StepOne Finance
Delivering a 180% increase in attributable revenue alongside a 55% reduction in acquisition costs, through product-segmented PPC, organic authority building, and AI-optimised bidding calibrated to funded loan outcomes across secured and unsecured products.
Headline Results
The Client
StepOne Finance is a specialist UK consumer lender based in Woking, Surrey, offering both secured second charge mortgages of up to £500,000 and unsecured personal loans from £1,000 to £10,000. Established in 2010 and regulated by the FCA, the business has completed over £200 million in loans, built on core principles of transparency, fairness, and responsible lending. StepOne operates across a broad range of customer circumstances, serving homeowners seeking debt consolidation, home improvements, or large purchases through its experienced underwriting team.
They engaged Digiconomy to scale direct-to-consumer acquisition through search, generating a consistent flow of qualified loan applications while maintaining the strict cost efficiency required in specialist lending.
We delivered a focused acquisition strategy combining Google PPC and SEO, augmented by AI-powered bid management and LLM-informed content strategy. Within 12 months, this approach produced a 180% increase in attributable revenue alongside a 55% reduction in acquisition costs, delivering an exceptional 20x return on investment.
To ensure every optimisation decision was grounded in real outcomes, we built attribution that tracked from initial search click through to completed, funded loan, giving the team clear visibility of which activity was driving genuine commercial value. This closed-loop data also fed the AI bidding models that continually refined targeting across both product lines.
The Objectives
Build a scalable direct-to-consumer channel and prove that revenue growth and cost reduction could be delivered simultaneously.
Drive Direct Application Volume
- Reduce reliance on broker-introduced business by building a scalable direct-to-consumer acquisition channel through paid and organic search.
- Ensure growth was measured against funded loan completions rather than enquiry volume, maintaining alignment between marketing performance and underwriting capacity.
Maximise Return on Marketing Investment
- Achieve significant revenue growth while simultaneously bringing down the cost of acquisition, proving that scale and efficiency could be delivered together rather than traded off against each other.
- Establish a tracking and reporting framework that gave the leadership team confidence in exactly where marketing spend was generating returns.
The Strategy
A high-efficiency search strategy designed to capture qualified borrowers across both secured and unsecured products, drive direct applications at scale, and deliver exceptional cost performance in a competitive specialist lending market.
Product-Led Campaign Architecture
Structure campaigns around StepOne's distinct product lines, separating secured second charge mortgage traffic from unsecured personal loan demand to ensure targeting, messaging, and bid strategies reflected the different borrower profiles and values involved. AI-powered audience segmentation further refined this separation, using machine learning to identify the behavioural and demographic signals that distinguished high-value mortgage applicants from personal loan seekers, allowing each campaign to optimise independently for its specific funded loan outcome.
Cost-Per-Funded-Loan Optimisation
Move optimisation upstream by tying bid decisions to funded loan data rather than front-end enquiry metrics, systematically eliminating wasteful spend and concentrating budget on the keywords and audiences that converted through to completion. AI-powered Smart Bidding was trained on completed loan outcomes across both product lines, enabling the algorithm to value each auction based on predicted funded loan probability and loan value, not just click likelihood or form submissions.
Organic Authority Building
Develop search visibility for specialist lending terms across both product categories, creating a sustainable source of qualified applications that reduced overall acquisition costs and supported long-term growth beyond paid media. Content architecture was structured for both traditional search rankings and LLM extractability, ensuring StepOne's specialist lending expertise surfaced in AI-generated answers when homeowners researched second charge options or consumers compared personal loan providers through AI search tools.
The Campaign
Product-segmented PPC, specialist organic authority, revenue-aware bidding, and closed-loop attribution, all calibrated across secured and unsecured products for maximum funded loan yield.
Product-Segmented PPC
Google PPC was structured around StepOne's two core product lines, with dedicated campaigns for second charge mortgages and unsecured personal loans targeting distinct borrower audiences. Each product vertical had its own keyword strategy, ad copy, and landing pages tailored to the specific borrower mindset, from homeowners considering equity release to consumers seeking unsecured credit. AI-powered Smart Bidding operated independently within each vertical, trained on product-specific funded loan data to optimise for the distinct conversion patterns and loan values of each line.
SEO & Specialist Authority
SEO built organic visibility across specialist lending terms, from homeowner loans and debt consolidation through to personal loan queries, establishing authority in a niche where trust and credibility are critical. Content strategy addressed both transactional queries and informational needs around second charges, secured borrowing, and responsible lending options. Structured data and entity markup reinforced StepOne's identity as an established specialist lender across both traditional search and AI platforms, positioning the brand for visibility in LLM-generated recommendations for complex lending queries.
Revenue-Aligned Bidding
Bid strategies were aligned to funded loan revenue, enabling rapid reallocation of budget toward the highest-performing keywords. The AI bidding models accounted for the significant difference in loan values between secured and unsecured products, ensuring a £200,000 second charge completion was weighted appropriately against a £5,000 personal loan in budget allocation decisions. This revenue-aware approach was central to driving the 55% reduction in acquisition costs while simultaneously scaling volume.
Closed-Loop Attribution
Closed-loop attribution connected every click to a funded outcome, providing granular visibility from first search interaction through to completed loan across both product lines. This tracking framework gave the leadership team confidence in exactly where marketing spend was generating returns, while feeding the AI bidding models with the downstream data they needed to continuously improve targeting precision. The result was a compounding cycle where each funded loan sharpened the next round of budget allocation decisions.
The Outcome
Increase in revenue
Reduction in acquisition costs
Return on investment
Within 12 months, the product-segmented strategy delivered a 180% increase in attributable revenue while cutting acquisition costs by 55%. AI-optimised bidding that accounted for the distinct values of secured and unsecured products, LLM-ready specialist lending content, and closed-loop attribution created a compounding engine where every funded loan refined the next round of budget allocation and targeting decisions.
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