Aspire Money
Driving a 240% increase in attributable revenue while cutting acquisition costs by nearly a third through intent-driven PPC, organic authority building, and AI-powered conversion optimisation.
Headline Results
The Client
Aspire Money is a well-established UK credit broker specialising in personal loans for consumers across all credit profiles. Founded in 2008 and authorised by the Financial Conduct Authority, the business connects borrowers with a curated panel of lenders, offering unsecured loans from £500 to £25,000.
They engaged Digiconomy to increase the volume of qualified loan applications generated online while reducing the cost per funded loan, all within the strict advertising requirements imposed by the FCA and individual lending partners.
We delivered an integrated acquisition strategy combining Google Ads, Microsoft Ads, SEO, and conversion rate optimisation, augmented by AI-powered bidding, LLM-informed content strategy, and machine learning-driven CRO. Within the first year, this approach drove a 240% increase in attributable revenue while cutting acquisition costs by nearly a third.
To underpin long-term performance, we built a robust tracking framework that connected ad click through to funded loan, giving the team full visibility of which keywords, ads, and landing pages were generating real commercial value, not just form submissions. This closed-loop data infrastructure also fed the AI bidding models that continually improved targeting precision.
The Objectives
Growth anchored to funded loans and lender commissions, not vanity metrics, while maintaining full regulatory compliance.
Scale Qualified Application Volume
- Grow the number of high-quality loan enquiries generated through search and organic channels without inflating spend or diluting lead quality.
- Ensure growth was measured against funded loans and lender commissions, not vanity metrics such as raw form fills or click volume.
Maintain Compliance Across All Activity
- Operate fully within FCA financial promotion rules, ensuring every ad, landing page, and piece of content met regulatory standards.
- Implement tracking and attribution that respected data privacy obligations while still providing the granularity needed for meaningful optimisation.
The Strategy
A performance-driven acquisition strategy designed to capture high-intent borrowers at the point of need, convert them efficiently, and scale spend in line with profitability.
Precision Keyword Targeting
Identify and prioritise the search terms that signalled genuine borrowing intent, separating tyre-kickers from applicants ready to proceed, across both Google and Microsoft Ads. AI-powered intent classification helped segment queries by predicted conversion probability, allowing budget to concentrate on the terms most likely to generate funded loans rather than just clicks.
Conversion-Focused Optimisation
Go beyond traffic generation by systematically testing and refining landing pages, application forms, and user journeys to maximise the rate at which visitors became funded borrowers. Machine learning models analysed user behaviour patterns across thousands of sessions, surfacing the friction points and layout variations that had the greatest impact on completion rates.
Sustainable Organic Growth
Build long-term search visibility for commercially valuable lending terms, reducing reliance on paid media and creating a compounding source of qualified traffic over time. Content architecture was optimised for both traditional search rankings and LLM extractability, ensuring Aspire Money's expert lending content would surface in AI-generated answers as generative search adoption grew.
The Campaign
Paid search, organic authority, and conversion rate optimisation working together, underpinned by closed-loop attribution and AI-driven performance signals.
Intent-Driven PPC
Google Ads and Microsoft Ads campaigns were structured around borrower intent, with tightly themed ad groups targeting specific loan types, amounts, and credit circumstances. Ad copy was developed in close collaboration with the compliance team to meet FCA financial promotion requirements while still driving strong click-through rates. Bid strategies were aligned to downstream revenue rather than surface-level conversions, with AI-powered Smart Bidding calibrated against actual lender commission data. This allowed budgets to flow towards the keywords and audiences generating the highest commercial value.
SEO & Content Authority
We built topical authority across the personal loans space through a content strategy targeting informational and transactional queries alike, from guides on improving credit scores and understanding APR through to direct loan comparison and application pages. Technical improvements ensured the site was fast, mobile-optimised, and structured for maximum crawl efficiency. Structured data and entity markup were implemented to strengthen the site's visibility not just in traditional rankings, but across AI search engines and LLM-powered answer platforms where lending queries are increasingly resolved.
Conversion Rate Optimisation
CRO tied the entire programme together. We ran a structured testing roadmap across application forms, landing page layouts, trust signals, and call-to-action placement. Even modest improvements in conversion rate delivered outsized returns given the volume of traffic flowing through the site, turning the same ad spend into significantly more funded loans. AI-assisted multivariate testing accelerated the learning cycle, identifying winning combinations faster than manual A/B testing alone.
Closed-Loop Attribution
All activity was underpinned by end-to-end tracking that followed each visitor from their first interaction through to a completed, funded loan. This closed-loop attribution enabled confident optimisation decisions based on actual revenue, continuously reallocating budget towards the highest-performing combinations of keyword, ad, and landing page. The same granular data fed the AI bidding models, creating a feedback loop where every funded loan improved the next round of targeting decisions.
The Outcome
Increase in revenue
Reduction in acquisition costs
Return on investment
Within the first year, the integrated strategy delivered a 240% increase in attributable revenue. AI-optimised bidding aligned to funded loan data, LLM-ready content architecture, and conversion-focused testing created a self-reinforcing system where every data point sharpened the next decision.
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