consulting · service

Discovery & signal mapping.

Q: How long does the discovery process take?

Discovery typically takes 1-2 weeks, depending on the complexity of your system and the amount of data available. We work efficiently to gather insights without delaying the start of actual improvements.

Q: What if we don't have much analytics data?

That's okay. We can work with whatever data you have, and we'll help you set up better tracking if needed. Team interviews and qualitative research often reveal insights that data alone can't show.

Q: Will you need access to our systems?

We'll need read-only access to your analytics platforms and session recording tools. We don't need access to your codebase or production systems—just the data that shows how users interact with your product.

Q: What makes this different from a standard audit?

Most audits focus on what's wrong. Discovery focuses on what matters. We prioritize opportunities by potential impact, not just by what's broken. The goal is actionable insights, not a comprehensive list of issues.

Q: How do you ensure objectivity?

We start with data, not opinions. We form hypotheses based on patterns we observe, then validate them through multiple sources. If the data doesn't support a hypothesis, we discard it and look elsewhere.

Q: Can you do discovery remotely?

Yes, most discovery work can be done remotely. We use screen sharing for analytics reviews, video calls for team interviews, and collaborative tools for documentation. On-site visits are only necessary if you specifically need them.

We identify where value is created, lost, or slowed—through analytics, session data, and team interviews. Clear priorities and leverage points.

Data analytics dashboard showing metrics and insights

What We Discover

Every engagement starts by understanding how your system actually behaves—not how you think it should. We map the signals that reveal where value flows and where it gets stuck.

Analytics & Data Signals

We analyze your existing analytics to identify patterns: where users convert, where they drop off, and which paths drive real business outcomes. This isn't about vanity metrics—it's about finding the signals that predict success.

Session Data & User Behavior

Heatmaps, session recordings, and user flow data reveal friction points that analytics alone can't show. We identify where users hesitate, get confused, or abandon their journey—the moments that cost you conversions.

Team Interviews & Internal Knowledge

Your team knows things the data doesn't. We interview stakeholders, product managers, and customer-facing teams to understand operational bottlenecks, customer pain points, and opportunities that haven't been quantified yet.

The Outcome

After discovery, you get a clear map of priorities and leverage points. Not a 50-page report—a focused list of high-impact opportunities ranked by potential impact and effort required.

Clear Priorities

You'll know exactly where to focus first. No guesswork, no "we'll see"—just evidence-based priorities that align with your business goals.

The Discovery Process

Discovery isn't a one-time event—it's a structured process that combines quantitative data with qualitative insights. We follow a systematic approach that ensures we capture both what the numbers say and what your team knows.

Phase 1: Data Collection

We start by gathering all available data sources: analytics platforms, session recording tools, heatmap data, customer feedback, support tickets, and internal metrics. The goal is to build a comprehensive picture of how your system actually performs, not how it's supposed to perform.

Phase 2: Pattern Analysis

Once we have the data, we look for patterns. Where do users consistently drop off? Which paths lead to conversions? What behaviors correlate with success? We use statistical analysis to separate signal from noise, identifying trends that matter.

Phase 3: Hypothesis Formation

Data alone doesn't tell you what to do—it tells you where to look. We form hypotheses about why certain patterns exist. Is it a UX issue? A messaging problem? A technical bottleneck? These hypotheses become the foundation for testing.

Phase 4: Validation Through Interviews

We validate our hypotheses by talking to the people who know your system best: your team. Product managers, customer support, sales, and engineering all have insights that data can't capture. These conversations reveal the "why" behind the numbers.

Tools and Methods

We use a combination of tools depending on what's available and what makes sense for your context. Common tools include Google Analytics, Hotjar, Microsoft Clarity, Mixpanel, and custom analytics dashboards. But tools are secondary—the methodology matters more.

Quantitative Analysis

We analyze conversion funnels, user flows, drop-off points, time-on-page, scroll depth, click patterns, and any other metrics that reveal user behavior. The key is understanding which metrics actually correlate with business outcomes.

Qualitative Research

Session recordings show us where users hesitate, get confused, or abandon their journey. Heatmaps reveal what users notice and what they ignore. User interviews (when possible) provide direct feedback about pain points and motivations.

Deliverables

At the end of discovery, you receive a prioritized list of opportunities, not a lengthy report. Each opportunity includes:

What we found: The specific signal or pattern we identified
Why it matters: The potential impact on your business goals
What to test: Specific hypotheses to validate
Expected effort: Rough estimate of implementation complexity

What Happens Next

Discovery feeds directly into rapid prototyping. Once we know where the leverage points are, we design small, measurable tests to validate our assumptions—minimizing risk while maximizing learning speed.

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