AI · Automation · Data
Dashboards, Analytics, Forecasting and Recommender Systems
I turn your numbers into a clear picture, a forecast, and a system that knows what to offer which customer.
What I build
For businesses that already have their data in order. I turn your figures into a picture you understand at a glance, and into forecasts that look ahead - so decisions rest on numbers instead of gut feel.
The same data can go one step further: I build recommendation systems that work out which product to offer which customer, and when.
What's included
- Live dashboard: revenue, profitability, stock, collections, order status and team performance side by side on one page - from your phone, no need to call anyone for a report
- Regular reporting: daily, weekly or monthly reports delivered automatically to your inbox
- Customer segmentation (RFM) and customer lifetime value (CLTV)
- A/B testing to see what actually works
- Instant data filtering: "customers who bought a second time in Izmir last quarter" answered in seconds
- Sales and demand forecasting from your own history
- Stock-need and reorder suggestions
- Cash-flow forecasting
- Load and staff planning
- Churn risk: spotting which customer is about to leave
- Product recommendations: "customers who bought this also bought" suggestions in the basket and on the page
- Personalised recommendations: a different product list for each customer, based on their own history
- Cross-sell and up-sell: identifying the next product an existing customer is likely to buy
- Measuring recommendation quality: A/B testing whether the suggestions actually convert
Who it's for
Right for you if your data is already tidy but you still can't quite see what it's telling you or plan ahead with it.
If you carry a wide range of products or services and still decide by hand what to offer whom, the recommendation part speaks directly to you.
This turns those numbers into a clear picture and a measurable forecast.
What you get
What you walk away with.
In practice
Before and after.
Retail
Before
Order quantities are set by experience, so some products overstock and tie up cash while others sell out and lose sales.
After
A demand-forecast model now gives weekly reorder suggestions per product and store, cutting both tied-up cash and lost sales.
Restaurant chain
Before
Staff schedules are set by guesswork - some days are overstaffed, others have queues and customers walk out.
After
A model using past sales, weather and holidays gives hour-by-hour load forecasts, and the schedule is built to match.
Subscription / recurring service
Before
A customer's departure is only noticed after they've gone, and winning them back costs far more than keeping them.
After
A model flags high-churn-risk customers early, so the team can call and make an offer before it's too late.
E-commerce
Before
The homepage and product pages show everyone the same "best sellers" list; what the customer bought before counts for nothing, and average basket size stays flat.
After
A recommendation system builds a list per customer from their own history and the behaviour of similar customers; which suggestions convert is measured, and the model updates accordingly.
Questions
Frequently asked.
A forecast isn't a certainty, but it's far more accurate than gut feel - and, importantly, its accuracy is measurable, so you always know how much to trust it.
Then we start with Data Engineering. A dashboard built on messy data just gives you a confident-looking wrong answer, so getting the data right comes first.
Less than people expect. A few hundred customers and a few thousand orders is usually enough for a useful start. Recommendations sharpen as data grows - but there's no need to wait for "big data" to begin. If your data is still scattered, we start with Data Engineering first.
Keep exploring
AI Strategy & Opportunity Analysis
We figure out where you should start - together.
Team Training & AI Adoption
I get your team using AI correctly, safely and productively.
Workflow Automation & Software Development
I turn your repetitive work into a production line.
AI Integration, Assistants & Agents (RAG, AI Agents, MCP)
A general AI doesn't know you. I build one that knows your company.
Data Engineering
I bring your scattered data into one reliable source.
Let's talk about your project.
Tell me where your team loses time and we'll find the right fit together. The first consultation is free.