general account-research-deep-dive

account-research-deep-dive

This skill should be used when the user asks to "research an account", "do a deep dive on a company", "build an account dossier", "prep for an ABM campaign", "research a target account", "analyze a prospect company", "do account intelligence", "build an account brief", "prep account research for outbound", or any variation of conducting deep research on a specific B2B account for sales or ABM purposes.
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Account Research Deep Dive

Deep account research builds a complete picture of a company before outreach begins. The output is a one-page account brief that any rep, AE, or ABM marketer can pick up and act on immediately.

Time budget: 45-90 minutes for a Tier 1 ABM account. 15-30 minutes for a Tier 2 account. If research takes longer than 90 minutes, the account is either too opaque or you're going too deep. Cap it and move on.

The Account Brief

Every deep dive produces one document with these sections:

  1. Company snapshot
  2. Business model and revenue
  3. Strategic priorities
  4. Tech stack
  5. Buying committee map
  6. Problem hypothesis
  7. Signal inventory
  8. Competitive landscape
  9. Recommended angle

One page. Not a slide deck. Not a Notion database with 40 fields. A single document a rep can read in 3 minutes before a call.


Section 1: Company Snapshot

Capture in under 60 seconds using LinkedIn, Crunchbase, and the company website.

Field Source Example
Company name - Acme Corp
Founded Crunchbase 2019
HQ LinkedIn San Francisco, CA
Employee count LinkedIn 180
Funding Crunchbase Series B, $45M (raised Oct 2025)
ARR estimate Hiring velocity + funding math $8-15M (estimate)
Industry / vertical Website Developer tools, API infrastructure
Target customer Website Mid-market engineering teams

ARR estimation rules

ARR is rarely public for private companies. Estimate using these proxies:

  • Headcount method: SaaS companies typically generate $150K-250K ARR per employee at Series A-B stage. 180 employees = roughly $27M-45M, but adjust down for heavily funded, pre-revenue-scale companies
  • Funding math: Typical Series B SaaS raises at 10-15x ARR multiple. $45M raise at 12x = ~$3.5M ARR at time of raise. Add 12-18 months of growth since raise
  • Job posting velocity: High hiring velocity (10+ open roles) relative to headcount signals growth phase. Low velocity signals efficiency mode or plateau
  • Customer evidence: Count logos on website, case studies, G2 reviews. 50+ G2 reviews usually means $5M+ ARR

Never present an ARR estimate as fact. Always label it as an estimate and note the method.


Section 2: Business Model and Revenue

Understand how they make money. This shapes the problem hypothesis and the angle.

Questions to answer:

  • Who is their buyer? (Enterprise, mid-market, SMB, developer, consumer)
  • What do they sell? (Platform, point solution, API, marketplace)
  • How do they charge? (Seat-based, usage-based, platform fee, hybrid)
  • What's their primary go-to-market motion? (Sales-led, product-led, hybrid)
  • What's their growth stage? (Finding PMF, scaling, expanding, optimizing)

Sources:

  • Company website (pricing page, product page, about page)
  • G2/TrustRadius reviews (reveal buyer type and use case)
  • Job postings (sales-heavy = sales-led, growth/product-heavy = PLG)
  • Podcast appearances by founders/execs (often reveal GTM strategy)
  • Blog posts or press releases about customer milestones

Business model rules

  • If the pricing page is hidden, they're enterprise sales-led. The absence of pricing is information
  • If they have a free tier or self-serve signup, there's a PLG motion. Even enterprise companies with PLG have different buying dynamics
  • If their job postings are heavy on SDR/AE roles, outbound is a primary motion. If heavy on marketing/growth, inbound or PLG dominates
  • Never assume business model from the product category alone. Two companies in the same category can have completely different GTM motions

Section 3: Strategic Priorities

What the company is focused on right now. This determines whether your product is relevant to their current agenda or a distraction.

Sources (in order of reliability):

Source Reliability What it reveals
Earnings calls / investor updates High (for public companies) Stated priorities, metrics they're tracking, challenges acknowledged
CEO/founder interviews and podcasts High Vision, current challenges, what keeps them up at night
Recent blog posts from leadership Medium-high Strategic themes, product direction
Job postings Medium-high What they're building, expanding, or fixing (infer from roles being hired)
Press releases Medium Partnerships, launches, milestones (often aspirational)
LinkedIn posts from execs Medium Real-time thinking, reactions to market events
Glassdoor reviews Low-medium Internal culture, operational challenges (noisy, use with caution)

How to extract priorities from job postings

Job postings are the most underrated research source. They reveal what the company is building before it's announced.

  • First RevOps hire: Rebuilding the sales infrastructure. Data, tooling, process. Prime target for ops tools
  • VP of Growth or Head of PLG: Shifting GTM motion. May be evaluating new tooling for the PLG layer
  • Multiple SDR hires: Scaling outbound. Need sequencing, enrichment, deliverability tools
  • Data engineering roles: Building internal data infrastructure. May be evaluating integration or data tools
  • Security/compliance roles: Preparing for enterprise buyers or a compliance milestone. Security tools, SOC 2 consultants
  • International roles (EMEA, APAC): Geographic expansion. Need localization, legal, payment, or GTM support for new regions

Priority rules

  • Identify the top 2-3 priorities only. More than 3 dilutes the brief. If everything is a priority, nothing is
  • Label each priority as "stated" (from public sources) or "inferred" (from job postings, hiring patterns). Stated priorities are safer to reference in outreach. Inferred priorities are hypotheses to validate on a call
  • Check recency. A blog post from 18 months ago about "scaling the team" may no longer reflect current priorities. Prioritize sources from the last 6 months

Section 4: Tech Stack

What tools they use. This shapes integration relevance, competitive positioning, and the technical angle.

Sources:

Source What it reveals Reliability
Job postings Tools mentioned in requirements ("experience with Salesforce, dbt, Snowflake") High
BuiltWith / Wappalyzer Website technologies (analytics, CMS, chat, tracking pixels) High for web stack, limited for internal tools
G2 reviews they've written Tools they use and evaluate Medium-high
LinkedIn profiles of their team Tools listed in skills, experience sections Medium
GitHub (if open-source presence) Languages, frameworks, CI/CD tools High for dev teams
Case studies / blog posts Tools mentioned in context of their workflow Medium
Integration directories Check if they're listed as a customer on vendor integration pages Low-medium

Tech stack research rules

  • Focus on the stack relevant to your product's integration layer. If you sell a CRM tool, map their CRM, sequencing, enrichment, and analytics stack. Don't catalog their design tools
  • Note the incumbent competitor. If they're using a tool you replace, that's the real competitive angle. Research when they likely adopted it (G2 review date, job posting mention start date) to estimate contract timing
  • Flag migration signals. "We migrated from X to Y" in a blog post or "experience with X, transitioning to Y" in a job posting signals active stack changes. Active migration = open buying window
  • Never assume stack from company stage. Not every Series B company uses HubSpot. Not every enterprise uses Salesforce. Verify

Section 5: Buying Committee Map

Identify the people who influence, evaluate, and approve the purchase.

Role Title patterns Where to find
Champion Manager/Director level who owns the daily problem LinkedIn (title search at company), conference speaker lists
Economic buyer VP/C-level who controls budget for this category LinkedIn, press mentions, podcast appearances
Technical evaluator Engineering, IT, or Ops role who validates integration LinkedIn, GitHub contributors, job postings mentioning the role
Influencer Adjacent leader affected by the decision LinkedIn org mapping, company about page
Blocker Incumbent tool champion or internal skeptic Often invisible until later. Note the risk, identify if possible

Committee mapping rules

  • Map at least 3 contacts across 2+ functions before any outreach
  • For each contact, capture: name, title, LinkedIn URL, likely stance (champion/neutral/blocker), and one personalization token (recent post, talk, hire date, mutual connection)
  • Check tenure. Contacts in role < 6 months are more likely to buy (new broom sweeps clean). Contacts in role > 3 years are more likely to be incumbents who resist change
  • Note reporting relationships. If the champion reports to the economic buyer, that's a clean escalation path. If they're in different orgs, you'll need multi-threading strategy
  • Update the map before every outreach touch. People change roles. New hires appear. A stale map produces embarrassing emails ("Hi [person who left 2 months ago]")

Section 6: Problem Hypothesis

One paragraph stating the specific problem you believe this account has, why it's acute right now, and what they're likely doing about it today.

Template:

[Company] is likely experiencing [specific problem] because [evidence: signal, stage, hiring pattern, tech stack gap]. They're currently [status quo: doing nothing, using incumbent tool, building in-house]. This is costing them [estimated impact: time, revenue, headcount, opportunity cost]. Our [product/approach] addresses this by [specific mechanism], which is relevant now because [why-now trigger].

Problem hypothesis rules

  • The hypothesis must be falsifiable. If you can't imagine a scenario where the prospect says "that's not a problem for us," the hypothesis is too vague
  • Ground it in evidence from the prior sections. "I think they have a pipeline problem" is not a hypothesis. "Their 6 open SDR roles and no RevOps hire suggests they're scaling outbound without ops infrastructure, which typically creates attribution and deliverability issues within 6 months" is a hypothesis
  • One hypothesis per account. If you have two strong hypotheses, pick the one with more evidence and save the other as a fallback angle for Email 2
  • The hypothesis drives everything: email angle, content choice, event framing, ad messaging. If the hypothesis is wrong, all of it misfires. Spend the time to get this right

Section 7: Signal Inventory

List every signal you found, scored by strength and recency.

Signal Type Date Strength Source
Raised $45M Series B Funding Oct 2025 Tier 1 Crunchbase
Posted VP RevOps role Hiring Mar 2026 Tier 1 LinkedIn
CEO spoke at SaaStr about scaling outbound Conference Feb 2026 Tier 2 YouTube
3 SDR roles open simultaneously Hiring Apr 2026 Tier 2 LinkedIn
Blog post on "building our sales engine" Content Jan 2026 Tier 3 Company blog

Signal rules

  • Minimum 1 Tier 1 or Tier 2 signal required to proceed with ABM. If the signal inventory is empty, the account goes to nurture, not ABM
  • Order signals by recency. The most recent signal anchors Email 1's opener
  • Note signal combinations. Funding + hiring signals together are stronger than either alone. Document these clusters
  • Check signal freshness at campaign launch. A signal found during research in March may be stale by May. Re-verify before the first touch

Section 8: Competitive Landscape

Who else is selling to this account, and where they stand.

Capture:

  • Incumbent tool: What they use today for the problem you solve. Source: tech stack research, job postings, G2 reviews
  • Incumbent status: Happy, neutral, or dissatisfied. Source: G2 review sentiment, LinkedIn posts, complaints in communities
  • Contract timing (if knowable): When the renewal likely is. Source: G2 review dates (reviews often post near renewal decisions), vendor announcement dates
  • Other vendors likely pitching: Who else is probably prospecting this account based on the same signals. This shapes urgency and positioning

Competitive rules

  • If the incumbent is deeply entrenched and the contact is a champion of that tool, flag it as a blocker risk. Your angle needs to be "complement" not "replace" in that scenario
  • If there's no incumbent (they're doing nothing or using spreadsheets), the competitor is inertia. Your angle needs to make the status quo feel expensive
  • If multiple vendors are likely pitching based on the same signal (e.g., every sales tool vendor targets fresh Series B companies), speed and differentiation matter more than sequence design. Get there first with a sharper angle

Section 9: Recommended Angle

Based on all prior sections, one clear recommendation for how to approach this account.

Template:

Lead with: [The strongest signal] → [The problem hypothesis, one sentence] Proof point: [Specific peer story or data point from a similar company] Ask: [Specific, small ask tailored to their role and stage] Channel priority: [Which channels to emphasize based on accessibility and committee map] Risk: [Primary risk: blocker, competitor, timing, internal priority conflict]

This section is the brief that the SDR, AE, or ABM marketer actually uses. Everything above it is the evidence. This is the action.


Research Time Budgets

Account tier Total time Snapshot + business model Priorities + tech stack Committee + signals Hypothesis + angle
Tier 1 (1-to-1 ABM) 45-90 min 10-15 min 15-20 min 15-25 min 10-15 min
Tier 2 (1-to-few ABM) 15-30 min 5 min 5-10 min 5-10 min 5 min
Tier 3 (targeted outbound) 5-10 min 2 min 3 min 3 min 2 min

Time budget rules

  • Set a timer. Research expands to fill available time. The diminishing returns on research past 90 minutes are severe
  • If you can't find enough information in the time budget, the account may not be ready for ABM. Flag it and move on
  • For Tier 2 accounts, use the cluster-level research from the 1-to-few playbook for sections 2-4 and only do per-account work on sections 5-7
  • Never skip the problem hypothesis to save time. A 5-minute hypothesis based on thin research is more valuable than a 60-minute research doc with no thesis

Anti-Pattern Check

  • Research without a hypothesis. Collecting facts is not research. The output is a specific, actionable thesis about what they need and why now. If the brief doesn't end with "Lead with X because Y," it's incomplete
  • Spending 3 hours on a single account. Diminishing returns. Cap at 90 minutes for Tier 1, hard stop. The remaining unknowns get answered on the discovery call
  • Researching without checking CRM first. If someone at your company already talked to this account, that context is worth more than any external research. Check CRM, Slack, and prior call notes before starting
  • Relying on a single source. Company websites are aspirational. Glassdoor reviews are biased. Job postings are directional. Triangulate across 3+ sources before drawing conclusions
  • Including unverified claims in the brief. "Their ARR is $15M" stated as fact when it's an estimate from headcount math. Always label estimates, inferences, and guesses
  • Sharing raw research instead of a brief. The account dossier is a decision-support document, not a research report. If the rep can't extract the angle in 3 minutes, rewrite the summary
  • Never updating the brief. Research done in January is stale by March. Re-verify signals and committee map before any campaign launch or re-engagement
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