Outdoo AI
Outdoo AI
AI platform turning sales calls into actionable revenue insights
AI platform turning sales calls into actionable revenue insights
Outdoo.ai is an AI Revenue Intelligence platform that helps sales teams sell smarter and coach better. It analyzes recorded sales meetings using AI-powered trackers to surface buying signals, objections, and customer pain points in real time.
Managers get a unified view of team performance, deal health, and coaching opportunities, while reps get scored, actionable feedback on every call. I led the design of the core intelligence workflows, from call review to manager dashboards to AI coaching, turning raw, messy sales conversations into clear, decision-ready insight. The redesign scaled with the platform to 300K+ active users.
Outdoo.ai is an AI Revenue Intelligence platform that helps sales teams sell smarter and coach better. It analyzes recorded sales meetings using AI-powered trackers to surface buying signals, objections, and customer pain points in real time.
Managers get a unified view of team performance, deal health, and coaching opportunities, while reps get scored, actionable feedback on every call. I led the design of the core intelligence workflows, from call review to manager dashboards to AI coaching, turning raw, messy sales conversations into clear, decision-ready insight. The redesign scaled with the platform to 300K+ active users.
AI SAAS
AI SAAS
—
NATIVE WEB
NATIVE WEB
—
REVENUE INTELLIGENCE
REVENUE INTELLIGENCE
—
ENTERPRISE UX
ENTERPRISE UX
—
AI AGENTS
AI AGENTS
—
UX RESEARCH
UX RESEARCH
—
PRODUCT STRATEGY
PRODUCT STRATEGY
CLIENT
CLIENT
Outdoo.ai (12 person startup)
Outdoo.ai (12 person startup)
MY ROLE
MY ROLE
Sole Product Designer.
Full ownership of strategy, research, and design systems across the redesign.
Sole Product Designer.
Full ownership of strategy, research, and design systems across the redesign.
DURATION
DURATION
February 2024 - March 2025 (13 months)
February 2024 - March 2025 (13 months)
TOOLS
TOOLS
OVERVIEW
OVERVIEW
Sales teams record thousands of hours of customer conversations and almost never look at them again. My job was to design the layer that sits between that raw AI output and the humans who need to act on it: the dashboards, the call review tools, the coaching systems. The redesign turned a 45-minute call recording into something a manager could review for risk and coaching in a few clicks, and helped scale the platform to 300K+ users and counting
Sales teams record thousands of hours of customer conversations and almost never look at them again. My job was to design the layer that sits between that raw AI output and the humans who need to act on it: the dashboards, the call review tools, the coaching systems. The redesign turned a 45-minute call recording into something a manager could review for risk and coaching in a few clicks, and helped scale the platform to 300K+ users and counting
45 min
45 min
3 Clicks
3 Clicks
Reviewing a call for objections and buying signals
Jumping to key moments in a call
Reviewing a call for objections and buying signals
Jumping to key moments in a call
5 Hrs
5 Hrs
1 Search
1 Search
Finding how reps handle a specific topic
Tracking a topic across every recorded call
Finding how reps handle a specific topic
Tracking a topic across every recorded call
THE PRODUCT CONTEXT
THE PRODUCT CONTEXT
"Just want to see the work? Skip to the delivered screens"
Sales teams generate an enormous amount of conversational data every day, but almost none of it gets reviewed or acted on in a structured way. Managers were relying on gut feel and spot-checking a handful of calls, while reps got inconsistent, infrequent coaching. There was no institutional mechanism turning conversations into a repeatable, improvable sales process.
The consequences compound. Deals stall without anyone noticing the warning signs; coaching happens reactively, if at all; and the same objections cost the same deals quarter after quarter with no system learning from them.
Sales teams generate an enormous amount of conversational data every day, but almost none of it gets reviewed or acted on in a structured way. Managers were relying on gut feel and spot-checking a handful of calls, while reps got inconsistent, infrequent coaching. There was no institutional mechanism turning conversations into a repeatable, improvable sales process.
The consequences compound. Deals stall without anyone noticing the warning signs; coaching happens reactively, if at all; and the same objections cost the same deals quarter after quarter with no system learning from them.
Outdoo.ai was built to solve this. Revenue Intelligence is a crowded, competitive category, and every player differentiates almost entirely on trust and usability, not raw AI capability, since most platforms use similar underlying models. The mandate was to make advanced AI output feel obvious and actionable for a non-technical, time-poor sales audience, at a scale spanning five-person pods to enterprise orgs with hundreds of reps.
Outdoo.ai was built to solve this. Revenue Intelligence is a crowded, competitive category, and every player differentiates almost entirely on trust and usability, not raw AI capability, since most platforms use similar underlying models. The mandate was to make advanced AI output feel obvious and actionable for a non-technical, time-poor sales audience, at a scale spanning five-person pods to enterprise orgs with hundreds of reps.
RESEARCH AND DISCOVERY
RESEARCH AND DISCOVERY
I ran interviews and shadowing sessions with sales managers and reps to understand how they actually reviewed calls, coached their teams, and tracked deal risk today, and where the current tools broke down. Two pain points came up constantly:
I ran interviews and shadowing sessions with sales managers and reps to understand how they actually reviewed calls, coached their teams, and tracked deal risk today, and where the current tools broke down. Two pain points came up constantly:
Finding #1 - Managers spent hours hunting for one detail inside a recording, not making decisions from it.
Finding #1 - Managers spent hours hunting for one detail inside a recording, not making decisions from it.
One sales manager described keeping a competitor's tool open on a second monitor most of the day, mainly to hunt for a single detail a rep had forgotten to log.
One sales manager described keeping a competitor's tool open on a second monitor most of the day, mainly to hunt for a single detail a rep had forgotten to log.
"It's mostly just a search tool for me at this point. I'm not going in to make a decision, I'm going in because I already know something's wrong and I need to find it."
"It's mostly just a search tool for me at this point. I'm not going in to make a decision, I'm going in because I already know something's wrong and I need to find it."
Sales Manager, mid-market SaaS team
Finding #2 - Coaching scorecards felt like a grade, so reps ignored it.
Finding #2 - Coaching scorecards felt like a grade, so reps ignored it.
Reps described bare numeric scorecards from other tools as demotivating rather than instructive, and said they were far more likely to engage with feedback tied to a specific, replayable moment in a call.
Reps described bare numeric scorecards from other tools as demotivating rather than instructive, and said they were far more likely to engage with feedback tied to a specific, replayable moment in a call.
"If you just show me a number, I don't know what to do with it. Show me the fifteen seconds where I messed up and I'll actually watch it."
"If you just show me a number, I don't know what to do with it. Show me the fifteen seconds where I messed up and I'll actually watch it."
Account Executive, enterprise sales team
In parallel, I ran a side-by-side teardown of Gong and Avoma, the two most established players in the category. Gong had the most mature information architecture, but its depth came at a cost: dense, metric-heavy screens that assumed familiarity, echoed in reviews describing the product as unintuitive and leaving users to figure out the "now what" themselves. Avoma took a lighter, modular approach that made individual screens simpler, but sacrificed coherence, with reviews frequently citing reliability gaps and a stitched-together feel across its separate assistant, scheduler, and intelligence modules. Neither competitor closed the loop from insight to action, that gap was outdoo.ai's opening.
In parallel, I ran a side-by-side teardown of Gong and Avoma, the two most established players in the category. Gong had the most mature information architecture, but its depth came at a cost: dense, metric-heavy screens that assumed familiarity, echoed in reviews describing the product as unintuitive and leaving users to figure out the "now what" themselves. Avoma took a lighter, modular approach that made individual screens simpler, but sacrificed coherence, with reviews frequently citing reliability gaps and a stitched-together feel across its separate assistant, scheduler, and intelligence modules. Neither competitor closed the loop from insight to action, that gap was outdoo.ai's opening.
KEY DECISIONS
KEY DECISIONS
Lead with narrative, not numbers.
Lead with narrative, not numbers.
The research made one thing clear: managers didn't want more data, they wanted faster judgment. Every screen leads with a plain-language AI summary or a visual timeline, with the underlying metrics (talk ratio, engagement score, sentiment) available a layer beneath for anyone who wants to dig in. This single decision is what separated the redesign from every competitor screen we tore down, none of them made that trade.
The research made one thing clear: managers didn't want more data, they wanted faster judgment. Every screen leads with a plain-language AI summary or a visual timeline, with the underlying metrics (talk ratio, engagement score, sentiment) available a layer beneath for anyone who wants to dig in. This single decision is what separated the redesign from every competitor screen we tore down, none of them made that trade.
AI coaching is a suggestion, not a verdict.
AI coaching is a suggestion, not a verdict.
Every competitor in the space scores reps with a number. That was table stakes, not a differentiator, and our research showed it actively got ignored. I reframed coaching around specific, evidence-backed moments, "at 12:40, the prospect raised pricing and there was no follow-up question", paired with the call snippet itself, so the AI's role felt like an assistant pointing at evidence rather than a system issuing a grade.
Every competitor in the space scores reps with a number. That was table stakes, not a differentiator, and our research showed it actively got ignored. I reframed coaching around specific, evidence-backed moments, "at 12:40, the prospect raised pricing and there was no follow-up question", paired with the call snippet itself, so the AI's role felt like an assistant pointing at evidence rather than a system issuing a grade.
One continuous workflow, not disconnected modules.
One continuous workflow, not disconnected modules.
Avoma's fragmentation across separate tools was a direct warning sign. Call recording, trackers, coaching, and deal activity were designed as a single connected narrative, so a manager could move from "this deal looks at risk" to "here's the call where it started" to "here's the coaching moment for the rep" without leaving the flow or re-orienting themselves in a different tool.
Avoma's fragmentation across separate tools was a direct warning sign. Call recording, trackers, coaching, and deal activity were designed as a single connected narrative, so a manager could move from "this deal looks at risk" to "here's the call where it started" to "here's the coaching moment for the rep" without leaving the flow or re-orienting themselves in a different tool.
SCREENS DELIVERED
SCREENS DELIVERED
A fully designed system spanning call review, team intelligence, and coaching, built to scale from a five-person sales pod to an enterprise org with hundreds of reps, and to hold up across both a dark and light theme for extended review sessions.
A fully designed system spanning call review, team intelligence, and coaching, built to scale from a five-person sales pod to an enterprise org with hundreds of reps, and to hold up across both a dark and light theme for extended review sessions.
Dark & Light Mode: Before any feature work, the platform was built on a dual-theme foundation designed in parallel from day one, not layered on as a setting later. Sales managers review calls and dashboards for hours at a stretch, so dark mode reduces eye strain during extended sessions while light mode keeps clarity for scanning dense tables during the day. Getting this right early meant every later chart, timeline, and data-heavy screen inherited a consistent, tested foundation instead of needing color and contrast fixes retrofitted module by module.
Dark & Light Mode: Before any feature work, the platform was built on a dual-theme foundation designed in parallel from day one, not layered on as a setting later. Sales managers review calls and dashboards for hours at a stretch, so dark mode reduces eye strain during extended sessions while light mode keeps clarity for scanning dense tables during the day. Getting this right early meant every later chart, timeline, and data-heavy screen inherited a consistent, tested foundation instead of needing color and contrast fixes retrofitted module by module.
Video Timeline & Call Review: An interactive playback experience with a dynamic, AI-annotated timeline marking objections, buying signals, and topic changes. Managers jump directly to the moments that matter, trim clips, and generate follow-up actions without re-watching entire calls.
Video Timeline & Call Review: An interactive playback experience with a dynamic, AI-annotated timeline marking objections, buying signals, and topic changes. Managers jump directly to the moments that matter, trim clips, and generate follow-up actions without re-watching entire calls.
Conversations Hub: A searchable, filterable command center for every recorded meeting, with AI summaries, coaching scores, and tracker activity on each call card. A cross-call search feature lets managers type any keyword, pricing, a competitor name, an objection, and instantly see every moment it was mentioned across the entire call library.
Conversations Hub: A searchable, filterable command center for every recorded meeting, with AI summaries, coaching scores, and tracker activity on each call card. A cross-call search feature lets managers type any keyword, pricing, a competitor name, an objection, and instantly see every moment it was mentioned across the entire call library.
Custom Trackers & Filters: A configurable system for building trackers around deal stage, sentiment, rep, duration, and AI-detected events, letting teams tailor the platform to their own sales motion rather than a fixed taxonomy.
Custom Trackers & Filters: A configurable system for building trackers around deal stage, sentiment, rep, duration, and AI-detected events, letting teams tailor the platform to their own sales motion rather than a fixed taxonomy.
Manager & RevOps Dashboard: A modular, widget-based dashboard surfacing meeting activity, coaching scores, team trends, deal health, and top performers in real time, giving a high-level snapshot with one-click drill-down into specifics.
Manager & RevOps Dashboard: A modular, widget-based dashboard surfacing meeting activity, coaching scores, team trends, deal health, and top performers in real time, giving a high-level snapshot with one-click drill-down into specifics.
Deal Activity Timeline (CRM-integrated): A chronological, AI-annotated narrative of every touchpoint in a deal: calls, emails, follow-ups, objections, re-engagements, surfacing both positive momentum and stalled moments so managers know exactly when to step in.
Deal Activity Timeline (CRM-integrated): A chronological, AI-annotated narrative of every touchpoint in a deal: calls, emails, follow-ups, objections, re-engagements, surfacing both positive momentum and stalled moments so managers know exactly when to step in.
Folder System: A structured way to organize calls by client, deal stage, rep, or workflow, replacing an unstructured, scrolling call list with folders that summarize meeting count, last activity, and key AI-detected insights.
Folder System: A structured way to organize calls by client, deal stage, rep, or workflow, replacing an unstructured, scrolling call list with folders that summarize meeting count, last activity, and key AI-detected insights.
Team Performance Overview: A dedicated screen for scoring individual and team performance at a glance, surfacing average call scores, call duration, talk-to-listen ratio, interactivity, and the other underlying metrics that feed into how a rep or a team is actually performing. Rather than burying these numbers inside individual call reviews, this screen pulls them together so managers can compare reps side by side, spot who's trending up or down, and know exactly which metric is driving a low score before stepping in.
Team Performance Overview: A dedicated screen for scoring individual and team performance at a glance, surfacing average call scores, call duration, talk-to-listen ratio, interactivity, and the other underlying metrics that feed into how a rep or a team is actually performing. Rather than burying these numbers inside individual call reviews, this screen pulls them together so managers can compare reps side by side, spot who's trending up or down, and know exactly which metric is driving a low score before stepping in.
Deal & Coaching Performance Insights: A real-time view of how each opportunity is progressing, with indicators for momentum, risk, and next steps at both the team and individual rep level. AI highlights key shifts in engagement or sentiment so managers can quickly spot deals that need attention, helping teams prioritize the right opportunities and stay ahead of blockers before they cost a deal.
Coaching Inbox: A centralized, actionable feed of AI-generated insights and manager feedback, with each coaching card highlighting a specific improvement area, objection handling, talk-to-listen balance, discovery depth, missed opportunities. Users review suggestions alongside the relevant call snippets and track progress over time, turning ad-hoc feedback into a continuous, structured learning loop across the team.
The redesign helped scale outdoo.ai to over 300,000 users and counting, while improving conversation quality, coaching consistency, and adoption across active customer accounts. The product is now in active development as its foundational features have been refined and it has been growing since then.
The redesign helped scale outdoo.ai to over 300,000 users and counting, while improving conversation quality, coaching consistency, and adoption across active customer accounts. The product is now in active development as its foundational features have been refined and it has been growing since then.
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