Designing a Unified Marketing Operations Dashboard

Designing a Unified Marketing Operations Dashboard

Designing a Unified Marketing Operations Dashboard

Designing a Unified Marketing Operations Dashboard

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, Frontend Engineer, Backend Engineer

Role

UX/UI Design, Cross-team Collaboration

challenge

challenge

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.

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.

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.

А problem: proving our value.

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 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

solution

solution

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.

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.

design

design

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.

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.