Evlo
Scaling online loan acquisition to nearly £6m in attributable revenue while significantly improving acquisition efficiency, powered by AI-optimised bidding, multi-channel search, and granular attribution.
Headline Results
The Client
Evlo is a leading UK consumer lender specialising in unsecured personal loans. Founded in 2006 and acquired by Secure Trust Bank in 2012, the business operates in a highly competitive and heavily regulated market.
They engaged Digiconomy to scale online loan acquisition profitably while maintaining strict compliance across all marketing activity.
We delivered a multi-channel inbound strategy combining Google Ads, Microsoft Ads, and SEO, augmented by AI-powered bid optimisation and LLM-informed content strategy. Within 12 months, this approach generated nearly £6m in attributable revenue while significantly improving acquisition efficiency.
To support sustainable growth, we implemented granular server-side tracking and multi-touch attribution, enabling revenue to be analysed at keyword, ad, and landing-page level for continuous optimisation. This same data infrastructure fed the AI bidding models that drove performance gains throughout the engagement.
The Objectives
Clear goals that tied every decision back to commercial outcomes and regulatory responsibility.
Profitable Online Growth
- Scale online loan applications while maintaining strong cost efficiency and predictable returns.
- Ensure acquisition activity could be increased without sacrificing profitability.
Regulatory Compliance & Transparency
- Deliver measurable growth while operating fully within FCA guidelines and platform policies.
- Implement clear attribution to understand true performance across channels and campaigns.
The Strategy
A data-led acquisition strategy designed to capture high-intent demand, support assisted conversions, and scale performance in a controlled, compliant manner.
Full-Funnel Acquisition
Capture high-intent users through search while supporting consideration and return visits across the funnel. AI-powered audience signals and intent modelling ensured budget flowed to the highest-value touchpoints at every stage.
Data-Led Optimisation
Optimise bids, budgets, and creative using revenue and profitability signals rather than lead volume. Machine learning models were trained on back-end conversion data, enabling the platform algorithms to prioritise applicants most likely to complete, not just click.
Scalable Frameworks
Build campaign structures capable of handling high budgets, large keyword volumes, and rapid iteration. Automated rules and AI-driven bid strategies allowed the campaigns to scale without manual bottlenecks or diminishing returns.
The Campaign
Multi-channel execution combining organic authority, AI-optimised paid media, intelligent remarketing, and full-funnel attribution.
SEO & Content Authority
Organic search activity focused on improving visibility for high-intent lending terms, building topical authority, and strengthening entity signals. Structured data and content architecture were optimised not only for traditional rankings but for LLM extractability, ensuring Evlo would surface in AI-generated answers for key queries. This dual-purpose approach supported long-term demand generation and brand authority across both conventional and generative search.
AI-Optimised PPC
Google Ads and Microsoft Ads campaigns were built on a compliance-first framework, with highly structured ad groups, granular keyword segmentation, and revenue-based bidding. Smart Bidding strategies were calibrated against actual loan completion data rather than front-end lead metrics, letting the platform AI optimise for real business outcomes. Continuous creative testing and landing page experimentation compounded performance gains over time.
Remarketing & Recovery
Remarketing across search, display, and social re-engaged users who had not converted on their first visit, recovering a significant volume of otherwise lost revenue. Sequential messaging adapted based on where users had dropped off, using AI-powered audience segmentation to personalise the return path and maximise conversion probability.
Advanced Tracking & Attribution
All activity was supported by server-side tracking and multi-touch attribution, providing clear insight from first click through to revenue. This granular data layer enabled continuous performance optimisation, informed budget allocation across channels, and fed the AI bidding models with the high-quality signals they needed to improve over time.
The Outcome
Increase in revenue
Reduction in acquisition costs
Return on investment
Within 12 months, the combined strategy generated nearly £6m in attributable revenue. AI-optimised bidding, structured data enhancements for LLM visibility, and server-side attribution created a compounding engine where every data point improved the next decision.
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