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Analyst Relations Briefing Template

Three documents and three sheets that read what an analyst actually publishes, then route every inaccuracy by whether it is a fact or a judgment.

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Inaccuracy Log

Before Anything Published Has Been Checked

Every note that mentions the company, tagged the day an error is found.

InaccuracyTypeCorrection RequestedLanded

A factual error gets a correction request with a dated source. An opinion-shaped one gets new evidence at the next briefing instead.

Most vendor briefings open with the same company-overview deck no matter who is on the call. The IIAR's own best-practice paper on running one says the majority of analyst briefings are poorly planned and fail to meet their objectives, when an objective was set at all. Most correction requests get sent the same way too, regardless of what kind of claim was actually wrong, a headcount confused with a competitive ranking.

Bellhaven Systems, a fictional identity and access management vendor, gives this pack its worked example: three analysts at three firms, tracked across fourteen months. Nine published inaccuracies got logged and tagged the day each was found. Six were factual, a headcount, a stale price, a feature marked unsupported two years after it shipped, and every one, requested with a dated source attached, landed in that analyst's next relevant publication. Three were opinion-shaped, a tier assignment, a ranking with no benchmark cited, a call that a roadmap was thin.

Those three got requested the same way, with the same promptness, by the same contacts, and none of them landed, which is the split the type of claim predicts rather than any one relationship. Forrester's own policy admits as much. It will correct material errors quickly once it finds evidence of a factual mistake, while a vendor's evaluative pushback on a Wave score will not get the vendor removed from the evaluation at all.

The split that predicts which correction lands

Three analysts and their coverage pattern, nine inaccuracies split by type, and the follow-up turnaround logged for every session.

Analyst Register

Three analysts, three firms. Stance and cadence traced to what each has actually published, not to how the relationship feels.

AnalystFirmCoverage AreaStanceNotes Mentioning UsCadence
Marisol FenwickCorrigan ResearchIdentity and Access MgmtPositive6Semiannual
Devon AchterbergBramwell AdvisoryCloud Security PlatformsNeutral5Semiannual
Yusuf KanervaThird Pillar InsightsEnterprise IdentityPositive3Annual

Yusuf's three published notes each carried an inaccuracy. The register alone would read that as a coincidence, which is why the log next to it exists.

Inaccuracy Log

Nine published errors, tagged factual or opinion the day each was found. Four of nine shown.

InaccuracyTypeLanded
Listed headcount at 40 against an actual 220FactualYes
Positioned us as a Challenger on evidence cited for two LeadersOpinionNo
Stated we do not support SSO, two years after it shippedFactualYes
Ranked a competitor ahead of us with no benchmark citedOpinionNo
TypeLoggedRequestedLandedLanded Rate
Factual666100%
Opinion3300%
All nine99666.7%

Same request, same promptness, same contacts. The split tracks the type of claim, not the relationship it was sent through.

Briefing History

Every session logged with the follow-up turnaround. Seven sessions, three analysts.

DateAnalystPrimary TopicDays to Follow-up
2025-02-03Marisol FenwickDeployment time and TCO2
2025-08-11Devon AchterbergSOC 2 posture and audit history3
2025-09-20Yusuf KanervaIntegration and ecosystem partners1
2026-01-15Yusuf KanervaCustomer base and reference accounts2
2026-02-10Marisol FenwickAI-assisted access review roadmap2
2026-03-05Devon AchterbergPricing tier changes4
2026-04-22Devon AchterbergRoadmap and AI-assisted features3
Average, all seven2.4

Her January note asked directly whether the roadmap item was real. That question set the February 10 briefing's opening slide before it was even scheduled.

What's in the pack

01

Analyst Register

Each analyst's firm, coverage area, stance, and briefing cadence, traced to a specific passage in a specific note rather than to a general impression.

02

Inaccuracy Log

Every published error tagged factual or opinion the day it is found, then tracked for whether a requested correction actually landed.

03

Briefing Deck Narrative

Opens with whatever that analyst's own last few notes keep returning to, never a generic overview, and answers any question their most recent note asked.

04

Q&A Preparation

Every anticipated question traced to a specific line in a past note or briefing, including how to answer one built on an unresolved opinion-type row.

05

Follow-up Note

Sent within two or three days with exactly what was promised attached, following the point-of-view register an executive's thought leadership already sources and dates.

06

Briefing History

Every session logged with the topic covered and the days elapsed before a follow-up went out, so a slow pattern is visible before an analyst names it first.

How to use it

  1. 1

    Send the analysts and whatever they've published

    Hand over the firms that actually cover your category and whatever recent notes exist, even just one or two per analyst.

  2. 2

    Each analyst's real pattern gets read

    River reads four to six past notes per analyst for what they keep returning to, and logs it on the register as their coverage pattern.

  3. 3

    Every published error gets tagged and routed

    A factual claim gets a correction request with a dated source. An opinion-shaped one gets routed to the next briefing as new evidence instead.

  4. 4

    The next briefing opens with what they actually asked

    The deck's first slides answer whatever question that analyst's last note raised, before anything else gets presented.

Frequently asked questions

Is this template free?

Yes, with no signup and no card, and the download is the complete pack rather than a preview of it. Edit with AI installs it as a private workspace and reads whatever your own analysts have actually published instead of this worked example. More packs sit in the template library.

What format are the downloaded files?

Three Word documents and three CSV sheets in one zip. The documents open in Word, Pages, and Google Docs, and the sheets open as real spreadsheets in Excel, Numbers, or Google Sheets, so the register and the log are usable data rather than a table flattened onto a page.

How is this different from a normal analyst briefing template?

The usual template gives a generic deck outline and a note to research the analyst first. This one reads four to six of their actual notes before drafting anything, and splits every published error by type. On the worked example, that split predicted which of nine corrections would land with 100% accuracy.

How do I know if an inaccuracy is factual or opinion-shaped?

Tag it by what it would take to resolve. A number, a date, a shipped feature are checkable against a record and get a correction request. A ranking, a tier, a judgment about direction have no record to check against, so they get routed to the next briefing as evidence instead, never a request.

Doesn't leaving an opinion-type error uncorrected just make things worse?

Usually, yes, which is exactly what this pack's own log shows: three opinion-type requests, sent the same way as six factual ones, and zero landed. That is why the routing rule exists. The point-of-view register behind an executive's thought leadership is one real source for the evidence that goes into the next briefing instead.

What does Edit with AI actually do?

It installs this pack as a private workspace and asks which analysts or firms actually cover your category. It reads whatever notes are public, drafts a register entry and a first briefing narrative from what each one actually returns to, and flags every open inaccuracy by type before anything gets sent.

Find out what your own analysts actually keep returning to

Send the firms that cover your category and whatever they've published. River reads the pattern, drafts the next briefing to it, and routes every inaccuracy by type.

Edit with AI