AI AGENT CASE STUDY: HOW WE HELPED LOGIC LUMINATE REDUCE CPA FROM $2800 TO $475
In 3 Months, Our AI Agent Increased reply rates from under 5% to 34%, raise close rate from 12% to 67%, and cut CPA from $2,800 to $475 in just 3 months
Logic Luminate, a digital marketing agency serving mid-market B2B companies, had a strong offer but a painfully manual outbound process.
We implemented an AI-driven prospecting and outbound system that helped them identify stronger-fit leads, personalise outreach at scale, and operate with far greater consistency.
Reply rate
under 5% → 34%
More relevant outreach created stronger first conversations.
Close rate
12% → 67%
Better-fit prospects improved the quality of booked calls.
Booked calls
Tripled
Outbound execution became more consistent and easier to scale.
Customer acquisition cost
$2,800 → $475
The team generated pipeline with far less manual effort.
About Logic Luminate
A B2B growth agency with a strong offer, but an outbound engine that was not built for scale.
Logic Luminate helps businesses grow through strategic marketing, lead generation, and campaign delivery. Their core offer is designed for mid-market B2B companies that want more than generic agency support.
Their ideal buyers are typically seven-figure business owners, heads of growth, or marketing directors looking for a more intelligence-led, results-driven marketing partner.
The challenge
The problem: too much manual effort, too little commercial leverage.
Before working with us, Logic Luminate's outbound workflow was heavily manual from start to finish. The team was working hard, but the system around them was not built to scale.
Their team manually browsed LinkedIn and company websites to identify prospects, checked industries and job titles by hand, logged data in spreadsheets, exported contact records to CSV files, wrote emails by hand or from lightweight templates, and tracked follow-ups in separate sheets.
CRM updates only tended to happen once somebody replied, which meant pipeline visibility was poor and reporting was fragmented.
Prospecting consumed an enormous amount of time. With a seven-person sales team, Logic Luminate was spending around 280 hours per week on prospecting-related activity alone.
Personalisation at scale was almost impossible. Because reps were manually researching and writing outreach, messaging either took too long to create or became too generic to convert well.
Why Logic Luminate chose us
They wanted more than off-the-shelf automation.
Logic Luminate had been referred to us because they wanted an AI partner who would understand the business properly before building around it. Their challenge was not simply a tooling problem. It was a workflow, decision-making, and scale problem.
From the start, our focus was not on layering random AI tools into their sales process. The aim was to understand the commercial logic behind the work before deciding what should be automated.
We looked closely at how they sourced leads, how they judged prospect fit, where friction appeared in their outbound motion, and what kind of messaging actually reflected their positioning.
AI agent solution
An AI-driven outbound system built around relevance, prioritisation, and scale.
We designed and implemented a multi-layer AI outbound system to help Logic Luminate move from manual prospecting and inconsistent outreach to a more intelligent, scalable growth engine.
The goal was not to create a giant volume machine. It was to help Logic Luminate focus on companies that were more commercially relevant from the start, then give the sales team the context, prioritisation, and workflow consistency needed to convert those opportunities more effectively.
Without revealing proprietary implementation details, the solution combined prospect sourcing, enrichment, scoring, message generation, campaign automation, CRM synchronisation, dashboard visibility, and human approval into one controlled outbound engine.
Intelligent prospect sourcing
The AI automation helped identify stronger-fit companies using company-fit indicators and commercial signals, reducing reliance on manual lead hunting.
Autonomous lead enrichment
The system added firmographic, market, and activity context so prospects became commercially useful records rather than names in a spreadsheet.
AI-led scoring and prioritisation
Leads were classified by fit and engagement potential so the team could focus on higher-value opportunities first.
Hyper-personalised outreach generation
Outreach moved beyond cosmetic mail-merge personalisation into context-aware messaging shaped around the prospect's business and likely needs.
Campaign automation and follow-up consistency
Outbound sequences became more structured and dependable, removing reliance on rep memory or spreadsheet tracking.
CRM synchronisation and dashboard visibility
Two-way CRM sync and dashboard visibility created cleaner feedback across lead status, outreach activity, and pipeline performance.
Human approval and control layer
Quality assurance remained built into the workflow, preserving trust, commercial judgment, and brand protection as the system scaled.
Implementation
How the AI outbound system was rolled out in 6 weeks.
The full implementation took 6 weeks. We used a phased rollout so Logic Luminate could build trust in the system, validate output quality, and refine the workflow before scaling it across the sales motion.
Discovery and process mapping
We analysed the existing workflow, shadowed the sales process, reviewed past outbound performance, mapped the ideal customer profile, and identified key friction points.
Build phase
We built the prospect sourcing, enrichment, and scoring framework that would become the foundation of the new outbound engine.
Integration phase
We connected the relevant data, outreach, and CRM layers so the workflow could operate with far less manual handoff.
Testing and manual review
We ran 500 leads through the system with structured human review, validating scoring quality, personalisation logic, and commercial fit.
Pilot rollout
The new workflow was rolled out to one sales rep first, creating a controlled comparison point before wider adoption.
Optimisation
Using real reply behaviour and early workflow feedback, we adjusted scoring emphasis and refined personalisation logic for live conditions.
What made the system effective
Why the AI system became so intelligent and powerful.
What made this implementation powerful was not simply that AI was introduced. It was that the entire prospecting-to-outbound motion became more intelligent, more structured, and more commercially useful.
Before implementation
Manual effort drove the outbound motion.
- Research depended heavily on manual prospect checks.
- Qualification was subjective and inconsistent.
- Execution relied on rep memory and separate spreadsheets.
After implementation
Structured intelligence guided the workflow.
- Stronger-fit prospects surfaced earlier.
- Outreach angles were shaped by richer context.
- Follow-up, CRM visibility, and oversight became systematic.
Better prospect context
Richer lead context was available before outreach, so the team no longer started from a cold, generic baseline.
Smarter prioritisation
Effort was directed toward stronger opportunities instead of being spread evenly across every prospect.
More relevant messaging
Outreach became more contextual and less robotic, creating stronger reasons for prospects to reply.
Systematic follow-up
Follow-up became structured and dependable rather than dependent on spreadsheets or individual rep memory.
Clearer CRM visibility
Pipeline data, campaign activity, and lead status became easier to track across the workflow.
Human oversight where it mattered
Quality control remained in the process, preserving trust and commercial judgment as automation scaled.
Human oversight and safeguards
Scaling AI without sacrificing control, quality, or brand protection.
One reason AI implementations fail is that businesses either over-trust them too quickly or force them into workflows with no guardrails. We avoided both mistakes by keeping humans in the loop at the right moments.
Logic Luminate did not want reckless automation, and neither did we. The outbound engine needed to scale responsibly while preserving commercial judgment, message quality, and trust.
That meant the system was designed with control points around approval, suppression, deliverability, fallback handling, CRM review, and audit visibility.
Final approval layer
Human review remained in the workflow so quality control was preserved before high-impact outbound activity went live.
Suppression and opt-out handling
The system respected suppression rules and opt-out signals so the outbound engine did not create unnecessary risk.
Deliverability safeguards
Sending controls helped protect domain health, campaign reliability, and the long-term quality of outbound execution.
Fallback rules for lower-confidence leads
Lower-confidence prospects followed safer workflows, preventing weak-fit leads from receiving the same treatment as high-confidence opportunities.
CRM review checkpoints
Review points were built in before direct sales rep action, improving operational clarity and reducing messy handoffs.
Regular audit visibility
The team could review campaign behaviour, system decisions, and workflow performance instead of operating from a black box.
Results
The outcome after 3 months.
The impact was transformational. Within three months of implementation, Logic Luminate had a far more efficient outbound engine capable of producing stronger results with fewer people and far less manual effort.
Reply rate
under 5% → 34%
More relevant outreach created stronger response rates.Booked calls
Tripled
More consistent outbound execution created more sales conversations.Close rate
12% → 67%
Better-fit calls improved conversion from booked call to closed-won.Customer acquisition cost
$2,800 → $475
Pipeline became less dependent on heavy manual effort.Sales team size
7 people → 3 people
The team became smaller while performance improved.These results represent more than marginal optimisation. Before the implementation, Logic Luminate was relying on a labour-heavy outbound process to create pipeline.
After implementation, they had a far more efficient system capable of producing stronger results with fewer people and far less manual effort.
Business impact
Why the numbers improved.
The results improved because the system raised the quality of the entire outbound process. Logic Luminate was no longer forcing the same amount of effort across every prospect.
Better-fit opportunities were identified earlier. Messaging became more relevant. The strongest leads were prioritised more effectively. Follow-up became more consistent. CRM visibility improved.
The team could work from a cleaner, more commercially useful pipeline instead of relying on manual hustle across disconnected workflows.
Client experience
What it was like working with Lotusbrains Studio.
Logic Luminate was exceptionally pleased with the collaboration. More than delivering strong results, the process was smooth, thoughtful, hands-on, and commercially grounded.
Business understanding first
We took the time to understand how their team actually worked, where performance was being lost, and what kind of system would be useful in practice.
Technical capability with commercial judgment
What they valued most was that we combined AI implementation discipline with a practical understanding of revenue workflows.
Not generic automation
Rather than dropping in random tools, we built around their real operating model, outbound positioning, and quality standards.
Final takeaway
Logic Luminate did not need another generic outbound tool.
They needed a smarter way to identify prospects, personalise outreach, improve conversion quality, and grow pipeline without scaling manual effort in parallel.
By working with us, they replaced a fragmented, labour-heavy outbound process with an AI-driven growth engine built around relevance, prioritisation, and operational control.
For agencies and service businesses looking to scale without drowning in manual outbound work, this case study shows what becomes possible when AI is implemented properly: not just more activity, but far better leverage.
Build smarter outbound
Want to build a smarter outbound engine for your business?
If your team is spending too much time on manual prospecting, inconsistent outreach, and disconnected follow-up, we can help you design and implement AI systems that make growth more scalable.
We do not believe in generic automation. We build tailored AI workflows that align with how your business actually operates, so you can identify better opportunities, communicate more intelligently, and scale with greater efficiency.
Book a free discovery call with us today.
Let's explore how an AI-driven workflow could improve your lead generation, outbound execution, and sales efficiency.
Book a Discovery Call