Real estate cost-per-lead has been climbing across Bangladeshi developers for years. The lead that cost BDT 500 in 2020 now costs BDT 1,500 or more in many markets. The lead that cost BDT 2,000 in 2020 now costs BDT 5,000+ for premium project categories. The competitive intensity in real estate marketing has driven costs up substantially, and most developers respond by increasing budgets to maintain lead volume rather than addressing the underlying inefficiencies that make their lead generation more expensive than it needs to be.
The honest assessment for most Bangladeshi real estate developers: substantial portions of current lead generation cost result from operational inefficiencies that systematic improvement would address. The 50% CPL reduction the title promises isn’t hyperbole — it’s realistic for developers currently operating with the inefficiencies that affect most of the market. Developers already operating at near-optimal CPL won’t achieve 50% reduction because they don’t have 50% of waste to eliminate. But developers operating with typical Bangladeshi real estate marketing inefficiencies routinely have substantial opportunity that systematic improvement captures.
This post is the diagnostic framework and intervention sequence that produces substantial CPL reduction. Where the inefficiencies typically hide. Which interventions produce highest impact relative to effort. The operational discipline that makes the improvements sustainable rather than temporary. The Bangladesh-specific considerations affecting how this work plays out.
For broader real estate marketing context, I covered the multi-platform strategy in Multi-Platform Real Estate Marketing Strategy and lead nurturing in Real Estate Lead Nurturing. This post focuses specifically on CPL reduction for Bangladeshi real estate developers.
If you’re currently paying more for real estate leads than you think you should be, working through this diagnostic will identify where the inefficiencies are and what to do about them.
Before getting into methodology, honest framing about what 50% CPL reduction actually involves.
The reduction is achievable when starting CPL is high relative to the realistic floor for your category and market. Most developers operating without systematic optimization face accumulated inefficiencies that compound their CPL substantially above achievable levels. Addressing those inefficiencies systematically often produces 50%+ reduction.
The reduction is harder when starting CPL is already near optimal levels for your category. Developers who’ve been operating with sophisticated marketing for years typically don’t have 50% of waste to eliminate. Their improvement opportunities are typically smaller (10-25% might be realistic) but still meaningful.
The timeline matters. Substantial CPL reduction happens over 3-6 months of systematic work rather than over weeks. Brands looking for immediate CPL transformation typically don’t get it; brands committed to systematic improvement typically produce results worth the timeline.
The work requires investment. Reducing CPL while maintaining lead quality requires investment in measurement infrastructure, creative production capability, landing page optimization, conversion tracking sophistication, and operational discipline. Brands hoping CPL improvement happens without proportional investment typically don’t see substantial improvement.
What you’ll get from working through this framework: a diagnostic understanding of where your current CPL is being driven up by addressable factors, prioritized intervention sequence focusing on highest-impact opportunities first, realistic expectations about what improvement should look like for your specific situation, and operational framework for sustaining improvements rather than capturing temporary gains.
What you won’t get: guarantee that your specific situation will produce 50% reduction (depends on starting point and execution), shortcut that produces results without proportional work, or template that works without customization to your specific projects and audiences.
Before discussing specific interventions, understanding where waste accumulates in Bangladeshi real estate marketing helps prioritize where to look first.
Wrong audience targeting wasting spend on unqualified traffic.
Most Bangladeshi real estate marketing reaches substantial audiences who can’t or won’t actually purchase the properties being marketed. The audiences look right demographically but lack actual buying capability or genuine purchase intent.
The targeting inefficiencies that consistently cost money: targeting by general income demographics that include people who can’t afford the property pricing, targeting by age ranges that don’t reflect actual buyer profiles, targeting by interests that suggest general home interest but not specific buying-stage interest, targeting by job titles that don’t correlate with actual purchasing capability in Bangladesh context.
The pattern: developers paying full ad rates to reach audiences who appear demographically reasonable but lack the specific situation, financial capability, or buying timeline that produces actual leads. The leads that do come from these audiences typically don’t convert because they shouldn’t have been classified as leads — they’re interest signals without purchasing capability.
Generic creative producing weak conversion rates.
Real estate creative that could apply to any project, any developer, any audience. The generic creative produces clicks but doesn’t qualify or convert because nothing in the creative differentiates between someone who might buy this specific project and someone idly browsing real estate content.
The pattern: developers running creative that looks polished but doesn’t communicate what specifically this project offers, who specifically should consider it, or why specifically they should consider it now. The clicks happen but conversion to leads underperforms what specific creative would produce.
Landing page friction losing leads after click.
Ads that produce clicks routing to landing pages that lose substantial portions of clickers before any lead capture happens. Slow loading, poor mobile experience, irrelevant content that doesn’t match ad promise, complicated forms, missing trust signals — each loses clicks that should have produced leads.
The pattern: paying full ad cost for clicks while landing page friction causes most clicks to abandon before becoming leads. The CPL gets calculated as cost divided by actual leads, which makes it look high. The actual cost per click is reasonable; the loss between click and lead is what makes CPL high.
Form design causing capture friction.
Lead forms requesting more information than necessary, requiring information in formats that don’t work for mobile users, providing inadequate value exchange (why should the user provide their information), or operating on assumptions about user behavior that don’t match Bangladeshi reality.
The pattern: developers losing 40-70% of users who would have filled simpler forms because form design assumes patience and motivation that most users don’t have for real estate inquiries.
Wrong conversion goal optimization.
Ad platforms optimize toward whatever conversion events they receive. If your conversion tracking sends events for low-quality interactions (page views, form starts, button clicks), platforms optimize toward producing those events rather than producing actual qualified leads.
The pattern: ad platforms efficiently producing the metric being optimized (lots of cheap conversions) while the underlying business outcome (qualified leads) doesn’t follow because the metric and outcome don’t actually correlate.
Inadequate creative testing missing better-performing variants.
Running the same creative for months without systematic testing typically means operating with creative that’s mediocre relative to what testing would produce. The creative that’s been running may be acceptable, but testing typically reveals variants that perform substantially better.
The pattern: developers running their initial creative concepts indefinitely without testing variations, missing the 20-40% performance improvement that systematic creative testing typically produces.
Channel mix dysfunction allocating budget inefficiently.
Budget distribution across channels that doesn’t reflect actual channel performance. Continuing to spend heavily on channels with poor CPL while underinvesting in channels producing better CPL.
The pattern: developers operating with channel mixes that emerged historically rather than that reflect current performance data. The channels that produced results 2 years ago continue receiving budget even as their performance degrades; the channels that would produce better results now receive insufficient investment.
Lead handling failures making leads functionally worthless.
Leads generated successfully but lost through poor handling — slow follow-up, unprofessional sales engagement, lack of nurture for not-yet-ready buyers, failure to convert qualified leads to site visits.
The pattern: marketing generates leads that operations doesn’t convert, making the marketing CPL artificially high because the leads don’t produce business outcomes. The CPL math gets calculated against leads that should have been higher-quality but functionally weren’t.
Attribution problems hiding what’s actually working.
Conversion tracking and attribution that doesn’t accurately measure which channels, campaigns, and creative actually produce qualified leads versus which produce noise. Without accurate measurement, optimization decisions operate on wrong information.
The pattern: developers making channel and creative decisions based on attribution data that doesn’t accurately reflect what’s driving business outcomes. The decisions optimize toward measured metrics rather than toward business value.
Most developers have multiple of these inefficiencies operating simultaneously. The cumulative effect is CPL substantially higher than systematic optimization would produce. Addressing the inefficiencies typically produces compound improvements as each fix amplifies the value of other fixes.
Before intervention, diagnosis. Understanding which inefficiencies are actually affecting your situation determines what interventions matter most.
Step 1: Honest current state assessment.
Document current CPL by channel, by campaign, by audience segment, by creative. The breakdowns reveal patterns that aggregate CPL hides. The campaign that has 5x the CPL of your best campaign represents specific opportunity. The audience segment that produces leads at half the cost of other segments reveals targeting insights worth applying broadly.
The discipline: working through your data systematically rather than relying on intuitions about what’s working. Most developers operating without systematic analysis have inaccurate beliefs about what’s actually performing.
Step 2: Lead quality analysis.
Beyond CPL, lead quality varies substantially. The CPL that looks high might reflect quality leads worth paying for; the CPL that looks low might reflect quality so poor that the leads don’t convert.
The quality analysis: tracking lead progression through your sales funnel by source. Which channels produce leads that become qualified versus stay unqualified. Which campaigns produce leads that convert to site visits versus disappear. Which audiences produce leads that complete transactions versus those that don’t.
The quality data reveals true cost per qualified lead, which is the metric that actually matters for business outcomes. The CPL improvement opportunity isn’t just lowering nominal CPL — it’s lowering true cost per qualified lead by either reducing CPL while maintaining quality or improving quality while maintaining CPL.
Step 3: Funnel stage diagnosis.
The journey from impression to qualified lead has multiple stages, each with potential inefficiency. Understanding where in this funnel your specific situation is losing efficiency:
Impression to click: Is your ad creative producing reasonable click-through rates? Below-benchmark CTR suggests creative or targeting issues.
Click to landing page engagement: Are clickers actually engaging with landing pages or bouncing immediately? Bounce patterns suggest landing page or ad-to-page match issues.
Engagement to lead capture: Are engaged users converting to leads at reasonable rates? Low engagement-to-lead conversion suggests form or value proposition issues.
Lead capture to qualified lead: Are captured leads becoming qualified leads at reasonable rates? Low qualification rates suggest targeting or lead quality issues.
Each stage has specific intervention opportunities. The stage where your funnel loses the most efficiency is typically where intervention produces the largest CPL improvement.
Step 4: Channel-specific diagnosis.
Different channels have different optimization opportunities. Meta CPL improvement involves different interventions than Google Ads CPL improvement involves different interventions than real estate listing platform CPL improvement.
The channel-specific diagnosis: working through each significant channel’s specific performance, identifying channel-specific inefficiencies, prioritizing interventions by channel based on where opportunity is largest.
Step 5: Competitive benchmarking where possible.
Understanding how your CPL compares to competitor benchmarks (where data is available) provides context for what improvement is realistic. CPL substantially above category benchmarks suggests substantial improvement opportunity; CPL near or below benchmarks suggests smaller improvement opportunity.
The benchmarking sources: agency relationships that aggregate data across multiple developers, industry reports where available, conversations with other developers about general patterns, observation of competitor advertising approaches.
Based on the diagnosis, the intervention priorities that consistently produce substantial CPL improvement for Bangladeshi real estate:
Priority 1: Audience targeting precision.
The single highest-impact intervention for most Bangladeshi real estate developers. The audience refinement that improves who you’re reaching produces compound effects across all subsequent metrics.
Specific tactics:
Lookalike audiences from existing customer data: Building lookalikes from your actual buyer database produces audiences with substantially better conversion than broad demographic targeting. The actual buyer characteristics often differ from assumed buyer characteristics in ways that broad demographic targeting misses.
Income proxy refinement beyond stated income: Income targeting in Bangladesh has limitations because Meta’s income data isn’t always accurate. Better proxies often include device type targeting (premium device users), specific employer targeting where data permits, geographic targeting at neighborhood level rather than just city level, and interest combinations that suggest financial capability.
NRB (Non-Resident Bangladeshi) targeting where relevant: For projects appealing to NRB buyers, geographic targeting to specific NRB-concentrated geographies (UK, US, Middle East locations with substantial Bangladeshi populations) produces audiences that broad Bangladesh targeting misses.
Behavioral targeting based on real estate engagement signals: Audiences who’ve engaged with real estate content recently, used real estate-related apps, searched real estate queries, visited real estate websites. These behavioral signals correlate with actual buying interest more reliably than demographic signals alone.
Custom audiences from website visitors, video viewers, lead form interactions: Remarketing audiences typically produce substantially better CPL than prospecting audiences. The visitors who showed interest but didn’t convert represent re-engagement opportunity at lower cost than acquiring new prospects.
Negative audience exclusions for unqualified segments: Excluding audiences unlikely to actually purchase — wrong age ranges, wrong geographic areas, customers who already purchased, audiences with engagement patterns suggesting non-buyer intent.
Expected impact: 20-40% CPL improvement is realistic for developers with poor current targeting, depending on starting point. Combined with other interventions, audience targeting often produces compound effects exceeding any individual intervention’s standalone impact.
Priority 2: Landing page optimization.
The landing page is where ad spend converts to leads or doesn’t. Landing page improvements affect every subsequent metric.
Specific tactics:
Mobile-first optimization for Bangladesh’s mobile-dominant traffic: As covered in Mobile-First Landing Page Design for Bangladesh, Bangladesh’s mobile network and device realities require specific optimization beyond generic responsive design.
Page speed improvements: Each second of load time reduction typically produces measurable conversion improvement. Image optimization, server response time optimization, JavaScript optimization all matter.
Ad-to-landing-page message match: The landing page should fulfill what the ad promised rather than requiring users to navigate to find what attracted them to click.
Trust signal optimization: Bangladesh-specific trust elements including project licensing information, RAJUK/RDA approvals where relevant, established developer credentials, project completion track record, customer testimonials, contact information prominence.
Clear conversion path: Single primary action prominently visible. Multiple competing CTAs producing decision paralysis or weak primary action eliminated.
Form optimization (covered as separate priority below).
Visual quality: Real estate is visual product. Quality imagery showing actual project (not stock photos), virtual tours where available, floor plans, location maps, amenity visualizations.
Expected impact: 15-30% CPL improvement is realistic for developers with poorly-optimized landing pages.
Priority 3: Lead form optimization.
Forms capture the leads or fail to. Form improvements affect the final conversion step.
Specific tactics:
Field minimization: Most real estate lead forms request more information than necessary for initial qualification. Phone number, name, project interest, budget range — limited initial capture with progressive disclosure for additional information after engagement.
Mobile-friendly field types: Numeric keyboard for phone numbers, appropriate input types for each field, mobile-optimized layouts.
Phone-first capture: For Bangladeshi context specifically, phone number is more valuable than email for follow-up via WhatsApp and direct call. Forms making phone primary rather than email perform better than email-primary forms.
Bangla input support: Forms accepting Bangla characters in name fields don’t exclude Bangla-keyboard users.
WhatsApp alternative to form: For audiences preferring WhatsApp over form filling, prominent click-to-WhatsApp option captures leads that wouldn’t have filled forms. This often produces leads at lower CPL than form completion.
Value exchange clarity: What does the user get for providing their information? Brochure download, callback scheduling, exclusive pricing information, site visit booking — clear value justifies the information request.
Trust elements near form: Why is this information safe to provide? Privacy assurance, developer credibility, contact information for verification.
Expected impact: 10-25% CPL improvement from form optimization specifically, often producing compounding effects with other interventions.
Priority 4: Creative refresh and testing.
Creative that has been running too long without testing typically produces diminishing returns. Systematic creative testing identifies higher-performing variants.
Specific tactics:
Project-specific creative rather than generic developer creative: Each project warrants specific creative communicating what differentiates it rather than generic developer messaging.
Audience-segment-specific creative: Different audience segments warrant different creative addressing what matters to each segment specifically. NRB audiences need different creative than domestic Dhaka audiences than upcountry audiences.
Video creative testing: Video typically outperforms static images for real estate. Project walkthroughs, neighborhood context, customer testimonials.
Format variation testing: Different platforms benefit from different creative formats. Carousel ads versus single image versus video versus collection ads.
Authentic versus polished aesthetic testing: Authentic-feeling creative (real footage of actual projects, real customers, real situations) often outperforms heavily-produced creative on social platforms.
Bangla versus English creative for relevant audiences: Language match to audience preference affects engagement and conversion.
Hook and opening variation: First 3 seconds of video creative substantially affects watch-through. Testing different openings reveals what works.
Call-to-action variation: Different CTAs perform differently. “Book Site Visit” versus “Get Brochure” versus “WhatsApp Us” versus “Get Pricing” — each represents different commitment level and audience response.
Expected impact: 15-30% CPL improvement from systematic creative testing over 3-6 months as testing reveals what works.
Priority 5: Conversion tracking sophistication.
Better tracking enables better optimization. Most developers operate with conversion tracking that limits platform optimization capability.
Specific tactics:
Meta Conversion API (CAPI) implementation: Server-side conversion data flow that’s more reliable than browser-based pixel tracking alone. Particularly important for iOS users where browser tracking is limited.
Google Enhanced Conversions: Similar server-side conversion enhancement for Google Ads optimization.
Quality-weighted conversion values: Sending different conversion values for different lead qualities rather than treating all leads as equivalent. Higher values for qualified leads, lower values for unqualified leads. The platforms optimize toward total conversion value rather than just conversion count.
Site visit tracking as conversion: For most real estate, site visit represents stronger conversion signal than form fill. Tracking site visits as conversions (where possible) optimizes campaigns toward actual purchase progression rather than just initial interest.
CRM integration for offline conversion tracking: When leads become qualified, become site visitors, become customers — feeding these downstream events back to ad platforms via offline conversion uploads enables platform optimization toward business outcomes rather than just initial leads.
Expected impact: 10-30% CPL improvement from better conversion tracking enabling better platform optimization. The improvement compounds over months as platforms learn from better signal.
Priority 6: Channel mix rebalancing.
Budget allocation that reflects current channel performance rather than historical patterns.
Specific tactics:
Performance analysis by channel: True CPL and true cost per qualified lead by channel, not just nominal CPL.
Budget reallocation toward better-performing channels: Shifting budget from underperforming channels to better-performing channels.
Channel expansion into underutilized opportunities: YouTube and Google Search for high-intent capture often underutilized relative to potential. Real estate listing platform optimization often underexploited.
WhatsApp integration as conversion channel: Routing more inquiry through WhatsApp where it produces better conversion than form fills.
Expected impact: 10-25% CPL improvement from optimal channel mix versus suboptimal mix.
Priority 7: Lead handling improvements.
Marketing CPL is determined partly by what marketing produces and partly by what operations does with what marketing produces. Lead handling improvements increase effective lead value, reducing effective CPL.
Specific tactics:
Response time improvement: Lead response within minutes rather than hours. Speed-to-lead substantially affects conversion to qualified opportunities.
Professional sales engagement: Sales conversation quality affecting whether leads progress or disappear.
Systematic nurture for not-yet-ready leads: Long sales cycles in real estate mean leads who aren’t ready now may be ready in 6-12 months. Systematic nurture maintains relationships rather than losing leads to inactivity.
Site visit conversion focus: The actual goal is site visits, not just leads. Lead handling that systematically converts leads to site visits produces better effective CPL than handling that lets leads dissipate.
WhatsApp-based sales engagement: As covered in WhatsApp Commerce: Selling Through Conversations, WhatsApp-based real estate sales conversations require specific discipline that affects conversion substantially.
Expected impact: 15-30% improvement in effective lead value through better handling, which translates directly to improved effective CPL.
Beyond individual interventions, the sequence matters. The order of implementation affects what works and how quickly results materialize.
Phase 1 (Months 1-2): Foundation.
Establish reliable measurement and tracking. Without accurate measurement, optimization operates blind.
Implement Meta CAPI and Google Enhanced Conversions. Set up CRM integration for offline conversion tracking. Audit current attribution to identify measurement gaps. Document current performance baseline across channels, campaigns, audiences, creative.
The foundation work feels less satisfying than running campaigns differently, but interventions on weak foundations produce unreliable results that waste subsequent work.
Phase 2 (Months 2-4): High-impact interventions.
Begin systematic improvement work focusing on highest-impact opportunities identified through diagnosis.
Audience targeting refinement using improved data. Landing page optimization beginning with most-trafficked landing pages. Lead form optimization. Initial creative testing pipeline.
The phase 2 work typically produces visible CPL improvements within 4-8 weeks of implementation as the changes take effect and platforms learn from improved signals.
Phase 3 (Months 4-6): Systematic optimization.
Build sustained optimization disciplines based on accumulated learning from phase 2.
Ongoing creative testing pipeline. Continued landing page refinement. Channel mix rebalancing based on accumulated performance data. Lead handling improvements integrated into operational workflows.
The phase 3 work produces compounding improvements as multiple optimizations combine. The 50% CPL reduction (where achievable) typically emerges by this phase rather than from individual interventions.
Phase 4 (Months 6+): Ongoing discipline.
Sustained CPL optimization as ongoing operational capability rather than as project.
Continuous testing and improvement. Quarterly strategic reviews assessing performance trends. Adjustment to changing platform dynamics and competitive landscape. Talent development ensuring capability sustains over years.
The sustained discipline produces continuing improvement rather than capturing point-in-time gains. The brands that maintain this discipline see CPL continue improving while competitive intensity in real estate continues increasing — competitive advantage that compounds.
Several Bangladesh-specific factors affect how this work plays out:
The seasonal patterns in Bangladeshi real estate.
Different periods produce different real estate buyer behavior. Festival periods (around Eid particularly) produce different buying patterns than non-festival periods. End of fiscal year affects some buyer categories. NRB buyer patterns reflect remittance cycles and return-to-Bangladesh visits.
The CPL optimization should account for these patterns rather than expecting uniform performance across the calendar.
The NRB segment specific dynamics.
NRB buyers as covered in NRB Property Buyer Targeting represent specific segment with different acquisition economics than domestic buyers. NRB CPL can be higher than domestic CPL but produces higher-value transactions; the math may justify higher CPL for NRB segment.
The long sales cycle affecting attribution.
The 90-540 day buyer journey for Bangladeshi real estate makes attribution complicated. Standard 28-day attribution windows miss substantial portions of actual conversion. The CPL math should account for the extended timeline.
The competitive intensity varying by location and project category.
Different Dhaka submarkets and different project categories have different competitive intensity. Premium projects in Banani/Gulshan face different competitive landscape than mid-market projects in suburbs. The realistic CPL benchmarks vary substantially.
The WhatsApp commerce reality.
As covered earlier, WhatsApp routes substantial portions of real estate inquiry. Optimization should consider WhatsApp paths alongside form-based capture.
The trust signal patterns specific to Bangladeshi buyers.
Local trust signals affect real estate marketing substantially. RAJUK/RDA approval visibility, established developer credentials, project completion track record, customer testimonials matter more for Bangladeshi audiences than international trust signals.
A Bangladeshi real estate developer operating CPL optimization seriously has:
Sophisticated conversion tracking including CAPI, Enhanced Conversions, and CRM-based offline conversion uploads enabling platform optimization toward actual qualified leads rather than just initial form fills.
Refined audience targeting using lookalike audiences from actual buyers, behavioral targeting based on real estate engagement signals, geographic precision at neighborhood level, and exclusions for unqualified segments.
Mobile-first landing pages optimized for Bangladesh’s network and device realities with appropriate trust signals, clear conversion paths, and minimal friction.
Optimized lead capture forms with field minimization, mobile-friendly design, phone-first capture, WhatsApp alternatives, and clear value exchange.
Systematic creative testing pipeline producing project-specific, audience-segment-specific creative refreshed regularly based on testing data.
Channel mix calibrated to current performance data rather than historical patterns, with budget allocation reflecting where leads are actually most efficient.
Lead handling discipline with rapid response, professional sales engagement, systematic nurture for long-cycle leads, and integration with broader sales operations.
Cross-channel attribution combining platform-reported data with CRM data and incrementality testing where appropriate.
Ongoing testing and improvement discipline sustained over months and years rather than as discrete projects.
The cumulative effect: CPL substantially below what competitors operating without this discipline achieve, lead quality substantially above what wasteful marketing produces, and unit economics that work in current competitive environment.
Most Bangladeshi real estate developers operate substantially below this standard. The brands that build proper optimization capability typically produce CPL and lead quality that brands operating informally can’t match through additional budget alone.
For developers currently paying more than they think they should for leads, the realistic starting point is honest diagnosis of where current inefficiencies are. Most developers discover multiple inefficiencies operating simultaneously, with substantial cumulative improvement opportunity that systematic work can address.
The strategic question worth being explicit about: are you accepting current CPL as fixed cost of doing business, or are you investing in optimization capability that compounds value over years? The first approach typically produces increasing budget requirements as competition pushes acquisition costs higher. The second approach builds capability that produces sustainable advantage as competitive intensity continues increasing.
The 50% CPL reduction the title promises is realistic for developers currently operating with typical Bangladeshi real estate marketing inefficiencies. Achieving it requires systematic work over 3-6 months addressing multiple inefficiencies simultaneously. Brands committed to this work produce results that justify the investment; brands hoping for shortcuts typically don’t see the improvement.
The competitive position this work produces: real estate marketing that becomes more efficient as competitors continue paying premium prices for inefficient lead generation. The CPL differential between developers operating with optimization discipline and those operating without it becomes structural competitive advantage that ad spend alone can’t replicate.
The honest framing for Bangladeshi developers evaluating their lead generation: most current CPL reflects accumulated inefficiencies rather than fundamental cost. The systematic work to address those inefficiencies produces substantial improvement. The brands willing to make the investment in this work build positions worth building. The brands that continue paying premium prices for inefficient lead generation continue subsidizing competitors who operate more efficiently.
