Blueprint Playbook for Wood Mackenzie

Who the Hell is Jordan Crawford?

Founder of Blueprint. I help companies stop sending emails nobody wants to read.

The problem with outbound isn't the message. It's the list. When you know WHO to target and WHY they need you right now, the message writes itself.

I built this system using government databases, public records, and 25 million job posts to find pain signals most companies miss. Predictable Revenue is dead. Data-driven intelligence is what works now.

The Old Way (What Everyone Does)

Your GTM team is buying lists from ZoomInfo, adding "personalization" like mentioning a LinkedIn post, then blasting generic messages about features. Here's what it actually looks like:

The Typical Wood Mackenzie SDR Email:

Subject: Transforming Your Energy Strategy Hi [First Name], I noticed you're a VP at [Company] in the energy sector. Congrats on the recent post about sustainability! Wood Mackenzie provides data and analytics to help companies like yours make better decisions in the rapidly evolving energy landscape. We work with leading firms to optimize portfolios and navigate the energy transition. Our platform gives you access to: • Real-time market data across 50+ years • Expert analysis from 2,100+ analysts • AI-powered insights for investment decisions Are you available for a quick 15-minute call next week to discuss how we can support your strategic initiatives? Best, Account Executive

Why this fails: The prospect is an expert. They've seen this template 1,000 times. There's zero indication you understand their specific situation. Delete.

The New Way: Intelligence-Driven GTM

Blueprint flips the approach. Instead of interrupting prospects with pitches, you deliver insights so valuable they'd pay consulting fees to receive them.

1. Hard Data Over Soft Signals

Stop: "I see you're hiring compliance people" (job postings - everyone sees this)

Start: "Your team researched copper+Chile 47x last quarter" (aggregated internal research patterns only Wood Mackenzie can see)

2. Mirror Situations, Don't Pitch Solutions

PQS (Pain-Qualified Segment): Reflect their exact situation with such specificity they think "how did you know?" Use data patterns with timing, intensity, and peer comparisons.

PVP (Permissionless Value Proposition): Deliver immediate value they can use today - analysis already done, peer patterns already identified, competitive timing already mapped - whether they buy or not.

Wood Mackenzie Intelligence Plays

These messages demonstrate Wood Mackenzie's unique competitive advantage: visibility into what 100+ sophisticated energy/metals/mining organizations are researching and how they're positioning capital. This intelligence is impossible for competitors to replicate.

PVP Internal Data Strong (9.3/10)

Historical Research Pattern Recognition

What's the play?

Analyze the recipient's historical research patterns in Wood Mackenzie's system and correlate them with their subsequent corporate actions (acquisitions, major capex announcements). When current research intensity mirrors past patterns that preceded major deals, alert them with actionable deal intelligence.

Why this works

This is genuinely predictive intelligence about the prospect's own behavior that they can't get anywhere else. By showing them "you did this exact research pattern before your Las Bambas acquisition," you're proving deep analytical sophistication and providing a mirror to their own strategic process. The timing-matched deal comps offer creates immediate actionable value.

Data Sources
  1. Internal customer research access logs - commodity type, geography, query frequency, time period
  2. Historical corporate action database - M&A announcements, capex decisions, timing correlation

The message:

Subject: Your copper+Peru focus matches 2019 pattern Your team's copper-Peru research intensity in Q4 2024 mirrors the exact pattern from Q2 2019 - right before your Las Bambas acquisition announcement. History suggests you're 2-3 months from a major move. Want updated deal comps for Peru copper assets?
DATA REQUIREMENT

This play requires tracking historical research patterns by client organization (commodity-geography pairs, query frequency, time periods) and correlating them with subsequent corporate actions like acquisitions or major capex announcements.

This pattern recognition across customer behavior and market timing is proprietary to Wood Mackenzie - competitors cannot replicate this play.
PVP Internal Data Strong (9.2/10)

Competitive Deal Timing Intelligence

What's the play?

Track when competitors evaluate the same commodity-geography pairs within close time windows (e.g., BP researches copper+Zambia 8 days before the prospect's team). Alert prospects to competitive research activity that suggests they're evaluating the same assets or facing auction scenarios.

Why this works

This is competitive intelligence gold that directly impacts deal strategy and bidding decisions. Knowing that BP is researching the same assets 8 days before you helps executives anticipate auction competition, adjust bidding strategy, and prioritize due diligence. The alert service offer provides ongoing value that makes Wood Mackenzie indispensable for M&A teams.

Data Sources
  1. Internal customer research timing logs - commodity-geography pairs, timestamps, client organization
  2. Peer group definitions - companies with similar market cap, strategic focus, deal history

The message:

Subject: BP researched copper+Zambia the week before you BP's team spiked copper-Zambia research intensity 8 days before yours began in early January. That timing overlap suggests you're evaluating the same asset or similar projects. Want me to alert you when competitors research commodity-geography pairs within 30 days of your team?
DATA REQUIREMENT

This play requires tracking research activity timing across client organizations and identifying when competitors evaluate similar opportunities within close time windows (e.g., 7-30 days).

This competitive timing intelligence is only visible to Wood Mackenzie - no competitor can provide early warning of rival deal activity.
PVP Internal Data Strong (9.1/10)

Emerging Deal Activity Clustering

What's the play?

Identify when multiple competitors within the same peer group dramatically increase research intensity on the same commodity-geography pair (e.g., 400%+ spike in lithium+Argentina queries). Alert prospects to emerging deal hotspots before public announcements, showing which plays are getting crowded.

Why this works

This is actionable competitive intelligence that helps executives avoid overpaying in crowded auctions and prioritize deal timing. The 60-90 day lead time before announced deals gives strategic teams a window to position themselves or pivot to less competitive opportunities. The heatmap offer provides ongoing visibility into market dynamics.

Data Sources
  1. Internal aggregated research usage patterns - query frequency by commodity-geography, peer group analysis
  2. Historical deal timing data - time lag between research spikes and public M&A announcements

The message:

Subject: 3 firms spiked lithium+Argentina research in January Three of your competitors increased lithium-Argentina research queries by 400%+ in January compared to their 6-month average. That clustering typically precedes announced deals by 60-90 days. Want the heatmap showing which plays are getting crowded?
DATA REQUIREMENT

This play requires aggregating anonymized research usage patterns across peer group clients to identify commodity-geography pairs experiencing sudden attention spikes (e.g., 300%+ increase in query frequency within 30 days).

This aggregated peer intelligence is unique to Wood Mackenzie's position serving 100+ major energy/mining companies - impossible for competitors to replicate.
PVP Public + Internal Strong (9.0/10)

Policy Incentive Deadline Risk Alert

What's the play?

Cross-reference public capex announcements with policy incentive deadlines (IRA Section 45Q) and Wood Mackenzie's project timeline models to identify when companies are at risk of missing critical incentive windows. Calculate specific financial impact (% of incentive window lost) and provide acceleration scenarios.

Why this works

This creates real urgency by quantifying financial risk from timing delays. The specific calculation of capture potential (1.2M tons annually) and the 2033 deadline makes this immediately actionable for CFOs and strategy teams. Showing competitor timelines (Exxon, Chevron) proves the prospect is behind on a time-sensitive opportunity. The acceleration scenarios provide exactly what executives need for board discussions.

Data Sources
  1. Public capex announcements - CCUS project size, timeline, announced investment
  2. IRA Section 45Q policy requirements - deadlines, capture volume thresholds, credit amounts
  3. Internal project timeline models - typical construction duration, permitting timelines, competitor project pace

The message:

Subject: Your CCUS spend lags policy incentive timelines Your carbon capture capex ($180M announced) would capture ~1.2M tons annually - but IRA Section 45Q requires projects operational by 2033 for full credits. At current pace, you'd miss 60% of the incentive window compared to Exxon and Chevron's timelines. Want the project acceleration scenarios showing required spend by quarter?
DATA REQUIREMENT

This play combines public capex announcements with Wood Mackenzie's proprietary policy analysis, project timeline modeling, and competitor benchmarking to calculate specific financial risk from timing delays.

The synthesis of policy requirements, project economics, and competitive positioning is unique to Wood Mackenzie's analytical capabilities.
PVP Public + Internal Strong (8.9/10)

Technology Transition Positioning Benchmark

What's the play?

Combine public capex announcements with Wood Mackenzie's proprietary peer classification to show when companies are taking aggressive or lagging positions on specific energy transition technologies (offshore wind, hydrogen, CCUS). Frame both upside (first-mover advantages) and risk (execution challenges, supply chain constraints).

Why this works

The 2x comparison is striking and immediately positions the conversation around strategic choice rather than judgment. By acknowledging both first-mover advantages AND execution risk, you demonstrate sophisticated understanding of strategy tradeoffs. The supply chain risk callout is timely given current offshore wind bottlenecks. Scenario models are exactly what executives need for board-level capital allocation discussions.

Data Sources
  1. Public capex announcements - offshore wind commitments by company, timeline, project size
  2. Internal peer benchmarking - market cap-matched comparison groups, median investment levels
  3. Internal supply chain risk models - equipment lead times, manufacturing capacity constraints, policy scenario forecasting

The message:

Subject: You're outpacing peers 2:1 on offshore wind Your offshore wind capex commitments ($1.8B announced) are 2x the median for oil majors with similar market cap. That aggressive positioning could create first-mover advantages in lease auctions - or execution risk if supply chains tighten. Want the scenario models showing break-even timelines under different policy outcomes?
DATA REQUIREMENT

This play combines public capex data with Wood Mackenzie's proprietary peer group classification, supply chain risk models, and policy scenario forecasting to provide strategic positioning context.

The balanced framing of first-mover advantages vs execution risk demonstrates Wood Mackenzie's analytical sophistication beyond simple benchmarking.
PVP Internal Data Strong (8.8/10)

Competitive Research Activity Gap Alert

What's the play?

Identify when competitors dramatically increase research intensity on a commodity-geography pair while the prospect's team shows no corresponding activity spike. Alert them to emerging opportunities they might be missing, with specific project-level intelligence available.

Why this works

The competitive intelligence ("five firms spiked lithium-Australia research 340%") combined with the urgency framing ("you might be missing an emerging opportunity window") creates immediate FOMO. This helps executives avoid being late to market moves that competitors are already evaluating. The specific projects offer makes this immediately actionable.

Data Sources
  1. Internal research usage patterns - query frequency by client, commodity-geography focus, time period comparison
  2. Peer group analysis - competitor identification and research activity benchmarking

The message:

Subject: Lithium+Australia queries up 340% across your competitors Five firms in your peer group spiked lithium-Australia research by 340% in the past 30 days compared to prior quarter. Your team's usage stayed flat - you might be missing an emerging opportunity window. Want to see which specific projects are drawing attention?
DATA REQUIREMENT

This play requires aggregating anonymized research usage patterns across peer group competitors to identify emerging hotspots, then comparing against the recipient's research activity to identify gaps.

This competitive gap analysis is unique to Wood Mackenzie's visibility across 100+ major energy/mining companies.
PVP Internal Data Strong (8.7/10)

Strategic Research Intensity Signals

What's the play?

Track which commodity-geography pairs individual client organizations research most intensely (e.g., 47 queries in one quarter). High intensity typically signals early-stage M&A diligence or major capex evaluation. Offer to alert them when competitors spike research on the same plays.

Why this works

This reveals strategic focus areas before public announcements, showing Wood Mackenzie sees internal planning processes. The inference that high intensity signals M&A diligence demonstrates pattern recognition across customer behavior. The competitor intel offer provides ongoing value by helping executives understand when their strategic priorities are shared by rivals.

Data Sources
  1. Internal customer research access logs - query frequency by commodity-geography, user organization, time period
  2. Historical correlation data - research intensity patterns preceding announced M&A or capex decisions

The message:

Subject: Your team researched copper+Chile 47x last quarter Your analysts pulled our copper reports for Chile 47 times in Q4 - 3x more than any other commodity-geography pair. That intensity usually signals early-stage M&A diligence or major capex evaluation. Should I flag when competitors spike research on the same plays?
DATA REQUIREMENT

This play requires tracking which client organizations access which commodity-geography research reports and identifying usage intensity patterns that typically precede strategic decisions.

This visibility into customer strategic planning processes is unique to Wood Mackenzie's platform usage data.
PVP Public + Internal Strong (8.6/10)

First-Mover Advantage Timeline Analysis

What's the play?

Compare public project timelines across competitors for emerging technologies (floating offshore wind) to identify specific timeline gaps that create first-mover pricing power or market disadvantages. Offer timeline compression analysis showing where acceleration is possible.

Why this works

The specific competitor comparison with exact timeline delta (18 months) makes the strategic disadvantage tangible and urgent. First-mover advantage framing creates strategic pressure without being accusatory. The timeline compression analysis provides actionable intelligence for project teams and helps executives make the case for acceleration to leadership.

Data Sources
  1. Public project timeline announcements - first commercial operation dates, construction start dates
  2. Internal competitive positioning analysis - market impact of timing advantages, lease market dynamics
  3. Internal timeline compression models - critical path analysis, acceleration scenario costs

The message:

Subject: Equinor beats you to floating wind by 18 months Equinor's floating offshore wind timeline puts their first commercial project online Q2 2026 - yours targets Q4 2027. That 18-month gap gives them first-mover pricing power in emerging lease markets. Want the timeline compression analysis showing where you could accelerate?
DATA REQUIREMENT

This play combines public project timelines with Wood Mackenzie's proprietary competitive positioning analysis and project acceleration scenario modeling to identify strategic timing risks.

The synthesis of competitive timing intelligence with actionable acceleration pathways is unique to Wood Mackenzie's analytical capabilities.
PVP Internal Data Strong (8.5/10)

Strategic Research Activity Drop Detection

What's the play?

Track when client organizations dramatically reduce research intensity on commodity-geography pairs after sustained high activity (e.g., 90% drop in rare earth elements research after Q3 peak). Sudden stops typically signal either deal completion or strategic pivot. Offer competitive redirect intelligence if they pivoted.

Why this works

This demonstrates sophisticated tracking that notices research activity DROPS, not just spikes. The two interpretations (deal done or pivot) show strategic thinking about what drives behavior change. The competitor redirect offer is useful if they pivoted away from an opportunity, helping them understand where peers moved instead.

Data Sources
  1. Internal research activity trends - query frequency over time, baseline activity levels, sudden drop detection
  2. Peer group redirect analysis - where competitors shifted research focus after similar drops

The message:

Subject: Your rare earths research went dark 60 days ago Your team's rare earth elements research dropped 90% in the past 60 days after sustained high activity in Q3. That sudden stop usually means either deal completion or strategic pivot away. If you pivoted, want to see which commodity-geography pairs your competitors moved toward instead?
DATA REQUIREMENT

This play requires tracking research activity trends over time to identify sudden drops that signal strategic shifts (deal completion, pivot decisions), then analyzing where peer competitors redirected focus.

This longitudinal behavior analysis and peer comparison is unique to Wood Mackenzie's visibility across customer strategic planning.
PVP Public + Internal Strong (8.4/10)

Energy Transition Capex Positioning Benchmark

What's the play?

Combine public capex announcements with Wood Mackenzie's proprietary peer classification and technology type categorization to show where companies rank in energy transition capital spending by specific technology (hydrogen, offshore wind, CCUS). Offer full benchmarking breakdown by technology type.

Why this works

The specific percentile ranking (40th) with exact dollar figure creates immediate context for strategic positioning. Naming specific competitors (Shell, BP, TotalEnergies) at 75th percentile makes it credible and creates competitive pressure. The technology breakdown offer is useful for portfolio allocation decisions and board discussions about where to deploy capital.

Data Sources
  1. Public capex announcements - hydrogen infrastructure investment amounts, project timelines
  2. Internal peer group classification - integrated energy majors with similar market cap and strategic focus
  3. Internal technology categorization - classification of announced investments by technology type

The message:

Subject: Your hydrogen capex is 40th percentile vs peers Your announced hydrogen infrastructure capex ($340M through 2026) puts you in the 40th percentile compared to integrated energy majors. Shell, BP, and TotalEnergies are all 75th percentile or higher - positioning for policy incentives. Want the full benchmarking breakdown by technology type?
DATA REQUIREMENT

This play combines public capex announcements with Wood Mackenzie's proprietary peer group classification and benchmarking methodology to provide percentile rankings by technology type.

The synthesis of public data with proprietary peer classification and technology categorization is unique to Wood Mackenzie's analytical framework.

What Changes

Old way: Spray generic messages at job titles. Hope someone replies.

New way: Use aggregated customer behavior data to identify who's evaluating which opportunities RIGHT NOW. Then mirror that intelligence back with competitive context.

Why this works: When you lead with "Your team researched copper+Chile 47 times last quarter - 3x more than any other commodity-geography pair" instead of "I see you're focused on growth opportunities," you're not another sales email. You're the person who sees patterns they didn't know were visible.

The messages above aren't templates. They're examples of what happens when you combine internal customer behavior data with competitive peer analysis. Your team can replicate this using the data capabilities and synthesis approaches outlined in each play.

Wood Mackenzie's unique advantage: You serve 100+ sophisticated energy/metals/mining organizations. That gives you visibility into what smart money is researching, when competitive activity clusters around opportunities, and how peer institutions position capital. No competitor can replicate this aggregated intelligence - it only exists because of your customer base.

Data Sources Reference

Every play traces back to Wood Mackenzie's unique data capabilities. Here are the sources that enable these intelligence plays:

Source Type Key Data Used For
Internal Customer Research Logs Query frequency, commodity-geography pairs, timestamps, user organization Identifying research intensity patterns, strategic focus areas, competitive activity clustering
Historical Corporate Action Database M&A announcements, major capex decisions, timing correlation with research patterns Correlating research patterns with subsequent deal activity, predictive intelligence
Peer Group Classification Market cap, strategic focus, deal history, technology positioning Benchmarking capital allocation, identifying competitive peer sets
Public Capex Announcements Investment amounts, project timelines, technology types, geographic focus Competitive positioning analysis, percentile rankings, timeline gap identification
Policy & Incentive Database IRA Section 45Q requirements, regulatory deadlines, carbon pricing proposals, renewable mandates Identifying policy incentive deadline risks, quantifying financial impact of timing delays
Project Timeline Models Construction duration, permitting timelines, supply chain constraints, competitor project pace Acceleration scenario modeling, first-mover advantage analysis, execution risk assessment

Critical insight: The most powerful plays combine internal customer behavior data with public market information. For example: tracking which commodity-geography pairs competitors research (internal) + their public capex announcements = predictive intelligence about where deals will happen before public announcements.