Contents

#Overview 1Introduction 2Competitor Analysis

3User Research 4Workshops 5Personas

6Solution 7Final Design 8Conclusion

Intro
Bud Financial sought to leverage Open Banking technology to develop a Customer Segmentation Dashboard, aiming to enable targeted, data-driven marketing campaigns tailored to individual customer needs.

Challenge
The primary challenge involved assessing the feasibility of connecting Bud's extensive customer data pool to the dashboard and converting this data into actionable insights, facilitating the seamless segmentation of customers into precise target groups.

Solution
A dashboard prototype was created to demonstrate how Bud’s technology could enhance customer experiences, increase retention, and drive product growth through strategic, personalised engagement.

1. Introduction

In a competitive financial landscape, banks and financial institutions needed solutions to deliver personalised experiences tailored to their customers' unique needs. Beyond simply identifying the right customers for the right products, banks aimed to:

Increase conversion rates in marketing campaigns by ensuring that efforts target only those customers with genuine interest and need for specific products.
Increase the revenue generated per customer by building customer retention and loyalty.
Be known as a bank that truly understands their customers and cares about what they really want.

Bud Financial aimed to address this by developing a Customer Segmentation Dashboard powered by Open Banking technology, designed to help banks gain deeper insights into customer behaviour and anticipate product needs with precision.

The project sought to enable data-driven marketing campaigns that delivered relevant products to customers at ideal times, enhancing engagement and satisfaction. By integrating Bud’s technology into a streamlined, accessible dashboard, marketing teams would be empowered to leverage transaction data insights to build stronger customer relationships. This solution would ultimately improve customer retention and encourage growth, positioning Bud Financial as a leader in innovative, customer-focused banking technology.

A recent IBM study revealed that over 25% of respondents were open to having their transaction data used to enhance personalisation, with nearly 50% of respondents aged 18-34 expressing a willingness to leverage technology to improve their banking interactions (see source here).

2. Competitor Analysis

In evaluating user segmentation tools for best practices and inspiration, several platforms with advanced analytics and in-app experience-building capabilities were reviewed. The top three tools considered: Userpilot, Amplitude, and Baremetrics, each offered unique features relevant to segmentation and customer insights.

Userpilot

Userpilot was a powerful platform designed to optimise user engagement and satisfaction. Its tools enabled product teams to monitor behaviour, create tailored in-app experiences, and gather actionable insights through advanced analytics. By facilitating customer segmentation, survey collection, and feature tagging, it empowered teams to enhance user experiences and achieve business goals.

Pros

Feature Tracking: Tracked product usage to monitor how users interacted with features.
In-App Guidance: Enabled the creation of guided in-app experiences to improve onboarding and feature adoption.
Feedback Collection: Collected user feedback through survey builders and NPS surveys for better satisfaction insights.
Advanced Segmentation: Supported detailed customer segmentation using multiple criteria for targeted analysis.
Behavioural Actions: Tagged features and triggered actions based on user behaviour for enhanced engagement.
Goal-Oriented Analytics: Offered analytics focused on tracking specific engagement or retention objectives.
Tool Integrations: Integrated seamlessly with Mixpanel, Google Analytics, and Kissmetrics for comprehensive analytics.

Cons

Content Maintenance: Required effort to manage and update in-app experiences to ensure relevance.
Learning Curve: Advanced segmentation and feature tagging demanded technical expertise.
Limited Offline Use: Lacked offline functionality for use in restricted environments.

Amplitude

Amplitude was a leading digital analytics tool tailored for SaaS companies, providing deep insights into user behaviour. It enabled teams to track and segment user actions, offering customisable analytics to drive growth and optimise user experiences. Amplitude's robust features allowed product managers to make data-driven decisions, aligning product development with user needs.

Pros

Behaviour Insights: Delivered valuable insights into user behaviour, improving customer engagement.
Event Tracking: Tracked events and enabled bulk filtering to analyse multiple interactions simultaneously.
Flexible Analytics: Offered customisable analytics options for diverse business needs.
User Segmentation: Supported advanced segmentation of users to identify trends and refine strategies.
Actionable Data: Provided data that drove growth and informed product decisions.

Cons

Technical Barrier: Advanced configurations required coding knowledge, limiting accessibility.
Manual Setup: Lacked ready-made templates, increasing setup time for new processes.
Niche Focus: Primarily catered to SaaS companies, limiting versatility for other industries.

Baremetrics

Baremetrics specialised in simplifying customer data analysis, offering a user-friendly platform for segmentation and growth monitoring. It catered to teams with straightforward needs, providing basic tools for categorising customers and assessing trends. While limited in advanced customisation, it remained ideal for teams prioritising simplicity over complexity.

Pros

Basic Segmentation: Offered simple tools for grouping customers by general characteristics.
Growth Monitoring: Provided health checks to track customer growth and emerging trends.
Ease of Use: Focused on simplicity, making it accessible to non-technical users.
Visual Insights: Delivered clear metric visualisations for quick decision-making.

Cons

Limited Features: Lacked advanced personalisation tools compared to competitors like Userpilot.
Restricted Segmentation: Simple segmentation options made it unsuitable for complex analysis.
Fewer Integrations: Offered fewer third-party tool integrations, restricting its broader functionality.

3. User Research

To gain a deeper understanding of user needs and challenges with the Customer Segmentation Dashboard, four users from Bud's marketing team were recruited. These users had prior experience with data platforms such as Google Analytics, Salesforce, and Matomo, which provided valuable insights into their requirements for a dashboard focused on customer segmentation.

In user interviews, expectations, pain points, and feature requests were explored across several key areas. An affinity map was created (shown below), synthesising and organising the gathered insights into four focus areas to address the primary needs and concerns:

Design of the Attributes: Users highlighted that attributes in segmentation should be intuitive and flexible, allowing them to easily adjust filters based on various criteria. Clear labels, consistent naming conventions, and the ability to sort or categorise attributes emerged as significant needs.
Filtering of Conditions: There was a desire for more advanced filtering conditions that allowed for greater precision. This included improved toggle options (e.g., AND/OR logic), better visualisation of nested conditions, and clearer summaries that accurately reflected selected criteria without overwhelming users.
Segments: Users expressed the need for clearer, more actionable segmentation options. They found it challenging to interpret segmented counters and suggested improvements like cascading segments, timestamp integration, and segment descriptions to make the dashboard more insightful.
General User Interface: The interface needed to be more cohesive, with accessible fonts and icons, colour-coded segments, and enhanced consistency in UI elements. Users also requested more visualisation options to help interpret data at a glance and preferred a first-person platform perspective for improved usability.

Affinity Mapping

4. Workshops

As part of the development process for TotallyMoney's integration of Bud's Open Banking technology, workshops played a critical role in shaping the tool's features and ensuring they met the needs of the target users. The same group from the initial user research participated in these workshops, providing additional insights, defining personas, and refining the feature list. This approach ensured that the new financial tool would be both practical and user-friendly.

The Miro board below is an example session where the functionality of creating a subset of customers based on search criteria that aligned with their financial behaviour was explored. A potential persona was developed, representing a user who needed to export financial data about customers into the existing CRM tool. This would enable the identification of current savings, ISA, and LISA account holders for targeted marketing efforts.Miro

User Story Mapping

5. Personas

Based on insights gathered from both user research and workshops, two key personas were developed to represent typical users of the Customer Segmentation Dashboard (shown below). These personas guided design decisions by aligning the dashboard functionalities with the diverse needs of both entry-level and senior marketing users. This approach ensured that the Customer Segmentation Dashboard was tailored to be effective for a wide range of marketing roles, addressing the specific requirements of each user type.

Helen Slater - The Rookie Marketer

“ I just want a tool that helps me get things done without feeling like I have to figure it all out first. Clear labels and easy filters would save me so much time. ”

Profile

Fresh graduate, recently hired into her first marketing role.
Enthusiastic, eager to learn, and determined to excel in her job.
Strives to impress her boss and advance her career.

Pains

Struggles with unintuitive features when building marketing campaigns.
Faces challenges in creating customer segments effectively.
Frustrated by the lack of clear attribute labels and flexible filter options.
Experiences friction in her workflow due to a complex interface.

Goals

Wants to quickly learn and navigate marketing tools to improve efficiency.
Aims to build more targeted campaigns with ease.
Seeks to impress her boss by delivering successful marketing initiatives.

Solutions

Simplifying the user interface would allow Helen and other entry-level users to quickly grasp the dashboard’s functions, improving their productivity and reducing frustration.

Requirements

Wants to efficiently complete marketing tasks, gain a deep understanding of customer behaviour, and enhance her skills in her new role.

Outcomes

With a more intuitive interface, Helen can complete tasks faster, reducing errors and improving job satisfaction. This will allow her to make better-informed decisions and contribute effectively to the team's goals.

John Wills - The Seasoned Marketing Manager

“ I need a system that works as fast as I do, so I can focus on leading my team and delivering results. ”

Profile

He is a senior marketing manager with over 20 years of experience.
Responsible for managing a large team and overseeing marketing campaigns to meet key performance indicators (KPIs).
Faced with high expectations and limited time, John needs a reliable, user-friendly system to monitor data and team activities.

Pains

Frustrated by inconsistencies in feature functionality.
Struggled with a lack of intuitive options for verifying marketing segments.
Time constraints added pressure to ensure campaigns were efficient and effective.

Goals

Maintain a clear overview of his team's performance.
Ensure data is easily accessible for quick decision-making.
Enable detailed analysis of campaign performance without friction.

Solutions

A streamlined interface with advanced filtering and segment summaries would help John quickly review performance and make decisions without the frustration of unintuitive features.

Requirements

John needs a system that offers clear, intuitive features for quick access to relevant data, enabling fast decision-making and efficient team management.

Outcomes

These improvements would streamline John’s workflow, helping him meet KPIs, track data more effectively, and boost team productivity and confidence in results.

6. Solution

After organising these insights, potential solutions were brainstormed to address the identified needs. Using prioritisation frameworks, including an Impact/Effort Matrix and a MoSCoW Matrix (shown below), key features were identified for initial focus in prototyping and testing. Priorities were categorised as follows:

Must-Have Features: Critical elements such as the redesigned segmented counter, AND/OR toggles, new segment categorisation options, and condition-based attribute filtering were inspired by competitor features in Userpilot and Amplitude, where similar tools streamlined complex filtering and segmentation.
Should-Have Features: Enhancements to the calendar UI, segment editor access post-creation, and a refined drag icon were considered important for usability. These ideas were drawn from Amplitude and Baremetrics, which provided smooth, user-friendly navigation in their dashboards, enhancing interaction and functionality.
Could-Have Features: Lower-priority items like clickable segments, removal of redundant icons, and additional sort/search functionalities were derived from optional, advanced tools observed in Baremetrics. These features allowed for a deeper data interaction experience but were less critical for core usage.
Won't-Have Features: Features like a "Notes" section and predictive search were excluded at this stage, as they were considered non-essential and infrequently used in competitor platforms. This decision aligned with Helen and John’s core needs, ensuring that the focus remained on functionalities that would directly enhance their workflow and productivity.

Features list prioritised using the MoSCow matrix

7. Final Design

After finalising the initial wireframe sketches, a high-fidelity prototype was created in Figma, featuring all the major screens and core interactions to closely simulate the live app experience.

Key inclusions in the final design were:

Broad Segmentation Categories: The segmentation functionality offered a wide range of categories for users to choose from. Users could also create custom segments, enabling them to segment customers by products, such as credit cards, loans, or mortgages, as well as by bank eligibility criteria. This flexibility aligned with Helen’s goal of understanding customer demographics and John’s focus on KPI tracking.
Segmented Counter and Condition-Based Filtering: The segmented counter and advanced filtering options with AND/OR toggles allowed users to customise and refine data segments intuitively. These features addressed Helen’s need for ease of use and John’s demand for efficiency in managing complex data.
Refined Drag Icon and Intuitive Navigation: A refined drag icon and an improved navigation flow ensured that users could interact with the interface seamlessly, inspired by usability elements observed in competitor tools like Amplitude and Baremetrics.
Clickable Segments and Additional Search/Sort Functionalities: Although lower in priority, clickable segments and advanced sorting options were included to provide a deeper data interaction experience, enhancing John’s oversight capabilities.

This prototype was built to provide a realistic, interactive experience for users, allowing them to navigate through the core functions and understand the flow and feel of the app.

Please click the link below to see the prototype in action.

Prototype

Customer Segmentation Dashboard - final design

8. Conclusion

This project provided valuable insights into the challenges of implementing subtle yet impactful changes to an existing product. Through careful consideration of user needs and iterative testing, the project successfully introduced improvements that enhanced both functionality and user experience. Key takeaways included a deeper understanding of data-driven design and the positive reception from clients, which affirmed the project’s value in meeting real-world needs.

For future iterations, expanding the product's capabilities could further empower marketing teams. Ideas for future development include:

Standalone Dashboard: A dedicated tool allowing marketing teams to query databases with customisable fields, complementing their CRM and marketing tools.
CRM Integrations: Direct integration with CRMs like Salesforce and Hubspot, enabling seamless enrichment of transaction data with marketing-specific insights.
Support for Additional Products: Broaden the product range to go beyond loans, mortgages, and credit cards by incorporating a diverse selection of financial and insurance offerings, including:
- Home Insurance
- Car Insurance
- Gadget Insurance
- Holiday Insurance
- Life Insurance
- Concierge Services
- Savings Accounts
- Investment / Wealth Accounts
Predictive Customer Attributes: Enhancing customer profiles with predictive attributes, offering marketing teams insights into the likelihood of customer interest in specific products.
Data Visualisation Features: Integrate advanced data visualisation tools to represent key metrics and insights visually. This feature will enable marketing teams to quickly grasp complex data, identify trends, and make informed decisions.
Bud Product Marketing Insights: Providing data-driven insights to drive engagement with Bud’s own products within client systems.

These potential features would help solidify the product as a comprehensive tool for marketing teams, making data more accessible and actionable across a broad range of use cases.