Sushma Padmanabhan

TaxOKPlease brought taxpayers together to a platform where they could choose which tax professional they wanted to file their tax returns with. The tax professionals were advertised along with their areas of expertise, ratings, and reviews from other tax filers.

The offering solved pain points for two sides of the chain:
• Chartered accountants (CAs) and tax preparers: Along with their photos and profiles, it gave tax preparers a platform to showcase their area of expertise, specifically in India, where the tax preparers cannot self-advertise. This platform used crowdsourcing and ML algorithms to showcase CAs in a specific area based on their area of expertise, ratings, and reviews.
• Taxpayers searching for a trusted CA to prepare their tax return and looking to have their own choice rather than being forced to go with the company-appointed accountants. The platform allowed them to review the ratings of CAs in their locality or area based on peer feedback.

Led a startup that offers a marketplace for accountants and tax preparers to find easy, trustworthy partnerships to prepare their individual tax returns in India.

In India, chartered accountants rely on word of mouth or advertising for getting new clients due to the official authority rules. On the other hand, tax preparers have to rely on locally available chartered accountants or rely on their families and friends to refer a CA. This creates more issues for the newer generation of taxpayers who have relocated to metros for work and have no reliable CA to help navigate the unsure waters of taxation.

Hence the idea of a marketplace where the CAs and taxpayers can look up for each other on common grounds along with ratings and reviews using the social media power generated.

Championed and led the Innovation Catalyst community for over 18 months, where I guided 30 IC champions to help impart the design for delight (D4D) principles to internal and external startup communities.

My main charter was to gain visibility across the industry for Intuit as an innovative company and build champions inside the company to promote the D4D principles.

Firstly, I created the who, i.e., an ideal customer persona for a new product. By building data using a top-down approach, total addressable market (TAM), serviceable addressable market (SAM), and serviceable obtainable market (SOM) were developed. To create user journeys, I answered questions about the workflow, how a new product or service would fit into the workflow, and what value it would provide to users. After that, I created the how—a business model for how to sell services and approach the supply and demand side of the problem. Also, the profit value matrix was defined to help formulate freemium and premium content by providing industry examples.

Additionally, the project involved identifying key metrics using the AARRR funnel, creating a competitive advantage by comparing the closest competitor across several dimensions, creating a release schedule with the Gantt chart, and formulating and executing a beta testing plan. I operationalized a decision-making process that included creating the DACI and setting up a process for deciding for the steering group via stakeholder meetings, communication channels like Slack, or follow-up clarification meetings. Finally, user stories were written along with acceptance criteria.

I conducted an in-depth analysis of key customer personas and their net promoter scores (NPS). I also investigated existing referral mechanisms and performed a SWOT analysis to benchmark Accointing’s position against competitors. Collaborating with development, UX design, and research teams, we mapped customer journey touchpoints and identified potential referral opportunities. I employed Design for Delight principles to brainstorm and generate innovative ideas for the referral program. Finally, I delivered actionable recommendations, leading to the successful launch of an MVP referral program targeting micro- and nano-influencers in the cryptocurrency space.

• 100% — % of client requirements captured as structured user stories & acceptance criteria.
• All — All scoped features implemented and validated by QA against acceptance tests.

Translating complex AI/ML concepts (RAG retrieval, embeddings, risk scoring, confidence thresholds) into clear, actionable requirements for cross-functional teams in the absence of a live product for validation.

Created structured user stories and acceptance criteria in plain language, simplifying technical logic for engineers, QA, and stakeholders, and ensuring a code-complete MVP ready for pilot launch.

Enabled delivery of a code-complete MVP, with curated datasets and defined integration pathways, positioning the product for pilot launch and future scalability.