Topvisor is a suite of SEO and analytics tools built for agencies and professionals. I led the end-to-end design of a brand new Competitor Research Tool, conceptualized and built from scratch as a flagship addition to Topvisor’s SaaS platform. Unlike other modules I had redesigned previously, this was a greenfield project — requiring foundational UX strategy, design system alignment, and user-driven discovery to bring the tool to life.

The goal was to create a competitive analysis product that empowers users to identify and analyze their SEO and PPC competitors across search engines — quickly, visually, and without overwhelming complexity.

User Research

To ensure the tool addressed actual user pain points, I initiated a lean discovery phase using Jobs-To-Be-Done (JTBD) and design thinking principles:

• Conducted 5 in-depth interviews with SEO consultants and in-house marketers

• Mapped their workflows and data needs using journey mapping

• Ran UX audits of competitors (Ahrefs, SEMrush, SpyFu) to identify opportunities for differentiation

• Facilitated wireframe co-creation sessions to validate information hierarchy and insight relevance

Using affinity mapping, we synthesised feedback into actionable design goals. This led to the definition of two core personas:

• Agencies and consultants who need fast, visual insights for clients

• In-house teams seeking structured, reliable reporting tools

Key Outcomes:

• De-scoped features using MoSCoW prioritisation, reducing time-to-market

• Persona needs directly informed tool architecture and feature flow

• Prototype usability success rate increased from 57% → 92%

Goals

This wasn’t just a visual UI challenge — users needed to uncover real competitors based on SERP behavior, shared keywords, and ad visibility, across engines like Google and Yandex. From a business perspective, this tool needed to:

• Increase product stickiness and user retention

• Drive upgrades by expanding perceived value of the Topvisor suite

• Provide new monetisable insights not available in legacy modules

Product Design Strategy

We used Lean UX and RICE prioritisation to manage velocity and business value. The foundational design strategy focused on clarity through progressive disclosure, exposing the right insights at the right time without overwhelming users.

The interface emphasised:

• SERP-based keyword clustering, grouping domains by real-world visibility patterns

• Preview cards of real search results, enriched with organic and ad placements

• Color-coded visual tables and compact filters for engine/device/context — all scoped to avoid global resets

Deep Thinking Workshops

As this was a greenfield project, I ran collaborative deep thinking workshops to ensure we were building the right product, not just the right UI:

• Information architecture mapping to define the base hierarchy of competitor analysis

• Priority flows to identify what insights matter most and in what sequence

• Card sorting to validate mental models and reduce decision fatigue

• Scenario-based design to simulate real-world consultant use cases

These led to critical decisions like:

• Keyword clusters as the primary lens

• Filtering scoped per context rather than global

• Pre-configured quick reports based on user goals

  
  

Report Anatomy

I designed a modular report structure that allowed users to:

Build and export structured reports without formatting manually

Analyse graphical data, tables

Filter and view report on user's terms

And do it all on the mobile as well

Outcomes

Competitor Research Tool launched as a net-new product within Topvisor

• Activation rate exceeded targets within the first 60 days

• Support tickets related to competitive insights dropped significantly

• Self-reported confidence and clarity increased based on post-launch interviews

• Task completion success rate jumped from 57% to 92% in final usability tests

Reflection

This project was a rare opportunity to bring a brand-new SaaS product to life from zero. It confirmed my belief that enterprise-grade tools don’t have to be intimidating — clarity, prioritisation, and empathy can turn dense data into decisive insights.

By anchoring design decisions in real user workflows and leveraging frameworks like JTBD, RICE, and Lean UX, we were able to deliver a product that was not only technically robust, but also user-loved and adoption-ready.