| Status | Published |
|---|---|
| Draft | July 8, 2025 |
assignment_late Important
Before reading Fairing's Strategy, make sure you've reviewed the Understanding Strategy primer.
Fairing Company Strategy
Table of Contents
Executive Summary
As an early-stage startup, our most valuable asset is focus. We have endless opportunities and limited resources. To win, we need to be crystal clear on where we are going and how we will get there, ensuring every team member is moving in the same direction.
This document is our blueprint for achieving that focus. This is not a
corporate process
; it’s a logical, founder-led exercise to help
us execute faster and make better decisions every day. By answering five
simple questions in sequence, we create a powerful, cohesive strategy that
eliminates wasted effort and aligns the entire company.
The five questions we’ve answered are:
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What is our winning aspiration? This is our north star. It’s what gets us out of bed in the morning and inspires our team.
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Where will we play? This is our battlefield. By being incredibly specific about our ideal customer-their size, challenges, and mindset-we focus our energy on the deals we can actually win, instead of chasing every shiny object.
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How will we win? This is our unique advantage. On our chosen battlefield, what makes us different and better than any other option? This is our recipe for success.
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What capabilities must we have? Based on how we’ve chosen to win, this identifies the handful of things we must be world-class at. Not good at, but truly excellent.
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What enabling management systems do we need? This defines the simple processes and systems we need to build and maintain those critical capabilities.
Winning Aspiration
Become the world’s best infrastructure for collecting reliable zero-party marketing attribution data.
Where to Play
Our ideal customer is a non-Shopify, growth-focused company of a specific scale that is investing heavily in marketing but struggling to get reliable attribution data from their most important or hard-to-measure channels.
Quantitative Customer Profile
This profile is defined by metrics that indicate a company has the scale and strategic intent to derive maximum value from our solution.
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Company Revenue: Spending between $2MM and $150MM on marketing annually, and between 15% to 30% of their annual gross revenue. This means companies between $10MM and $500MM in gross revenue.
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Vertical: Agnostic. Our solution works across industries.
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Minimum Scale: Handling at least 5,000 conversions a month.
info Rationale for this profile
This quantitative profile was developed by synthesizing data from our most successful existing customers with forward-looking analysis of our ideal customer archetype.
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Learning from Existing Data: Our Shopify customer base reveals a clear pattern: our best customers, in terms of both revenue and stickiness, are those processing over 10,000 orders per month, marketing on at least one hard-to-measure channel, and spending at least $2MM annually on marketing.
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Budget Size: When a brand starts spending more than $2MM annually on marketing, they are forced to expand into harder to measure channels due to diminishing returns on easier to track but highly competitive digital channels (e.g. Google Ads, Meta Ads, etc).
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Budget Proportion: When companies are spending 15%-30% of gross revenue on marketing, it indicates they are in a high or aggressive growth phase. In this phase, they are typically experimenting with a broad range of channels, and those channels create a mix of signals (e.g. clicks, UTMs, etc) that make it difficult to attribute conversions to the correct source.
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Conversion Scale: Brands processing at least 5,000 conversions per month have enough volume to generate meaningful attribution insights. We set this below our Shopify baseline of 10,000 because customers with larger cart sizes can have fewer conversions while still being ideal fits.
This approach anchors our strategy in what has already proven successful while building a clear, data-informed profile for the new customers we aim to acquire.
Qualitative Customer Profile
This profile describes the common situations, mindsets, and challenges that make a company a perfect fit for our infrastructure and expertise.
Common Challenges & Pain Points
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They are actively or about to start marketing on channels where traditional pixel-based attribution fails, such as podcasts, TV, influencer marketing, or out-of-home advertising.
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They may have an inflexible in-house solution that cannot be easily iterated upon because their development teams typically deprioritize marketing initiatives.
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Marketing on more than a handful of channels and don't have a good overview of all channel performance.
Mindset & Expertise Gap
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They are typically data-driven but not always data-fluent; they value data but lack the deep expertise to optimize its collection and interpretation.
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They are highly design conscious and require any customer-facing element to be polished and complete.
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They know which questions to ask, but not how to phrase them, or how survey design impacts data quality and bias.
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They recognize they have this expertise gap and value strategic support, often seeking advice before committing to a solution.
How to Win
We capitalize on marketing measurement's biggest missed opportunity, transforming an intrusive question into a rewarding exchange for the consumer, and the responses into the world's most reliable attribution intelligence.
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We’re a Partner, Not a Platform
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Our Choice: We will treat the entire customer lifecycle—from their first website visit to ongoing support—as a core part of our product. We will guide our customers with a strategic, prescriptive approach that eliminates guesswork.
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Our Competitive Edge: Competitors sell tools; we deliver answers. We win by embedding our expertise directly into our product and process, providing a clear, fast path to reliable data from day one. This transforms us from a software vendor into an indispensable strategic partner.
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Optimized for Delight in the Day-to-Day
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Our Choice: We will build a customer product experience that is not just functional, but delightful and intuitive. We obsess over the details of workflow, information hierarchy, and visual design.
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Our Competitive Edge: Our obsession with craft in the product UI communicates a level of quality that builds deep trust. It signals to our customers that if we sweat the small details, we also sweat the big ones. This creates confidence and makes our product a joy to use.
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Research-Driven and Evidence-Based Collection
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Our Choice: We are obsessed with the science of the ask and treat the consumer as a human, not a data point. Our design process will be rooted in continuous research into consumer psychology and user experience design, and validated by relentless testing.
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Our Competitive Edge: Our deep, research-driven approach to designing high-converting consumer experiences is our defensible moat.
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Verified Reliable, Structured Attribution Data
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Our Choice: We will deliver verifiably reliable data by investing in the capability to experimentally validate its quality, and then programmatically clean, normalize, and enrich it into an analytics-optimized format.
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Our Competitive Edge: Customers don’t think about response reliability, and don’t have the capabilities to test it. Their pain is messy, unstructured data. We win by acting as their outsourced data science team: we solve the critical problem they don't see (reliability) and deliver the elegant solution to the pain they feel every day (actionable data). This unique, two-pronged value proposition makes our solution essential.
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Must Have Capabilities
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Scalable Lead Generation Engine The ability to predictably and efficiently generate a pipeline of qualified leads who match our Ideal Customer Profile.
Our strategy only works if we can find the right customers at scale. This means building a marketing engine that attracts growth-focused, data-driven buyers. We don't care about leads, we care about quality leads.
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Seamless Customer Integration & Time-to-Value A repeatable process that takes customers from discovering Fairing to their first valuable data point as quickly as possible.
We act as strategic advisors, not pushy salespeople. We quickly diagnose customer needs, map their integration path, and guide them to value fast using a repeatable process, not heroic efforts.
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Actionable Data Transformation The ability to programmatically clean, structure, and normalize messy, unstructured consumer responses into analytics-ready data.
Raw consumer responses are messy, inconsistent, and full of typos. We programmatically transform this chaos into clean, analytics-ready data. Without this capability, we're just collecting noise, not actionable intelligence.
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World-Class Product Experience Design Designing exceptional experiences across our entire product, from the surveys consumers take to the dashboards our customers use daily.
This isn't about making things look pretty. It's understanding the psychology and needs of both consumers and customers to create experiences that feel intuitive, rewarding, and frictionless.
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High-Velocity Experimentation & Insight Generation The ability to rapidly test hypotheses and translate data into proven improvements for our product and our customers.
This goes beyond having a platform. It's our organizational muscle to continuously form hypotheses, run A/B tests on everything from button colors to question phrasing, and quickly turn results into product improvements.
Enabling Management Systems
These processes help us build and maintain our Must Have Capabilities. We'll start with the most critical parts and improve them over time. We won't try to do everything at once—that's a recipe for burnout and failure. Instead, we'll focus on building the foundation that turns us into a high-performance team.
Scalable Lead Generation Engine
These processes turn our marketing and sales efforts from guesswork into a predictable system that consistently generates qualified opportunities.
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Marketing & Sales Performance & Strategy Sessions: Regular sessions to review funnel performance, learn what's working, and plan our next marketing experiments and content.
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Lead Qualification & Handoff: A clear system for scoring leads based on their fit and buying intent, managing qualified leads, and smoothly transitioning them to the sales team.
Customer Journey to Value
Guide customers from their first conversation with us to getting real value from our product—without the chaos of making it up as we go.
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Strategic Sales Playbook: A guide for the sales team that outlines our consultative, strategy-led sales approach, ensuring we position ourselves as strategic advisors from the first conversation.
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Customer Onboarding Playbook: A step-by-step guide that walks our team through getting new customers up and running, from their first call to full integration.
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Customer Success Check-ins: Regular reviews with customers to make sure they're getting maximum value and to spot opportunities for deeper partnership.
Integrated Design & Experimentation
Connect our design and experimentation work into one fast-moving cycle: test ideas, learn what works, design better solutions, then test again.
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Feature Design & Validation Process: When we get insights from experiments, we turn them into features through design sprints, rapid prototyping, and user testing. No feature gets built until real users validate that it actually solves their problem.
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Automated Visual & Responsive Testing System: Automated tests that run every time we change code to catch visual bugs before customers see them. This ensures our product looks and works consistently across all devices and browsers.
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Experiment Review & Design Process: Regular sessions led by our data scientist to share what we learned from our tests and outside research, then decide what to test next.
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Consistent Experimentation Mechanism: A standard toolkit and process for running experiments so we're not reinventing the wheel each time. Everyone follows the same approach for testing, measuring, and analyzing results.