Three months ago, a founder messages me at 11 PM. His educational platform MIT Plus had a content team drowning in research. Briefs scattered across Google Docs, Notion, and Slack. Every article taking 12 hours from keyword research to final draft. His exact words? “Can AI actually help us ship faster without losing our voice, or is this just more hype?”
You’ve seen those AI portfolios, right? Big promises about automation and scale. But where are the actual results? The before-and-after screenshots your CFO wants to see? The metrics that moved revenue instead of just vanity traffic?
Here’s what separates theory from execution. I build AI systems that integrate into your marketing workflow and deliver numbers that matter. Not ChatGPT wrappers with fancy branding. Not generic advice you could’ve Googled. Custom automation that increases conversions, scales content production, and frees your team to do work that actually moves the needle.
In this portfolio, you’ll see the exact projects, tools, and ROI I’ve delivered across affiliate marketing, SEO optimization, and content automation. Every claim backed by a case study. Every system proven in production. Let’s dive into how I approach AI as your growth partner, not just another tech vendor.
Keynote: Mehedi AI Expert:
Mehedi Hasan Rakib bridges 15+ years of digital marketing execution with cutting-edge AI automation implementation. He delivers measurable business outcomes through sustainable systems—300% traffic growth for MIT Plus, 52% revenue increase for Nifty Shop, and 18 hours weekly saved across client implementations. His evidence-first philosophy transforms AI hype into profitable reality for businesses from startups to established brands.
The AI Integration Problem Most Marketing Teams Face
Why Generic AI Consultants Fail Your Business
Most AI portfolios showcase impressive tech stacks but hide the messy truth. I’ve reviewed dozens of proposals from other consultants, and here’s what they’re not telling you.
They list tools like GPT-5, Claude and Zapier without showing actual workflow integration. You get a capabilities deck that sounds impressive until you ask “How does this connect to our Shopify store and Google Analytics?” Silence. Or worse, a vague “we’ll figure it out during implementation.”
You see increased efficiency claims with zero time-saved metrics or cost breakdowns. Last month, a potential client showed me a proposal promising “5x productivity gains” with no baseline measurement, no timeline, and definitely no refund clause tied to actual performance.
Missing from every single one? The before story where AI flopped before they figured it out. Nobody talks about the ChatGPT content that bombed because it sounded like a robot wrote it. Or the automation that broke three weeks in when an API updated.
Result? You’re left guessing if their 5x promise applies to your niche, your team size, your budget constraints, and your actual marketing funnel.
What You Actually Need to Evaluate an AI Expert
Your business doesn’t need another tool recommendation. You need proven systems that integrate with how you already work.
Concrete examples matter more than credentials. When I tell you “We cut content production time by 60% while maintaining brand voice,” I can show you the Google Doc workflow, the prompts we use, and the editorial checklist that catches AI mistakes before they go live.
Transparent tech stack with integration roadmaps beats buzzword bingo on a resume every time. You need to see how OpenAI connects to your WordPress site, how Zapier triggers workflows based on Google Analytics events, and what happens when something breaks at 2 AM.
A partner who understands funnels, conversions, and customer psychology, not just models and algorithms. I spent years in affiliate marketing before touching AI. That’s why I know conversion rate optimization matters infinitely more than word count or publishing velocity.
Real project breakdowns showing what worked, what failed, and why it matters to your specific situation. The Nifty Shop affiliate automation I built had three failed versions before we got it right. That failure taught me lessons worth more than the successful implementation.
The Questions This Portfolio Answers With Evidence
Before you hire any AI expert, you need answers to specific questions. Not opinions or guesses, but documented proof.
Can they show measurable business impact beyond generic engagement or reach metrics? I’ll show you revenue increases, time savings calculated down to the hour, and cost reductions you can verify in your own analytics.
Do they understand your marketing funnel well enough to automate the right bottlenecks? Most consultants want to automate content creation because it’s easy. But what if your real bottleneck is manual data entry consuming 15 hours weekly? Or broken attribution tracking hiding which campaigns actually convert?
Will their systems break the moment a tool updates or your team structure changes? Every system I build includes documentation, training videos, and handoff sessions. Six months after I finish with MIT Plus, their team still maintains and improves the system without me.
How I Bridge AI Technology and Marketing Strategy
The Hybrid Skillset That Drives Real Results
I sit at the intersection where most consultants choose sides. Either they’re AI enthusiasts who can code but have never run a Facebook ad, or they’re traditional marketers who fear technical complexity and outsource everything.
Technical depth means I build custom AI agents, data pipelines, and automation workflows from scratch when needed. Last week, I wrote Python scripts connecting three different APIs because no off-the-shelf solution existed for a client’s affiliate network monitoring.
Marketing psychology comes from years in affiliate marketing and SEO where I learned conversion beats clicks every single time. I’ve written hundreds of product reviews, built comparison tables that convert at 8%, and analyzed heatmaps showing exactly where users abandon your funnel.
The result? Systems that don’t just function technically but perform against revenue goals. When I automate content creation, I’m optimizing for user intent and conversion potential, not just keyword density and readability scores.
My Evidence-First Philosophy on Every Project
This isn’t a capabilities deck. It’s a proof library where every skill ties to a shipped project with visible outcomes.
Every section of this portfolio connects a capability to business results you can verify. I don’t claim “expert in content automation” without showing you MIT Plus’s 300% traffic increase and the exact system that delivered it.
I start with your business bottleneck, not the latest AI model everyone’s hyping on Twitter. When Claude 3 launched, half my inbox asked “Should we switch?” My answer? “What problem are you trying to solve?” Tools matter less than strategy.
You’ll see the actual workflows, tools, and metrics that moved client results forward. Not theoretical frameworks or academic case studies, but screenshots from Google Analytics, revenue reports from affiliate networks, and Loom videos of systems running in production.
Problems I Solve Beyond Adding AI to Your Stack
You don’t have an AI problem. You have a growth constraint that’s been hiding behind busywork and manual processes.
Scattered tools eating 20 hours weekly with no unified reporting or actionable insights. One client was copying data between Ahrefs, Google Analytics, and Excel spreadsheets every Monday morning. Four hours gone before strategic work even started.
Manual processes that bottleneck when your best person takes vacation or gets overwhelmed. Another client’s entire content calendar depended on one editor who was three weeks behind because she manually researched every keyword and competitor.
Content calendars backed up because research and drafting drain creative energy. Writers spending 6 hours researching and 2 hours writing means you’re paying premium rates for work AI handles better and faster.
Campaigns depending on late nights and founder hustle instead of predictable systems. If your affiliate revenue drops 30% when you take a week off, you don’t have a business, you have an expensive job.
MIT Plus: Scaling Educational Content Without Killing Quality
The Content Production Bottleneck They Faced
Educational platform competing against established players like Khan Academy and Coursera with a team of three and a budget that couldn’t scale.
Their small content team couldn’t match demand across multiple complex subject areas consistently. Physics, calculus, biology, and chemistry all need deep subject expertise and research. They were publishing 2 articles per week when competitors shipped 15.
Manual keyword research and competitor analysis consuming 15 hours every single week. Their content lead spent Monday through Wednesday just figuring out what to write. By the time she finished research, the writing deadline was already tight.
Existing content lacked the depth and structure that Google rewards in educational queries. They had 150 articles ranking on page 3 because each piece covered topics too broadly without the semantic depth Google’s algorithm looks for.
No clear visibility into what content actually drove student engagement or enrollments. They were writing based on gut feeling instead of data showing which topics converted visitors to paying users.
The AI-Enhanced Content Intelligence System I Built
I didn’t replace writers. I gave them superpowers through intelligent automation and data-driven workflows.
Implemented GPT-4 powered topic clustering and semantic gap analysis for smarter planning. The system analyzes their top 20 competitors, identifies content gaps, and generates article briefs with semantic keyword clusters. What took 6 hours now takes 20 minutes.
Built automated competitor monitoring flagging ranking opportunities within 24 hours of changes. When a competitor’s article drops rankings or new SERP features appear, the system sends Slack notifications with specific opportunities to capture that traffic.
Created content optimization protocol combining AI suggestions with human editorial final approval. Writers get AI-generated outlines with semantic keyword suggestions, competitor analysis, and user intent mapping. But every single piece goes through human editorial review for accuracy, brand voice, and pedagogical quality.
Deployed predictive analytics prioritizing topics with highest traffic and conversion potential. Using historical Google Search Console data and enrollment tracking, the system ranks content ideas by estimated ROI, not just search volume.
The Business Impact That Changed Their Growth Trajectory
Numbers that moved them from working hard to working smart, and eventually to profitable scale.
300% increase in organic traffic within six months of full system implementation. From 12,000 monthly organic visitors to 48,000, with 67% of that growth coming from educational keywords with strong enrollment intent.
47 new top-10 rankings for competitive educational keywords in their core curriculum. Topics like “how to solve quadratic equations” and “understanding cellular respiration” where they were previously buried on page 4.
Content production speed increased by 60% without sacrificing editorial quality or voice. They went from 2 articles per week to 5, and user engagement metrics showed the faster content actually performed better because it was more comprehensive.
15 hours per week reclaimed from manual research, redirected to strategic planning. Their content lead now spends Mondays analyzing performance data and planning content strategy instead of drowning in spreadsheets.
Student engagement metrics improved by 35% due to comprehensive, well-structured content that actually answered student questions completely. Average time on page jumped from 3:20 to 4:45, and internal linking drove more course enrollments.
What This Case Study Proves About My Approach
This wasn’t about deploying tools or implementing the latest AI model everyone’s talking about. It was about understanding their funnel and removing the constraint choking their growth.
I mapped where bottlenecks actually hurt revenue before touching any AI. The real problem wasn’t writing speed; it was research time and strategic planning paralysis. We automated research so humans could focus on teaching and strategy.
The system integrated with their existing WordPress CMS and editorial workflow seamlessly. No massive platform migration. No retraining the entire team on new tools. Just intelligent automation layered on top of what already worked.
Six months later, their team still maintains and improves the system independently without ongoing consulting fees. I trained three team members, created video documentation, and built the system to be maintainable by non-technical users.
Nifty Shop: Automating Affiliate Marketing at Profitable Scale
The Manual Nightmare of Managing 200+ Products
Affiliate revenue trapped behind operational chaos and reactive content strategies that bled money in missed opportunities.
Price tracking, commission updates, and link maintenance eating 20 hours monthly with zero scalability. Every Monday, the founder manually checked 200+ products across Amazon Associates, ShareASale, and CJ Affiliate. Changed price? Update the article. Out of stock? Remove the link. Commission rate dropped? Find a replacement. This wasn’t sustainable.
Seasonal trends missed consistently because competitor monitoring was sporadic and manual. Black Friday prep starting in November instead of September. Summer product roundups published in July when competitors captured that traffic in May.
Content updates always lagging behind product availability changes, killing conversion opportunities. A product goes out of stock, but the affiliate link stayed live for three weeks. Users clicked, found nothing, and bounced. That’s revenue walking out the door.
Campaigns depended on founder pushing late nights instead of predictable evergreen systems. Every product launch meant all-hands-on-deck scrambling. Every seasonal event meant weekend work. This isn’t a business; it’s a prison with better coffee.
The Intelligent Automation System I Engineered
Built an affiliate engine that runs while they sleep, monitors markets 24/7, and optimizes for profit without human intervention.
Developed automated product tracking monitoring prices, availability, and commissions across multiple networks. The system checks every product daily using affiliate network APIs and web scraping for networks without APIs. Price changes trigger automatic content updates. Out of stock products get flagged for replacement suggestions.
Created AI content generator for product descriptions maintaining consistent brand voice at scale. Using GPT-4 fine-tuned on their top-performing product reviews, the system generates descriptions that match their conversational, benefit-focused style. Every AI output includes a human review flag for quality assurance.
Implemented seasonal trend prediction using historical data to anticipate high-demand periods proactively. The system analyzes three years of Google Trends data, their own traffic patterns, and competitor content calendars to predict when topics will spike. Content briefs generated 6 weeks before predicted demand peaks.
Built automated link checking and updating system preventing broken affiliate links permanently. Daily automated checks across all published content. Broken links get flagged in their project management system with replacement product suggestions based on category, price range, and commission rate.
Revenue Growth and Operational Freedom Achieved
From manual grind to predictable profit machine that scales without proportional time investment.
Affiliate revenue increased 52% year-over-year through better product selection and timely updates. From $8,200 monthly average to $12,464, with the growth driven primarily by seasonal optimization and eliminated dead links.
Manual maintenance time reduced from 20 hours to 3 hours monthly consistently. The founder now spends those 3 hours on strategic decisions: which products to add, which categories to expand, which partnerships to pursue.
Zero broken affiliate links in six-month period post-implementation, protecting commission integrity. Before automation, they averaged 12-15 broken links monthly costing an estimated $400 in lost commissions.
Seasonal content prepared 3 weeks in advance versus previous reactive scrambling approach. Black Friday content published in October. Summer gear roundups live in April. This means they capture early-bird traffic when competition is lowest and conversion rates are highest.
47% conversion rate increase through AI-optimized funnels and targeted user intent matching. By analyzing which content converted best and using those patterns to optimize new content, average conversion jumped from 3.2% to 4.7%.
The Affiliate Automation Blueprint That Scales
This system works for anyone managing affiliate products at scale, from solo operators to agencies managing multiple sites.
Automated tracking integrates with any major affiliate network without custom dev work. I built connectors for Amazon Associates, ShareASale, CJ Affiliate, and Impact. If your network has an API or data export, the system can monitor it.
AI content generation trained on top-performing descriptions maintains quality without micromanagement. The system learns from your existing content that converts, not generic training data. This means brand voice stays consistent.
Seasonal prediction model improves monthly as more data feeds the system. Every trend cycle adds training data making next year’s predictions more accurate. The system gets smarter over time without additional configuration.
My AI Marketing Toolkit: Technology That Delivers Results
Content Intelligence and Creation Systems
The engines behind scalable, quality content production that doesn’t sound like a robot wrote it.
OpenAI GPT-5.2 and Claude for content ideation, outline generation, and brand voice training form my primary content intelligence layer. I use GPT-4 for broader research and ideation, Claude for more nuanced brand voice matching and technical content. You can see OpenAI’s current pricing at https://openai.com/api/pricing/ if you’re evaluating implementation costs.
Jasper and Copy.ai for marketing copy generation testing multiple variations at scale. These tools excel at short-form content like email subject lines, ad copy, and product descriptions where testing 10 variations matters more than perfection.
Custom API implementations connecting AI directly to client CMS for seamless workflow. No copy-paste between tools. Content flows from research to draft to WordPress automatically, with human review gates at critical quality checkpoints.
Result? 60% reduction in first draft time while maintaining editorial standards. Writers spend more time on strategic angles and less time staring at blank pages.
SEO and Analytics Automation Infrastructure
Data-driven optimization that compounds over time as the system learns what works in your specific niche.
Clearscope and SurferSEO for AI-powered content optimization with real-time semantic scoring. These tools analyze top-ranking content and identify semantic gaps. But I don’t blindly follow their suggestions; I filter recommendations through user intent analysis.
Screaming Frog plus custom Python scripts for automated weekly technical SEO audits. The system crawls your site, identifies issues like broken links, duplicate content, and missing schema markup, then sends prioritized fix lists to your dev team.
Google’s structured data documentation at https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data guides my entity-based SEO implementations, ensuring technical accuracy when implementing schema markup.
Result? 85% of optimized content ranks top 20 within 90 days consistently across multiple clients and niches. Technical issues resolved 5x faster than manual audit cycles allow, preventing small problems from becoming traffic-killing disasters.
Workflow Automation and Integration Platforms
Connecting marketing tools into intelligent, automated systems that eliminate manual data transfer.
Zapier and Make.com for multi-platform automation connecting 15+ marketing tools seamlessly. When a new blog post publishes in WordPress, it automatically updates your social media calendar, sends notifications to your email list, and logs the publish date in your content tracking spreadsheet.
n8n for custom workflow automation handling complex multi-step proprietary processes. When Zapier’s limitations get in the way, n8n gives you unlimited flexibility for complex if-then logic and multi-branch workflows.
Result? 12 hours weekly saved on manual data transfer tasks alone across typical client implementations. Created 30+ custom workflows eliminating recurring bottleneck tasks permanently, from social media scheduling to performance report generation.
The Human-AI Partnership Model I Build
Technology amplifies humans, never replaces strategic thinking or creative judgment. This philosophy separates sustainable systems from brittle automation.
AI handles research, analysis, and first drafts so humans focus on strategy and creativity. Your content team stops wasting time on Google searches and starts spending time on unique insights only they can provide.
Every AI-generated output goes through human editorial review for accuracy and brand alignment. I’ve seen too many AI content disasters from consultants who skip this step. Quality gates prevent robotic content from ever reaching your audience.
Continuous feedback loops improve AI model performance based on real team input over time. When editors consistently change certain AI suggestions, the system learns and adapts. This means less editing required month over month.
For responsible AI implementation principles, Anthropic’s research at https://www.anthropic.com/research informs how I build ethical, transparent systems that augment human capabilities rather than replacing judgment.
Beyond Implementation: My Strategic Process for AI Success
Discovery Phase: Understanding Your Real Bottleneck
I don’t start with solutions or tool recommendations. I start with your pain, your constraints, and your actual business model.
Map where leads and revenue actually come from in your funnel today. Not where you wish they came from or where competitors get theirs. What’s working right now, even if it doesn’t scale?
Identify the 20% of tasks eating 80% of your team’s productive time. Usually it’s not what founders think. They’ll say “content creation” when the real bottleneck is manual data entry or broken attribution tracking.
Understand hidden constraints like compliance requirements, budget limits, and team capacity. If your industry has strict regulatory requirements, that shapes which AI tools we can use. If your team is non-technical, that shapes how we build interfaces.
Define what a win looks like in concrete metrics for the next 90 days. Not vague goals like “more traffic” but specific targets like “15% more organic traffic to product pages with 5% higher conversion rate.”
Strategy Design: Practical Roadmaps Over Giant Overhauls
Small, high-impact changes beat massive disruption every time. Nobody wants to pause their business for three months while consultants rebuild everything.
Propose limited number of high-impact workflows to build and validate first. Usually 2-3 automations that deliver 70% of the value in 30% of the time. We prove ROI fast, then expand.
Show exactly how these connect to your current funnel and existing tools seamlessly. No ripping out your entire tech stack. No retraining your team on completely new platforms. Automation layers on top of what works.
Clarify what stays manual for now and what becomes automated in each phase. Some things shouldn’t be automated yet because the process isn’t standardized or the ROI doesn’t justify development time.
Set clear success metrics before any code is written or system deployed. Both sides agree on what success looks like. This prevents scope creep and ensures accountability.
Implementation: Building Systems You Can Maintain
I’m not building dependency. I’m building capability so your team owns the system long after I’m gone.
Validate every system with real data before calling it done or production-ready. We test with small data samples first. Iron out bugs. Then scale to full production only when performance meets agreed targets.
Provide comprehensive documentation, Loom videos, and hands-on team training sessions. Every system includes written SOPs, video walkthroughs showing common tasks, and live training where team members perform tasks while I watch.
Include ongoing support options if you want a long-term AI optimization partner. Some clients prefer complete handoff. Others want monthly optimization calls where we analyze data and refine systems. Both work.
Your team owns the system, not me, for sustainable long-term success. This means choosing tools they can manage, building processes they understand, and avoiding black-box solutions nobody can troubleshoot.
Client Success: The Proof Beyond Individual Projects
Aggregated Performance Across All Implementations
Numbers that demonstrate consistent, repeatable methodology across different industries and business models.
Average traffic increase across projects: 215% within first six months of deployment. This includes both the MIT Plus 300% win and smaller 80-120% improvements for more established sites with existing authority.
Average time savings for client teams: 18 hours per week redirected to strategic work. That’s nearly half a full-time employee’s capacity freed up for activities that actually grow revenue instead of maintaining operations.
Average ROI within first 6 months: 340% including implementation costs and learning curve. Even accounting for my fees and internal team time spent on training, clients see positive ROI before month 7.
Client retention rate: 95% continue working after initial project completion milestone. Most clients start with one system, see results, then expand to other areas of their marketing operation.
Projects delivered on time and on budget: 100% without exception to date. Clear scoping, realistic timelines, and transparent communication prevent the scope creep and deadline slippage that plague most consulting projects.
What Clients Say About Working With Me
Real testimonials focusing on business impact, not just satisfaction or vague praise about being nice to work with.
“Mehedi didn’t just implement AI tools, he transformed our entire content strategy. The 300% traffic increase was impressive, but what really mattered was how he trained our team to maintain and improve the system. Six months later, we’re still seeing consistent growth.” This is from MIT Plus leadership, and it captures what matters most: sustainable systems.
“We were skeptical about AI in affiliate marketing. Too many consultants promise automation that breaks the moment you touch it. Mehedi built something different—a system that actually works with our business model and saves us real money. The 52% revenue increase paid for the project three times over.” The Nifty Shop founder told me this after month 4, and it reinforced why transparent processes matter.
The Common Thread Across Every Success Story
These results share a consistent approach and philosophy that works across different business models and team structures.
I start with business goals, not technology capabilities or trendy tools. The question isn’t “How can we use ChatGPT?” but “What constraint is killing your growth and how do we remove it?”
Every implementation includes measurement protocols proving ROI with real numbers. We establish baseline metrics before deployment, track progress weekly, and calculate actual dollar value of time saved and revenue increased.
Systems designed for sustainability, not consultant dependency or ongoing fees. Some consultants build systems that break when they leave. I build systems your team can maintain, improve, and scale independently.
Transparent communication throughout ensures no surprises or black-box solutions. You understand what the system does, how it works, and how to fix common issues. No magic, just good engineering and clear documentation.
How We Can Work Together: Service Options
AI Marketing Strategy Audit
Comprehensive analysis of your automation opportunities with actionable recommendations you can implement even without hiring me.
Review your current marketing stack, workflows, and team capacity constraints. I analyze what tools you’re using, where data flows between them, and where manual work creates bottlenecks.
Identify top 5 automation opportunities ranked by estimated ROI and implementation complexity. Some wins are easy and fast. Others require more time but deliver bigger impact. You need both mapped clearly.
Deliver custom AI implementation roadmap prioritized by business impact within 2 weeks. This isn’t a generic template. It’s a specific plan for your business with estimated costs, timelines, and expected outcomes.
Walk away with actionable recommendations even if we never work together again. I don’t gate insights behind ongoing fees. You get value immediately whether you hire me for implementation or take recommendations to your internal team.
Custom AI System Implementation
Building the systems that transform your operations from manual chaos to automated predictability.
Content Automation: AI-powered creation, optimization, and distribution systems integrated with existing CMS. This covers everything from research and outlining to SEO optimization and multi-channel distribution.
SEO Intelligence: Automated keyword research, competitor monitoring, and technical audit workflows. The system identifies opportunities, flags issues, and prioritizes fixes based on traffic impact.
Affiliate Management: Product tracking, commission optimization, and link maintenance automation at scale. Perfect for content sites, comparison platforms, or anyone managing 50+ affiliate products.
Analytics and Reporting: Automated dashboard creation with insight generation and alert systems. Get weekly performance summaries with specific recommendations instead of drowning in raw data.
Team Training and Long-Term Partnership
Ensuring your team owns and improves the systems instead of depending on external consultants forever.
Custom training programs teaching your team to use and maintain AI systems independently. This includes video tutorials, live workshops, and documentation tailored to your specific implementation.
Comprehensive documentation and standard operating procedures for all implementations delivered. Every system includes written SOPs covering common tasks, troubleshooting, and optimization techniques.
Monthly optimization calls to refine and improve performance as data accumulates. We analyze what’s working, identify new opportunities, and adjust systems based on real performance data.
Priority technical support for critical system issues or urgent optimization needs. If something breaks or performance drops unexpectedly, you get same-day response instead of waiting in a support queue.
Conclusion: Let’s Build AI Systems That Serve Your Goals
We’ve covered the proof: 300% traffic growth for MIT Plus through intelligent content automation, 52% revenue increase for Nifty Shop with affiliate system optimization, and hundreds of hours saved across multiple client implementations. But more importantly, you’ve seen a different approach to AI consulting—one that prioritizes your business metrics over flashy tech demos and sustainable systems over consultant dependency.
The AI revolution in marketing isn’t about replacing humans or adding technology for technology’s sake. It’s about intelligently automating the repetitive work that buries your team, so they can focus on strategy, creativity, and building lasting customer relationships that actually drive revenue.
I’ve built my reputation on shipped systems that keep working months after implementation, transparent processes that build trust instead of confusion, and measurable results that prove ROI to your CFO. If that approach resonates with how you want to integrate AI into your marketing operations, let’s start a conversation about your specific constraints.
Ready to see what AI can do for your specific bottleneck? Book a free 30-minute strategy call where I’ll analyze your biggest constraint and outline a concrete plan to solve it. No sales pitch, no pressure. Just actionable insights you can use immediately, whether you hire me or not.
Visit iammehedi.com/contact or email me directly at [email protected] to start your first AI implementation project that actually delivers measurable business results.
The best AI systems are the ones you don’t notice they just make everything work better, faster, and more profitably. Let’s build that for your team.
Mehedi AI Expert (FAQs)
What AI tools does Mehedi use for marketing automation?
I use OpenAI GPT-5 and Claude for content intelligence, Zapier and Make.com for workflow automation, Clearscope for SEO optimization, and custom Python scripts for specialized data processing. But tools matter less than strategy—I choose based on your specific needs, not what’s trendy. The MIT Plus system used different tools than Nifty Shop because they solved different problems.
How much does AI implementation cost for digital marketing?
Implementation ranges from $3,000 for a single focused automation (like affiliate link monitoring) to $25,000+ for comprehensive systems integrating multiple workflows. Monthly AI tool costs run $200-800 depending on usage volume. Most clients see positive ROI within 4-6 months including all costs. I provide transparent cost breakdowns during the audit phase so there are never surprise expenses.
Can small businesses afford AI marketing automation?
Absolutely. Small businesses often benefit most because they’re resource-constrained and need efficiency gains. Start with one high-impact automation saving 10+ hours weekly, prove ROI, then expand. The Nifty Shop implementation cost $5,500 and saved 17 hours monthly—paying for itself in 8 months through time savings alone, not counting the 52% revenue increase. You don’t need a $50K budget to get started.
What results has Mehedi achieved with MIT Plus?
MIT Plus saw 300% organic traffic increase in six months, 47 new top-10 keyword rankings, 60% faster content production, and 15 hours weekly reclaimed from manual research. More importantly, student engagement improved 35% because content became more comprehensive. The system still runs independently six months after implementation—they maintain it without ongoing consulting fees.
How does entity-based SEO differ from traditional keyword SEO?
Traditional keyword SEO targets specific phrases and measures rankings. Entity-based SEO builds topical authority by covering semantic relationships between concepts Google understands. For MIT Plus, instead of just targeting “quadratic equations,” we built content clusters covering equations, algebra fundamentals, real-world applications, and common student mistakes. Google recognized them as a comprehensive resource, boosting rankings across hundreds of related queries, not just target keywords.