Simplr

SaaS Platform Architecture & Lifecycle Intelligence Ownership

Platform Architecture & Product Ownership

Held end-to-end ownership of the Simplr SaaS platform, spanning product definition, platform architecture, and operating constraints
Defined system boundaries, data models, and lifecycle stages to support scalable, multi-tenant usage

Lifecycle Automation & Intelligence

Owned customer lifecycle logic across onboarding, feedback capture, sentiment analysis, and churn-risk detection
Defined automation rules and data flows designed to surface actionable insight rather than raw feedback

Governance, Data & Commercial Accountability

Established data governance, access control, and reporting standards to protect insight integrity
Took responsibility for prioritisation decisions, including pausing further development to focus on higher-impact platform ownership work

Overview

Simplr was conceived as a SaaS platform designed to help B2B and wholesale organisations capture customer feedback, analyse sentiment, and identify retention risk through automated lifecycle intelligence. I held full ownership of the platform from concept through technical validation. Responsibility covered platform architecture, lifecycle design, automation logic, data governance, and reporting standards. The work progressed through core build and validation phases, establishing a robust technical foundation and proving feasibility. Following this phase, I made a deliberate decision to pause further development in order to prioritise higher-impact platform ownership responsibilities within active organisations. Simplr remains a validated, future-ready platform architecture, retained as a reference system for product-grade lifecycle design and data intelligence.

Client

Simplr

Project Date

2024

Category

SaaS Platform & Lifecycle Ownership

Challenge

Many B2B organisations collect customer feedback but lack the systems to translate it into timely, actionable insight. Feedback is fragmented across tools, sentiment analysis is manual or inconsistent, and retention risk is often identified too late to intervene.
The challenge was to design a platform that could automate feedback capture, interpret sentiment at scale, and surface meaningful risk signals without introducing operational overhead or unreliable data.

Impact

Validated a scalable SaaS platform architecture and lifecycle model.
Established automated feedback and sentiment analysis workflows.
Demonstrated feasibility of proactive retention-risk identification.
Created a reusable, governed foundation for future productisation.

Solution

The solution was to design Simplr as a governed SaaS platform rather than a survey tool. This required clear ownership of platform architecture, lifecycle stages, automation logic, and data standards from the outset.
Lifecycle triggers were defined to automate feedback collection, sentiment interpretation, and insight surfacing at key customer moments. Data models and access rules were established to ensure insight accuracy, while reporting outputs were designed to support decision-making rather than vanity metrics.
By retaining ownership of system boundaries and operating constraints, Simplr was built as a scalable intelligence layer capable of integrating into existing business workflows.

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Homepage of Simplr, featuring AI-powered wholesale intelligence tools with a call-to-action for a free trial.

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