Switch
& Save
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
overhead title
Detail
overhead title
Detail
overhead title
Detail
overhead title
Detail
Context & problem statement
Context
A large majority of users carry over balances on their credit cards, often paying high interests on this debt.
We’ve calculated that we could help save ~£200M across our users if they switched their credit cards to balance transfer cards available in our marketplace.
Users don’t currently know how much they could save with a balance transfer card and so are less motivated to switch.
Problem statement
Who has the problem ...
Users with outstanding credit card balances.
What is the problem ...
They pay high interest and don’t realise they could save by switching to balance transfer cards.
When/where does the problem occur ...
When managing credit card debt and browsing the marketplace.
Why is it important to address for the customer ...
They miss out on potential savings and lack motivation to switch.
Existing relevant insights
- Over 231,000 users could save £576 on average by switching to a balance transfer card.
- Previous optimisations around ‘switching and saving’ have performed well.
- Personalised messaging always outperforms generic messages
Goals & Objectives
User value goals
- Delivering real savings by helping users reduce interest payments.
- Educate users on balance transfer benefits.
- Highlight personalised savings for users.
Business value goals
- Increasing card conversions from the marketplace.
- Boost engagement with balance transfer offers.
Success metrics
Metrics are measured against analytics from the live app.
Percentage of users that apply from the new product list page
Success
> 10%
Ok
7-10%
Fail
< 7%
Percentage of eligible users that start the new journey
Success
> 10%
Ok
7-10%
Fail
< 7%
Target Audience
Requirements
- Users we predict can save above £100 by switching to a balance transfer card.
- Users with at least a 70% chance of approval for the balance transfer card.
- Users that have revolved a balance for the last 3 months.
- Active & semi-active users (logged in within the last 6 months)
- Users who are not flagged to be on a 0% promotional rate
- Users with credit score above 300.
Personas
ClearScore has 6 personas — 4 of these are a target audience for this project and described below:
Money Maker - Maria
High earner with strong credit, rarely uses ClearScore.
Growth Phase - Grace
Busy working mum, tech-savvy and credit confident.
Mutual Resources - Mike
Older self-employed user, focused on clearing debt, uses ClearScore occasionally.
Deal Seeker - Deepak
Budget-savvy dad, always hunting for savings, uses ClearScore often.
Design Requirements
- Savings Calculation
• Show real-time savings using actual card data (APR, balance, payment).• Only calculate after eligible cards are returned.
- API Integration UX
• Trigger panel search via partner APIs. • Handle delays with smooth loading/progress indicators.
- Pre-condition Logic
• Require Offers flow completion (30-day + credit card). • Integrate into journey as needed.
- In-App Entry Points
• Add entry points from dashboard, cards tab, or credit report. • Target users with card debt or interest.
- Existing credit card input
• Allow editing of card details (APR, balance, payment).
- Results Presentation
• Show savings for top 1, 3, or all eligible cards. • Include APR, terms, eligibility, example. • Link to product pages.
- Unhappy Path
• Fallback if no savings or BT cards. • Suggest next steps or alternatives.
Design stage 1 OF 4
Discover
Our initial problem statement was based on the saving calculation and success of related optimisations. So needed to know users thoughts about switching or why users are not saving on their interest payments.
Assumed Problem Insights
Research Topics Gathering
Research Prioritisation
Importance knowledge matrix
Top Priority Research Topics
Top Priority Research Topics
Top Priority Research Topics
Top Priority Research Topics
Design stage 2 OF 4
Define
We needed to refine the numerous research findings into the most relevant insights and a thorough problem definition to start ideating from.
Unstructured Research Findings
Findings Themes
Key Research Insights
Insight 1
Personalised savings must be made clear and tangible
1. Key Insight
Users are more likely to switch when shown personalised, clear savings.
2. Context
Happens during offer comparison and decision-making.
3. Root Cause
Generic savings don’t feel relevant or motivating.
4. Impact
Users disengage if they don’t see clear benefit.
5. User Goal
Users disengage if they don’t see clear benefit.
6. Recommendation
Show estimated monthly and total savings using real card data.
Insight 2
Educational gaps undermine switching confidence
1. Key Insight
Users hesitate due to confusion about switching steps or terms.
2. Context
Visible early in the journey or while browsing offers.
3. Root Cause
Lack of plain explanations or onboarding guidance.
4. Impact
Motivated users drop off from uncertainty.z
5. User Goal
Feel confident about how switching works.
6. Recommendation
Use visual guides and simple explanations at key touchpoints.
Insight 3
Too many card options lead to decision paralysis
1. Key Insight
Users feel overwhelmed by large lists of similar cards.
2. Context
Occurs during browsing or comparison.
3. Root Cause
Lack of curation or clear ranking.
4. Impact
Leads to indecision and drop-off.
5. User Goal
Quickly find the best match.
6. Recommendation
Show 1–3 top offers by default with the option to explore more.
Insight 4
Confidence in eligibility drives switching action
1. Key Insight
Users apply more when they’re confident they’ll be approved.
2. Context
Appears when reviewing offer lists.
3. Root Cause
Fear of rejection or harming credit score.
4. Impact
Users skip offers, even when eligible.
5. User Goal
Apply only to offers they’re likely to get.
6. Recommendation
Display strong approval signals and explain how they're calculated.
Themes Problem Statements
What the user problem is
Who has the problem ...
ClearScore users with credit card debt who are open to switching but feel uncertain or overwhelmed during the process.
What is the problem...
They can’t easily understand how much they’ll save, feel unsure how the process works, and lack confidence in choosing and being approved for a card.
When/where does the problem occur...
While exploring switching options in the app — particularly during offer comparison, information review, and decision-making.
Why is it important to address for the user...
Unclear value, too many choices, and low confidence prevent users from switching — even when it would save them money and reduce interest payments.
Other Projects
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
If you like what you see
— Don’t be a stranger! ...
o.hardisty@me.com
Switch
& Save
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
overhead title
Detail
overhead title
Detail
overhead title
Detail
overhead title
Detail
Context & problem statement
Context
A large majority of users carry over balances on their credit cards, often paying high interests on this debt.
We’ve calculated that we could help save ~£200M across our users if they switched their credit cards to balance transfer cards available in our marketplace.
Users don’t currently know how much they could save with a balance transfer card and so are less motivated to switch.
Problem statement
Who has the problem ...
Users with outstanding credit card balances.
What is the problem ...
They pay high interest and don’t realise they could save by switching to balance transfer cards.
When/where does the problem occur ...
When managing credit card debt and browsing the marketplace.
Why is it important to address for the customer ...
They miss out on potential savings and lack motivation to switch.
Existing relevant insights
- Over 231,000 users could save £576 on average by switching to a balance transfer card.
- Previous optimisations around ‘switching and saving’ have performed well.
- Personalised messaging always outperforms generic messages
Goals & Objectives
User value goals
- Delivering real savings by helping users reduce interest payments.
- Educate users on balance transfer benefits.
- Highlight personalised savings for users.
Business value goals
- Increasing card conversions from the marketplace.
- Boost engagement with balance transfer offers.
Success metrics
Metrics are measured against analytics from the live app.
Success
Ok
Fail
Percentage of users that apply from the new product list page
> 10%
7-10%
< 7%
Percentage of eligible users that start the new journey
> 10%
7-10%
< 7%
Target Audience
Requirements
- Users we predict can save above £100 by switching to a balance transfer card.
- Users with at least a 70% chance of approval for the balance transfer card.
- Users that have revolved a balance for the last 3 months.
- Active & semi-active users (logged in within the last 6 months)
- Users who are not flagged to be on a 0% promotional rate
- Users with credit score above 300.
Personas
ClearScore has 6 personas — 4 of these are a target audience for this project and described below:
Money Maker - Maria
High earner with strong credit, rarely uses ClearScore.
Growth Phase - Grace
Busy working mum, tech-savvy and credit confident.
Mutual Resources - Mike
Older self-employed user, focused on clearing debt, uses ClearScore occasionally.
Deal Seeker - Deepak
Budget-savvy dad, always hunting for savings, uses ClearScore often.
Design Requirements
- Savings Calculation
• Show real-time savings using actual card data (APR, balance, payment).• Only calculate after eligible cards are returned.
- API Integration UX
• Trigger panel search via partner APIs. • Handle delays with smooth loading/progress indicators.
- Pre-condition Logic
• Require Offers flow completion (30-day + credit card). • Integrate into journey as needed.
- In-App Entry Points
• Add entry points from dashboard, cards tab, or credit report. • Target users with card debt or interest.
- Existing credit card input
• Allow editing of card details (APR, balance, payment).
- Results Presentation
• Show savings for top 1, 3, or all eligible cards. • Include APR, terms, eligibility, example. • Link to product pages.
- Unhappy Path
• Fallback if no savings or BT cards. • Suggest next steps or alternatives.
Design stage 1 OF 4
Discover
Our initial problem statement was based on the saving calculation and success of related optimisations. So needed to know users thoughts about switching or why users are not saving on their interest payments.
Assumed Problem Insights
Research Topics Gathering
Research Prioritisation
Importance knowledge matrix
Top Priority Research Topics
Top Priority Research Topics
Top Priority Research Topics
Top Priority Research Topics
Design stage 2 OF 4
Define
We needed to refine the numerous research findings into the most relevant insights and a thorough problem definition to start ideating from.
Unstructured Research Findings
Findings Themes
Key Research Insights
Insight 1
Personalised savings must be made clear and tangible
1. Key Insight
Users are more likely to switch when shown personalised, clear savings.
2. Context
Happens during offer comparison and decision-making.
3. Root Cause
Generic savings don’t feel relevant or motivating.
4. Impact
Users disengage if they don’t see clear benefit.
5. User Goal
Users disengage if they don’t see clear benefit.
6. Recommendation
Show estimated monthly and total savings using real card data.
Insight 2
Educational gaps undermine switching confidence
1. Key Insight
Users hesitate due to confusion about switching steps or terms.
2. Context
Visible early in the journey or while browsing offers.
3. Root Cause
Lack of plain explanations or onboarding guidance.
4. Impact
Motivated users drop off from uncertainty.z
5. User Goal
Feel confident about how switching works.
6. Recommendation
Use visual guides and simple explanations at key touchpoints.
Insight 3
Too many card options lead to decision paralysis
1. Key Insight
Users feel overwhelmed by large lists of similar cards.
2. Context
Occurs during browsing or comparison.
3. Root Cause
Lack of curation or clear ranking.
4. Impact
Leads to indecision and drop-off.
5. User Goal
Quickly find the best match.
6. Recommendation
Show 1–3 top offers by default with the option to explore more.
Insight 4
Confidence in eligibility drives switching action
1. Key Insight
Users apply more when they’re confident they’ll be approved.
2. Context
Appears when reviewing offer lists.
3. Root Cause
Fear of rejection or harming credit score.
4. Impact
Users skip offers, even when eligible.
5. User Goal
Apply only to offers they’re likely to get.
6. Recommendation
Display strong approval signals and explain how they're calculated.
Insights Problem Statements
What the user problem is
Who has the problem ...
ClearScore users with credit card debt who are open to switching but feel uncertain or overwhelmed during the process.
What is the problem...
They can’t easily understand how much they’ll save, feel unsure how the process works, and lack confidence in choosing and being approved for a card.
When/where does the problem occur...
While exploring switching options in the app — particularly during offer comparison, information review, and decision-making.
Why is it important to address for the user...
Unclear value, too many choices, and low confidence prevent users from switching — even when it would save them money and reduce interest payments.
Other Projects
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
If you like what you see — Don’t be a stranger! ...
o.hardisty@me.com
Switch
& Save
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
overhead title
Detail
overhead title
Detail
overhead title
Detail
overhead title
Detail
Context & problem statement
Context
A large majority of users carry over balances on their credit cards, often paying high interests on this debt.
We’ve calculated that we could help save ~£200M across our users if they switched their credit cards to balance transfer cards available in our marketplace.
Users don’t currently know how much they could save with a balance transfer card and so are less motivated to switch.
Problem statement
Who has the problem ...
Users with outstanding credit card balances.
What is the problem ...
They pay high interest and don’t realise they could save by switching to balance transfer cards.
When/where does the problem occur ...
When managing credit card debt and browsing the marketplace.
Why is it important to address for the customer ...
They miss out on potential savings and lack motivation to switch.
Existing relevant insights
- Over 231,000 users could save £576 on average by switching to a balance transfer card.
- Previous optimisations around ‘switching and saving’ have performed well.
- Personalised messaging always outperforms generic messages
Goals & Objectives
User value goals
- Delivering real savings by helping users reduce interest payments.
- Educate users on balance transfer benefits.
- Highlight personalised savings for users.
Business value goals
- Increasing card conversions from the marketplace.
- Boost engagement with balance transfer offers.
Success metrics
Metrics are measured against analytics from the live app.
Success
Ok
Fail
Percentage of users that apply from the new product list page
> 10%
7-10%
< 7%
Percentage of eligible users that start the new journey
> 10%
7-10%
< 7%
Target Audience
Requirements
- Users we predict can save above £100 by switching to a balance transfer card.
- Users with at least a 70% chance of approval for the balance transfer card.
- Users that have revolved a balance for the last 3 months.
- Active & semi-active users (logged in within the last 6 months)
- Users who are not flagged to be on a 0% promotional rate
- Users with credit score above 300.
Personas
ClearScore has 6 personas — 4 of these are a target audience for this project and described below:
Money Maker - Maria
High earner with strong credit, rarely uses ClearScore.
Growth Phase - Grace
Busy working mum, tech-savvy and credit confident.
Mutual Resources - Mike
Older self-employed user, focused on clearing debt, uses ClearScore occasionally.
Deal Seeker - Deepak
Budget-savvy dad, always hunting for savings, uses ClearScore often.
Design Requirements
- Savings Calculation
• Show real-time savings using actual card data (APR, balance, payment).• Only calculate after eligible cards are returned.
- API Integration UX
• Trigger panel search via partner APIs. • Handle delays with smooth loading/progress indicators.
- Pre-condition Logic
• Require Offers flow completion (30-day + credit card). • Integrate into journey as needed.
- In-App Entry Points
• Add entry points from dashboard, cards tab, or credit report. • Target users with card debt or interest.
- Existing credit card input
• Allow editing of card details (APR, balance, payment).
- Results Presentation
• Show savings for top 1, 3, or all eligible cards. • Include APR, terms, eligibility, example. • Link to product pages.
- Unhappy Path
• Fallback if no savings or BT cards. • Suggest next steps or alternatives.
Design stage 1 OF 4
Discover
Our initial problem statement was based on the saving calculation and success of related optimisations. So needed to know users thoughts about switching or why users are not saving on their interest payments.
Assumed Problem Insights
Research Topics Gathering
Research Prioritisation
Importance knowledge matrix
Top Priority Research Topics
Top Priority Research Topics
Top Priority Research Topics
Top Priority Research Topics
Design stage 2 OF 4
Define
We needed to refine the numerous research findings into the most relevant insights and a thorough problem definition to start ideating from.
Unstructured Research Findings
Findings Themes
Key Research Insights
Insight 1
Personalised savings must be made clear and tangible
1. Key Insight
Users are more likely to switch when shown personalised, clear savings.
2. Context
Happens during offer comparison and decision-making.
3. Root Cause
Generic savings don’t feel relevant or motivating.
4. Impact
Users disengage if they don’t see clear benefit.
5. User Goal
Users disengage if they don’t see clear benefit.
6. Recommendation
Show estimated monthly and total savings using real card data.
Insight 2
Educational gaps undermine switching confidence
1. Key Insight
Users hesitate due to confusion about switching steps or terms.
2. Context
Visible early in the journey or while browsing offers.
3. Root Cause
Lack of plain explanations or onboarding guidance.
4. Impact
Motivated users drop off from uncertainty.z
5. User Goal
Feel confident about how switching works.
6. Recommendation
Use visual guides and simple explanations at key touchpoints.
Insight 3
Too many card options lead to decision paralysis
1. Key Insight
Users feel overwhelmed by large lists of similar cards.
2. Context
Occurs during browsing or comparison.
3. Root Cause
Lack of curation or clear ranking.
4. Impact
Leads to indecision and drop-off.
5. User Goal
Quickly find the best match.
6. Recommendation
Show 1–3 top offers by default with the option to explore more.
Insight 4
Confidence in eligibility drives switching action
1. Key Insight
Users apply more when they’re confident they’ll be approved.
2. Context
Appears when reviewing offer lists.
3. Root Cause
Fear of rejection or harming credit score.
4. Impact
Users skip offers, even when eligible.
5. User Goal
Apply only to offers they’re likely to get.
6. Recommendation
Display strong approval signals and explain how they're calculated.
Insights Problem Statements
What the user problem is
Who has the problem ...
ClearScore users with credit card debt who are open to switching but feel uncertain or overwhelmed during the process.
What is the problem...
They can’t easily understand how much they’ll save, feel unsure how the process works, and lack confidence in choosing and being approved for a card.
When/where does the problem occur...
While exploring switching options in the app — particularly during offer comparison, information review, and decision-making.
Why is it important to address for the user...
Unclear value, too many choices, and low confidence prevent users from switching — even when it would save them money and reduce interest payments.
Other Projects
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
Cignpost
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna
See Project
→
If you like what you see — Don’t be a stranger! ...
o.hardisty@me.com