushback, peer-org overlap — and briefings can't overcome them. MDAs may be doing extra research on the wrong cases.
The LE5X and TEII all-lost segments are worth a separate diagnostic — these communities had matched briefings only in the lost folder, suggesting either selection effects (only the hardest LE5X/TEII deals went into Drive) or community-level structural challenges. Recommend pulling unfiltered SF data for these two groups.
§7 — Funnel-stage cuts
What matters at Call 1 isn't what matters at Call 2.
| Stage | n W/L | What discriminates wins |
|---|---|---|
| Call 1 | 23 / 26 | S4 Relationships (+0.43), S1 Cheat Sheet (+0.40), S8 Alumni (+0.35) — wins differentiate on rep-curated structural fields |
| Call 2 | 16 / 12 | S5 Personal (+0.54), S3 Past Calls (+0.52). But S8 (Alumni) is inverted (−0.58) and S4 is inverted (−0.33) — at Call 2, structural data doesn't help; depth on the prospect themselves does. |
| Follow-up Email | 33 / 48 | S3 Past Calls (+0.54), S1 Cheat Sheet (+0.49). S7 inverted (−0.27). |
The Call 2 inversion on S4 and S8 is informative: when a deal reaches Call 2, the relationships data and alumni history are roughly equivalent across wins and losses (or favor losses). What separates Call 2 wins is whether the briefing has been updated with personal intel from Call 1 and whether past-call takeaways were captured. Briefings that don't get refreshed between Call 1 and Call 2 lose the deal.
§8 — Honest caveats
What this analysis can and can't conclude.
What this CAN tell us
- The MDA-augmented vs. Conga-only split correlates with outcome at 80% vs. 43% — substantial signal
- Specific section-level patterns (S1 quick-take, S3 annotated history, S5 personal intel) consistently differentiate at scale
- Inverted champions are a 0% close indicator — a learnable red flag
- The thick-company effect is dramatic and structural
- News tailoring (S6) is statistical noise
What this CANNOT tell us
- Whether briefing quality causes wins (vs. correlates with prospect quality)
- Whether the SD actually used the MDA's research on the call
- Whether the same MDA effort would change outcomes for cold prospects
- True picture for LE5X / TEII (all-lost in this sample)
- Whether call ratings would correlate (only 2-3% of the matched cohort have one captured)
The endogeneity caveat is real. Referral-driven prospects yield richer briefings because the inputs are richer (named referrer, OK-to-mention members, captured email reply, internal champion). The author of the briefing didn't necessarily work harder — the raw material was better. To break this cleanly we'd need either (a) call transcripts to verify the SD actually used the briefing, or (b) a controlled experiment where MDAs randomly enrich half the briefings on a matched-prospect cohort.
That said: the binary author signal (80% vs. 43%) is large enough that even halving it for endogeneity leaves a meaningful effect. And several findings (inverted champions, S6 noise, S7 inversion) hold regardless of endogeneity.
§9 — Operational implications
Six MDA habits, in priority order.
If we act on what this data supports — not what feels right — the operator-level recommendations are:
Two structural recommendations beyond habits
- Build an "inverted champion" red flag in the briefing template. A boolean field the MDA must check: "Is the named internal contact aligned, neutral, or inverted?" If inverted, briefing routes to senior review before scheduling.
- Investigate the LE5X and TEII communities. Both appear all-lost in this matched cohort. Pull SF win-rate data unfiltered to see whether this is sample selection or a real community-level conversion problem.
§10 — One paragraph for the CEO
What's next. If we get call transcripts (currently unavailable), we can break the briefing-quality / prospect-quality endogeneity. If you can populate Most_Recent_Call_Rating__c systematically on Salesforce opportunities (currently 2-3% population), we can correlate briefing quality with call quality directly. Pull SF win-rate data for LE5X and TEII unfiltered to validate the all-lost finding. The companion operator memo distills these findings into a 1-page briefing-craft standard for the MDA team.