AI Marketing Solutions: Every Marketing Data Science Build, Mapped by the Problem It Solves
Six solution areas for SEO, Google Ads, paid social, e-commerce, content and measurement, all built on one foundation of predictive marketing analytics. Each solution diagnoses a specific problem in your data before any money moves. Find your area, then the build inside it.
Finds why rankings and organic revenue move, beyond what SEO tools can show.
Feeds Google Ads better value signals and finds where spend stops paying.
Keeps Meta and TikTok learning from clean signal and fresh creative.
Finds margin leaks in returns, discounts, stock and lapsed buyers.
Shows which content earns its cost, and what to write, refresh or retire.
Measures what marketing actually caused, across every channel.
Each build is a custom model on your own data, made with advanced data science, supervised and reviewed by me.
Career figures, not solution results. Every solution starts with an audit of what your data can actually support.
Solutions Diagnose. Services Deliver.
Running ads, publishing content and building links are activities. They only help once the real problem is known. Most problems that cost money don’t show up in a dashboard at all:
Find and size the problem
A custom model on your raw data shows what's actually happening, what it's costing, and what would fix it. Sometimes the honest finding is that your data can't support a model yet.
Do the work, guided by the finding
The SEO, Google Ads, paid social and e-commerce work that carries the fix into your accounts. See all services.
Intelligence-led marketing, one problem at a time
Your first-party data goes in; custom models find the problem and size it; the output flows into the tools where decisions are made; and every model has to beat a simple baseline before it touches budget.
Most businesses need two or three of these solutions, not all of them. The audit tells you which.
Find Your Starting Point From the Sentence You'd Actually Say
You don’t need to know the name of a solution. Find the problem that sounds like yours.
| What you'd say | Start with | Open |
|---|---|---|
| "Rankings dropped, but the SEO tools say everything is fine" | Organic Growth Intelligence | View |
| "CPA is on target, but profit keeps falling" | Customer LTV prediction | View |
| "Performance Max spends, and we can't see where" | Paid Search Intelligence | View |
| "Meta's numbers don't match our backend revenue" | Media Buying Intelligence | View |
| "Discounts bring orders, but margins shrink" | E-Commerce Intelligence | View |
| "We can't prove which content drives revenue" | Content Marketing Intelligence | View |
| "Every channel claims the same conversion" | Omnichannel Data Intelligence | View |
| "Acquisition is strong, but customers leave early" | Churn prediction | View |
Every AI Marketing Solution, and What Each One Does
All 40+ builds in one place, grouped by area. Each one is a custom model on your own data, made with advanced data science and supervised and reviewed by me. Click any build to read its detail page.
Predictive Intelligence
Custom models that score customer value, risk and likelihood before you spend, used by every other area.
Open PredictiveOrganic Growth Intelligence
Finds why rankings and organic revenue move, beyond what SEO tools can show.
Open Organic GrowthPaid Search Intelligence
Feeds Google Ads better value signals and finds where spend stops paying.
Open Paid SearchMedia Buying Intelligence
Keeps Meta and TikTok learning from clean signal and fresh creative.
Open Media BuyingE-Commerce Intelligence
Finds margin leaks in returns, discounts, stock and lapsed buyers.
Open E-CommerceContent Marketing Intelligence
Shows which content earns its cost, and what to write, refresh or retire.
Open Content MarketingOmnichannel Data Intelligence
Measures what marketing actually caused, across every channel.
Open Omnichannel DataHow to pick the two or three solutions you actually need
A short walkthrough of the seven areas, how the foundation models feed every channel, and why the work always starts with what your data can support.
These Solutions Stack in an Order, and the Order Matters
A model can only be as good as the data under it. Skipping a layer is the most common reason AI marketing projects disappoint.
Signal integrity
Clean, matched, de-duplicated conversion data. Every model downstream learns from this.
Customer models
Value, churn, intent and segments: the scores every channel decision uses.
Channel activation
Scores pushed into bidding, email, on-site and sales tools, where decisions happen.
Allocation & proof
Budget envelopes from marketing mix modeling, checked by incrementality tests.
What Every Engagement Here Has in Common
It starts with a data audit
Before any build, the audit checks what your data can actually support, and says so if the answer is "not yet".
The baseline has to be beaten
Every model is tested against a simple rule of thumb. If it can't beat it, it doesn't ship.
No performance guarantees
What's promised is a sized, honest finding and a model that's checked, never a fixed result.
The limits are written down
Every solution page states its honest limit, and every delivered model comes with its own.
Who These Marketing Solutions Are Built For
Delivered remotely from Lahore for brands across Pakistan, the UK, USA, UAE, Canada and Turkey, with every model fitted per market. Working hours overlap with the Gulf and UK, and partly with US mornings.
Established e-commerce and DTC
With enough order history for customer value and churn models to learn from.
Growth-stage SaaS and B2B
Where lead quality and pipeline value matter more than lead volume.
Enterprise teams and agencies
Multi-channel budgets that need measurement that doesn't rely on platform figures.
Not for brand-new businesses
With little data yet, a solid service setup comes first; the audit will say so.
How AI Agents Keep These Solutions Running
A SaaS tool is someone else’s generic model. An AI agent is your own model, kept running between reviews. The agents are autonomous, built from data science and marketing work, and every action is reviewed. More on the AI agents hub.
What the agents watch
- Watch every model for drift as your business changes
- Flag unusual weeks in spend, traffic or revenue as they happen
- Check every data feed for broken tracking and missing days
- Refresh scores on schedule and push them where they're used
What stays with a person
- Defining the business objective a model optimises for.
- Judging drift. When a model needs refitting, or retiring.
- Owning privacy and identity. What may be linked, and on what consent.
- Deciding to stop spend. The call no agent makes.
AI Marketing Solutions: Frequently Asked Questions
What are AI marketing solutions?
AI marketing solutions here are custom models built on your own marketing and customer data, each designed to diagnose and size one specific problem, such as wasted ad spend, falling rankings or customers leaving early.
What is the difference between Solutions and Services?
Solutions diagnose: they find and size the problem. Services deliver: they carry the fix into your SEO, Google Ads, paid social or store.
Which solution should we start with?
Start from the problem you’d describe in your own words (see the starting-point table). The data audit then confirms which two or three builds your data can support.
Do we need all seven areas?
No. Most businesses need two or three. Predictive Intelligence is the shared foundation; the rest depends on where you spend.
What is predictive marketing analytics?
Predictive marketing analytics uses your history to score what’s likely next: a customer’s value, their risk of leaving, or their chance to buy, so decisions happen before money is spent.
What is marketing data science?
Marketing data science applies statistics and machine learning to marketing questions that dashboards can’t answer, like what a channel actually caused or which customers are worth acquiring.
Are these SaaS tools or custom models?
Custom models on your raw data, made with advanced data science and supervised and reviewed by me. You keep the models and the outputs.
Why does everything start with a data audit?
Because a model is only as good as its data. The audit shows what your data can support today, and sometimes the honest answer is “fix tracking first”.
What if a platform feature would do the job instead?
Then you’ll be told to use it. A custom build is only worth it where it beats what the platform already offers.
Can you guarantee results?
No. What’s offered is an honest, sized finding and models tested against a simple baseline before they touch budget.
Do you work with businesses outside Pakistan?
Yes, remotely, for brands across Pakistan, the UK, USA, UAE, Canada and Turkey, with each model fitted per market.
Performance marketer applying data science to marketing problems. 12+ years in digital marketing, 100+ clients across 15 industries and 6 markets, a Master's in Computer Science and MPhil / MS Data Science (AI). Every solution is designed, checked and reviewed by me personally, with no hand-off to an account manager.
Where to Go Next
Start With What Your Data Can Actually Support
A data audit shows which two or three solutions fit your business, what each problem is costing, and what to build first, in plain language.