Emergency Dashboard Design & Delivery

Designing a Unified Marketing Operations Dashboard

Emergency Dashboard Design & Delivery

Designing a Unified Marketing Operations Dashboard

How I designed and shipped a critical sales dashboard in 3 weeks with zero product knowledge and a junior developer

Company

Winn.ai - AI-Powered Real-Time Sales Assistant Platform

Introduction

AI-powered real-time sales assistant that joins virtual meeting and helps sales reps focus more on customers by reducing administrative tasks:

Detecting customer answers during calls

Immediately surfaces relevant information for salespeople and updates CRM systems

Breaks down captured data into different sales methodology fields (e.g. MEDDICC, BANT)

Provides prompts from sales playbooks to keep meetings on track

Improves productivity by automating note-taking and follow-up actions.

Outcome

TIME TO CRM: 20 min → 4.5 min with Winn.ai
FILL RATE: 7% → 63% with Winn.ai
PLAYBOOK ADOPTION: 66% → 82% with Winn.ai

TIME TO CRM:
20 min → 4.5 min with Winn.ai
FILL RATE:
7% → 63% with Winn.ai
PLAYBOOK ADOPTION:
66% → 82% with Winn.ai

Team

Product Designer, PM - Danielle Cheban, Frontend Engineer, Backend Engineer

Role

UX/UI Design, Cross-team Collaboration

Duration

3 weeks

Tools

Figma, XD, Miro

Day 1: Just Another Startup Tuesday

The Perfect Storm Situation

The Perfect Storm Situation

I arrived at Winn.ai for my first day, walking into what would become a delightful moment.

"We need a sales dashboard," the Product Manager explained. "It's been announced to customers, the VP Sales is expecting it, and you have three weeks to design and deliver it. Oh, and we haven't started designing it yet."

My reaction? Classic startup situation.

The Reality Check:

  • 3-week hard deadline with customer commitments already made

  • Zero product knowledge - this was literally day one

  • Dashboard design hadn't even begun

  • Junior developer on his first professional job as my only frontend resource

  • "Research" = sketched wireframes and sticky notes

  • Multiple stakeholders with conflicting needs (VP Sales, Sales Ops, Sales Managers)

Nothing is impossible and I was the only designer.

The Stakes: Customer expectations were set, sales operations were waiting, and failure wasn't an option.

Business Context

Battlefield

Winn.ai's AI sales assistant was competing in a crowded market against established players like Gong.io, Fireflies.ai, and Avoma. While competitors offered post-call summaries with 5-60 minute delays, Winn.ai's unique value proposition was real-time insights during live calls with instant CRM synchronization.

But we had a problem: proving our value.

Challenge

Sales operations teams were drowning in post-meeting paperwork, spending an average of 20 minutes per call on administrative tasks. Industry benchmark showed the best solutions could reduce this to 4.5 minutes.

We claimed we could reduce it to zero.

Mission

  • Prove our competitive advantage with measurable data

  • Demonstrate ROI to existing customers

  • Enable sales managers to track team performance and optimize playbooks

  • Show real-time efficiency gains vs. competitor delays

Metrics

For Customers:

  • Increased team performance through better playbook adoption

  • Reduced time-to-CRM (targeting 0 minutes vs. 4.5-minute industry benchmark)

  • Faster follow-up email delivery

For Winn.ai:

  • Proof of competitive differentiation

  • Customer retention through demonstrated value

  • Platform to showcase real-time capabilities

Failure Scenario

High time-to-CRM and delayed email follow-ups would prove we were no better than competitors charging similar prices.

Technical Reality

This dashboard would be built completely from scratch - new backend aggregations, new frontend interface, new data visualization infrastructure. Everything had to work perfectly in three weeks.

This dashboard would be built completely from scratch - new backend aggregations, new frontend interface, new data visualization infrastructure. Everything had to work perfectly in three weeks.


The Challenge + Early Iterations

The Design Nightmare Unfolds

The Design Nightmare Unfolds

The PM's "preliminary research" consisted of:

What I Actually Got

  • Sticky notes with vague requirements

  • 6 key metrics identified: Time to CRM, CRM fill rate, Time to email, Email send rate, Playbook adoption, Talking point usage

  • A paper sketch that looked more like abstract art than a dashboard

  • Zero technical specifications

  • Zero user personas

  • Zero understanding of data structure



StakeholderS Chaos

Each stakeholder required completely different things:

  • VP Sales: High-level executive view, quarterly trends, team comparisons

  • Sales Ops: Operational metrics, drill-down capabilities, administrative controls

  • Sales Managers: Individual rep performance, coaching insights, daily actionable data

What was "highly insightful" for the VP was "completely redundant" for Sales Managers. What Sales Ops needed was "way too detailed" for executives.

The Breakthrough Decision

After spinning our wheels for a week trying to please everyone, I made a strategic call: Create one concept that would be suitable for all layers with small changes, but start with Sales Managers first.

This meant designing a flexible foundation that could scale up for executives and drill down for operations, while prioritizing the daily users who would make or break adoption.



Rapid Design Evolution: 72 Hours, 3 Iterations

With only 3 weeks total, I had to move fast.
To align the dashboard with real-world needs, I conducted daily 20-minute conversations with our 3 internal sales managers and director who actively used the Winn.ai system. I focused on understanding how a dashboard would help them, identifying the most important metrics, and mapping their real workflow after analyzing dashboard data. Since they were actual users of our system, their feedback was invaluable for understanding practical needs rather than theoretical requirements.
Three iterations in three days.

Iteration 1: The Focused Start

  • Clean metric cards at the top

  • Horizontal bar charts for easy scanning

  • Simple meetings visualization

  • Playbook adoption as bubble chart



Iteration 2: The Simplification

  • Added more visual variety with pie charts and bubble clusters

  • Enhanced playbook adoption visualization

  • More sophisticated data presentation

  • Better team comparison views



Iteration 3: The Focus

  • Comprehensive data tables added

  • Multiple chart types for different insights

  • Maximum information density

  • Full feature exploration

  • Key decision: We didn't include the playbook usage widget on the main dashboard, but recognized its value. The plan was to add it as a drill-down feature in the next version .



Final Version: The Reality Check

  • Major pivot: Highly-rated playbook usage widget moved to drill-down

  • Visual compromise: All fancy graphs replaced with simple column charts

  • Constraint win: Everything fits above the fold without scrolling

  • Personal touch: Added the playful mascot hands to bring some personality to the interface

    Visual compromise: All fancy graphs replaced with simple column charts based on user feedback. The complex visualizations were less intuitive - while they might suit the VP's analytical needs, they were definitely redundant for sales managers and sales ops who needed quick, actionable insights. Stakeholders agreed with this simplification.



The Developer Partnership

With a junior developer on his first job, I had to become a teacher while designing. I taught him how to read Figma specifications and extract assets efficiently, then optimized our development process with structured handoffs for rapid iteration. As the deadline approached, our final sprint involved pair programming sessions where I sat with him to ensure we hit our target. The reality of our timeline was that design took just 3-4 days, while development consumed the remaining 2.5 weeks with small PM-driven changes throughout. The breakthrough came from treating him as a partner rather than just an implementer - this collaborative approach made all the difference in our success.

Process & Stakeholder Navigation

The Elegant Solution

The Elegant Solution


The Elegant Solution to Stakeholder Chaos

With no time for traditional UX process, I developed a rapid decision framework to cut through the chaos

1) Does it serve the daily user (sales manager)?
2) Can we build it in time?
3) Does it prove business value?

Rather than building three different dashboards, I found a way to satisfy everyone with one flexible design:

The "User vs. Team" Strategy: For VP Sales and Sales Managers, I created exactly the same dashboard with one crucial difference - where Sales Managers saw "USERS" (individual rep data), the VP saw "TEAMS" (aggregated team data). Same interface, different perspective. Each manager saw their version perfectly tailored to their needs.


This lens kept us focused when stakeholders suggested feature creep and ensured every design choice moved us toward our core objective.

For Sales Ops, I made targeted adjustments - removed the meetings widget and customized other widgets to show their specific operational information.

Decision-Making Framework

With limited time and competing demands, we used a simple but effective criteria for feature prioritization:

  1. Business strategy alignment - what was a killing feature for our competitive advantage?

  2. Technical feasibility - what could our backend aggregations actually deliver in the given timeframe?

The Decision Trio: Major calls were made collaboratively between myself, the PM, and the company director (who brought valuable sales field experience to the table). This kept decisions grounded in both user needs and business reality.

Validation Approach

We didn't need traditional validation testing in this case - this was a startup environment with performance systems already in place. We could see the dynamics and impact ourselves in real-time, allowing for immediate course corrections based on actual usage patterns rather than theoretical testing scenarios.

Results & Impact

Delivery Success


Delivery Success


20 min | 4.5 min

20 min | 4.5 min

TIME TO CRM
WITHOUT | WITH WINN.AI

TIME TO CRM
WITHOUT | WITH WINN.AI

7 % | 63 %

7 % | 63 %

FILL RATE
WITHOUT | WITH WINN.AI

FILL RATE
WITHOUT | WITH WINN.AI

66 % | 82 %

66 % | 82 %

PLAYBOOK ADOPTION
WITHOUT | WITH WINN.AI

PLAYBOOK ADOPTION
WITHOUT | WITH WINN.AI


The Elegant Solution to Stakeholder Chaos

We shipped on time. Three weeks from zero to live dashboard, with a junior developer, under impossible constraints. The fact that we delivered at all was a success.

Technical Achievement

  • Built complete dashboard infrastructure from scratch

  • Implemented backend aggregations for real-time data

  • Created responsive, multi-stakeholder interface

  • Zero post-launch critical design bugs

The dashboard's role

By showing real-time playbook adoption during calls and CRM update tracking, the dashboard created team discipline around these processes. Sales managers could now see exactly who was following procedures and intervene immediately when needed.

User Response

Sales managers responded positively to the dashboard's ease of use and clarity in presenting complex data. The tool's seamless integration into their workflows significantly enhanced their ability to track playbook adoption and make data-driven decisions.

Key User Wins

  • Effortless metric tracking - managers could monitor team performance at a glance

  • Actionable coaching insights - real-time playbook adoption data enabled targeted interventions

  • Workflow integration - the dashboard fit naturally into daily management routines

Business Impact

Competitive Advantage Proven

  • Demonstrated our zero-minute time-to-CRM vs. industry benchmark of 4.5 minutes

  • Showcased real-time capabilities against competitors' 5-60 minute delays

  • Provided concrete ROI data to justify platform investment

Strategic Value

  • Enabled sales managers to optimize playbook adoption across teams

  • Created foundation for data-driven sales coaching

  • Established metrics framework for ongoing performance improvement

Knowledge Transfer Success

The junior developer went from Figma-illiterate to confident dashboard implementer in three weeks. The pair programming approach didn't just ship the product - it built internal capability for future iterations.

Lessons Learned

What Worked

  • Single flexible design serving multiple stakeholder needs

  • User vs. Team perspective strategy

  • Developer partnership approach

  • Ruthless prioritization based on business impact

What We'd Do Differently

Continuous user feedback is guiding ongoing improvements, with plans to add the drill-down playbook usage widget and enhanced filtering capabilities in Phase 2.

20 min | 4.5 min

TIME TO CRM
WITHOUT | WITH WINN.AI

7 % | 63 %

FILL RATE
WITHOUT | WITH WINN.AI

66 % | 82 %

PLAYBOOK ADOPTION
WITHOUT | WITH WINN.AI

66 % | 82 %

PLAYBOOK ADOPTION
WITHOUT | WITH WINN.AI

7 % | 63 %

FILL RATE
WITHOUT | WITH WINN.AI

20 min | 4.5 min

TIME TO CRM
WITHOUT | WITH WINN.AI

Future Vision & Next Steps

Phase 2: Expanding Capabilities

Phase 2: Expanding Capabilities

The successful Phase 1 launch proved the concept and established user trust. Now we can build on that foundation with more sophisticated capabilities.

Planned Enhancements

  • Deep dives into individual metrics - allowing managers to drill down from high-level trends to specific performance details

  • Actionable recommendations tailored to areas of improvement - AI-powered insights that suggest specific coaching actions

  • Heatmap visualization of playbook adoption for trend analysis - visual patterns to identify adoption bottlenecks

  • Benchmarking insights based on customer industry - contextual performance comparison across verticals

  • Expanded dashboards for team leads and sales reps - democratizing data access across the sales organization

Strategic Evolution

These enhancements will offer a more comprehensive view, further supporting data-driven coaching and decision-making at all levels. The goal is to transform from a reporting tool into an intelligent coaching platform that not only shows what's happening, but recommends what to do about it.

Learning-Driven Roadmap

Each planned feature addresses specific gaps identified during Phase 1 user feedback sessions. We're not adding features for the sake of complexity - we're solving real problems that emerged once users started working with the dashboard daily.

The vision

Transform Winn.ai's dashboard from a performance monitor into a sales optimization engine.