Forecast

UX/UI and User Research

Forecast is a predictive cash flow tool for Wells Fargo small business customers to analyze the week ahead and gain insights about their business.

Overview 

Wells Fargo engaged Fahrenheit 212 to develop ideas that solved an unmet need for small business owners while creating cross-selling and up-selling opportunities for the bank. I’ll focus here on the designed outcome and the iterative process used to arrive at this validated concept recommendation.

Persona Development

Wells Fargo’s existing data on small business owners covered a breadth of demographic data points, but lacked realistic motivations, needs and emotional qualities which are often the dynamics that hinder or boost the adoption of a new tool.

Based on qualitative research conducted via online forums as well as intimate group conversations with customers, we developed 6 core personas. Psychological factors like perceived level of control, relationship to their business and foundational motivations were distilled into a group of mindsets. In turn, personas provided fertile ground for developing a broad range of notional ideas.

Ideation Workshop

Collaborating with stakeholders to understand and challenge their domain insights is incredibly valuable. We used a workshop setting to share a wide range of initial one-page concepts, gather direct feedback, do real-time sketching and conduct sense making exercises. During the workshop it’s more about curiosity and debate, but stepping back and assessing the workshop’s output allowed us to shape the first set of concepts to kick off the more design heavy testing phase.

Borrowing from the Google Venture's sprint methodology, I collaborated with a team of creative and business strategists to narrow to a validated concpet over the course of 4 cycles, 5 days each.

Learning Gameboard

Problem

What problem does the product solve?

Experience

What is the primary use case?

Features

What core features are required?

Personality

What does the interaction feel like?

Credibility

How credible is this idea coming from a bank?

Perceived Value

How does the product drive willingess to pay?

Business Value

How does the product lead to cross-selling and up-selling opportunities?

Sprint
01

Narrowing to the right ideas

We designed our first experiment to evaluate a set of 8 concepts. We crafted one page value propositions with realistic copy and faux product branding that made it feel like the hard part of the product development had already been finished. Pitching the top-line value and highlighting a few core features was all that we needed to gauge whether ideas were worth pursuing.

Core Experience Iteration

For the second and third sprints we drilled into the core user story and built prototypes to bring the core features to life. These rounds of testing were invaluable to tweak the product based on real user needs and concerns.

For example, we learned that consumers will trust the tool’s predictive output if they can see the data going in and how it’s being calculated. To answer this we showed how known transactions and predicted data based on historical averages factor in, and allowed users to adjust inflows and outflows for the coming week. 

Sprint
02-03

Sprint
04

Pivoting to Mobile

A key learning from sprint 3 informed our choice to move the experience prototype into a mobile context. It turns out that digging into historical data provided intriguing insight, but small business owners tend to already know the big patterns of their business. What they really need is predictions that are more actionable on a daily basis. 

Additionally our previous iteration presented a mix of emotional and objective takeaways. For our final prototype we reduced to clearly stated 7-day cash position, which brough a much needed focus to the interface.

7-day Rolling Forecast

The primary feature states a clear cash position 7 days into the future and is supported by a projected cashflow module.

Insights and Solutions

Users historical data is used to support key insights, which link directly to other product offerings.

Quick Input Cards

The forecast is only as strong as the data that feeds it, so necessary manual inputs are designed to feel quick and easy.

I’d definitely try this out, since I’m already doing all of this but it’s just in my head.  It’d be great to see it on screen.  I really like the insights, maybe suggest an appointment for a Money Manager or extension on business credit?  That’s the spot to do it and I would look into it.

— Research Participant, Sprint 4