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SmartBank Business: from near-zero retention to product–market fit signals

Smart Bank • 2024

SmartBank Business is a B2B product designed for business owners and accountants, covering daily financial operations.

Despite having a wide range of features, the product was not becoming a core tool for users and failed to deliver consistent value.

Context

At the time I joined, the product was already live but showed weak performance:

  • users signed up but did not return;
  • key flows were underused;
  • engagement remained low;
  • the product was used only for occasional banking tasks.

In practice, it existed — but was not part of users’ daily workflow.

Problem

The core issue was not missing functionality, but lack of perceived value.

This showed up in metrics:

  • daily retention was close to zero;
  • DAU was significantly below expectations;
  • users did not reach key scenarios;
  • time-to-value was too long;
  • usage was episodic, not habitual.

Additionally, the product often misrepresented its own value.

For example, all account types (operational, card, deposit) were displayed as a single balance. This created false expectations and reduced trust, since not all funds were actually available.

Opportunity

The opportunity was clear:

If users could quickly understand and access value, it would be possible to:

  • significantly improve retention;
  • reduce time-to-value;
  • increase engagement and frequency of use;
  • drive upgrades to higher-tier plans.

My Role

I led the effort to fix product metrics and redefine how the product was developed.

Responsibilities included:

  • identifying root causes behind metric drops;
  • running full-cycle discovery;
  • redesigning activation and key flows;
  • reshaping product strategy;
  • aligning stakeholders and teams;
  • introducing a data-driven product approach.

What I Did

Ran full-cycle discovery

Started with deep analysis:

  • user session reviews;
  • identifying behavioral patterns;
  • in-depth interviews with business owners and accountants;
  • mapping real usage scenarios.

This made it clear where and why users dropped off.

Rebuilt activation as the core growth driver

Shifted focus to activation as the primary lever:

  • defined real product value;
  • analyzed how users perceived it;
  • identified key entry points and scenarios;
  • formulated the Aha-moment;
  • redesigned JTBD and user journeys;
  • rebuilt onboarding and activation flow;
  • reduced time-to-value.

Activation became a growth system, not just an onboarding step.

Simplified and clarified user experience

Removed major friction points and confusion.

A key example:

  • separating account types and fixing balance representation.

This improved trust and made the product behavior more transparent.

Also redesigned flows and product structure to bring value closer to the user and reduce friction.

Introduced a data-driven product approach

Before this, decisions were often made without validation.

I introduced:

  • metric-driven decision making;
  • hypothesis validation;
  • continuous discovery;
  • structured experimentation.

This changed both the product and how the team operated.

Improved the product through iterative changes

Alongside major changes, the product evolved through:

  • targeted UX fixes;
  • optimizing key scenarios;
  • removing friction step by step.

This helped build a more consistent and usable experience.

Challenges

The main challenge was not just improving the product, but changing how it was built.

It required:

  • introducing product thinking from scratch;
  • shifting decision-making to data;
  • changing team mindset;
  • replacing intuition-based decisions with validated hypotheses.

This was a transformation of both product and team.

Results

The impact was significant:

  • retention increased from ~5% to ~34%
  • time-to-value decreased substantially;
  • repeat usage increased;
  • more users upgraded to higher-tier plans;
  • share of paying users increased;
  • the product began showing product–market fit signals

Additionally:

  • users found value faster;
  • the product shifted from occasional use to a regular tool;
  • activation and engagement metrics became more stable.

Why This Project Matters

This project is about working at the level of user behavior.

It shows that growth is not driven by features, but by:

  • how quickly users reach value;
  • how clearly the product communicates its purpose;
  • how well it fits into real user workflows.

It combines:

  • product thinking;
  • data-driven decisions;
  • deep user understanding;
  • and direct business impact.

This is the type of work where product decisions directly translate into growth.

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