
Prediktivna i preskriptivna analitika | Predviđanje prodaje i optimizacija zaliha
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betterdecisions.ai je dokazao svoje veštine Zinn Hub-u i pružio dokaze o svom radu. Svaki verifikovani Zinner prolazi praktičnu proveru kvaliteta — tako da možete angažovati sa poverenjem.
🛡️ Verifikovano od September 2026
Jasnoća podataka za bolje odluke.
Pomažem vlasnicima malih preduzeća da svoje neuredne podatke o prodaji i zalihama pretvore u jasne, delotvorne odluke.
Most business owners have data sitting in a spreadsheet — but no idea what it is actually telling them. They plan inventory based on gut feeling. They discount products without knowing if those discounts are driving sales or quietly killing profit. They look at last month's numbers and hope next month will be better.
Tu ja stupam na scenu.
What I do:
I analyze your sales and inventory data to find three things:
What is actually making you money
What is quietly losing you money
What is coming next
I use Facebook's Prophet, a widely adopted open-source forecasting tool, to build forecasts you can trust. Instead of a lengthy report full of jargon, I give you clear, specific recommendations you can act on the same day. I give you clear, specific recommendations you can act on the same day.
What "predictive analytics" actually means for you:
Most business reports tell you what happened last month. That is the past. You cannot change the past.
Predictive analytics is different. It looks at your historical data — your sales, your inventory, your seasons, your discounts — and uses it to forecast what is coming next.
Na primer:
"Based on the last 4 years, your sales will peak in November and drop by 30% in April."
"Your top-selling product will run out of stock in 3 weeks if you do not reorder now."
"If you keep discounting at 40%, you will lose money on every sale next quarter."
This is the difference between looking in the rear-view mirror and looking at the road ahead. Predictive analytics lets you plan instead of react.
What "prescriptive analytics" actually means for you:
Knowing what is coming is useful. But knowing what to do about it is where the money is.
Prescriptive analytics goes one step further than predictive. It does not just tell you what will happen — it tells you what to do about it.
When I analyze your data, I do not just hand you a chart. I give you prioritized recommendations you can act on the same day. For example:
"Stop discounting Product X — it is losing you money every time it sells."
"Reorder Product Y two weeks earlier — you are running out during your busiest season."
"Your top 10 customers drive 40% of profit. Focus your retention budget on them."
You walk away knowing exactly what to do — not just what happened.
Zašto ja:
I have analyzed over 10,000 rows of real retail data — as shown in my portfolio — and developed my forecasting approach hands-on from the ground up.
I explain everything in plain English. No jargon. No confusing charts.
I bring the discipline of an analyst and the clarity of a teacher — every report is written for a business owner, not for a data scientist.
How I work:
Every report I deliver follows three rules:
If you do not understand it, I have not done my job. Plain English. No jargon.
I focus on decisions, not charts. A chart that does not lead to an action is decoration.
I agree the scope with you before I start. No surprises on delivery time.
Šta možete očekivati kada radite sa mnom:
Delivery timelines are agreed with you before work begins and depend on data size and scope — many projects are turned around quickly.
Jasna komunikacija.
A report you can actually read and understand.
Recommendations that save you money or make you money.
If you have sales or inventory data sitting in a spreadsheet and are not sure what it is telling you, you are in the right place.
Share your data and I will show you what it is telling you.
Tehnologije i ekspertiza za koje je ovaj frilenser specijalizovan.
Područja usluga za koje je ovaj freelancer dostupan.

Analysed 4 years of retail sales data to identify hidden profit leaks and build a 12-month forecast using Facebook's Prophet. Key findings: The average order value was $230, but the median was only $54 — meaning most customers spent far less than the average. Discounts above 30% turned profit negative in the Furniture category. A 12-month forecast was built to help plan inventory and staffing. This project demonstrates my ability to take messy sales data and turn it into clear, actionable recommendations.
Pogledajte detalje →Ručno odabrano od strane betterdecisions.ai — ovo su njihove vodeće usluge.

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