General

Research online to find the typical purchase frequency and basket 
size of online beauty products in Germany, Switzerland and France for 
2022-25. Present the data in a new tab and add 
clickable links directly in the Excel to verify all facts.

Extract the full 3 statements from the attached quarterly reports. 
Include full granularity on all line items and implement checks to 
verify extraction accuracy (balance sheet must balance, Net Profit 
must match sum of P&L components, etc.). Add source references in 
the cells.

Get me the accounting data for Sol Cigar, a Norwegian entity that sells 
tobacco

Put the uploaded Excels into this model. Make a consolidated tab 
where you link in content from each added tab into the consolidated 
one. 

The data from each tab must be stacked vertically. Keep column 
headers at the top only (don't repeat for each file). If column 
structures don't match exactly, align common columns and document 
any mismatches.

Clean and organize the customer data on the Customers tab.
1. Understand the structure of the data. Identify duplicates or 
   entities that likely refer to the same customer (e.g., Crunched 
   Holding AS and Crunched AS).
2. Create a unique customer list with a mapping column showing 
   how you grouped similar entities together.
3. Build a revenue summary table by reformulated customer for 
   2020-25 showing: BoP, new customers, expansion, contraction, 
   full churn, EoP.

Build a DCF based on the forecasted financials in this model. 
Extrapolate the explicit forecast (if needed) to get an 8-year 
forecast period which smoothly decays to the terminal year. Use 
perpetual growth at terminal. Add a WACC calculation with rationales
for each component (risk-free rate, equity risk premium, beta, debt 
cost) that I can tweak later. Show each net debt component 
as available in the EV-equity bridge at the end.

Below the debt schedule section of this LBO (ending at row 45), 
insert rows to build a credit metrics section showing net debt / 
EBITDA, net debt / (EBITDA - Capex), Interest / EBITDA and 
Interest / (EBITDA - Capex). Add similar metrics for each debt 
tranche - senior and mezz. Match the formatting style of the 
existing debt schedule section.

Populate the input sheet historical fields (B5:G20) with data from 
the Raw Data sheet. If you have to consolidate line items to match 
the input sheet, document which lines you consolidated in a dedicated 
column for me to review. For any items that cannot be matched with 
confidence, flag them separately for manual review. Make a check 
at the end to ensure you were exhaustive in the linking of all 
raw data.

Review sheet (A) and (B) for mistakes

Walk me through how you built this model. Go step by step. Flag 
any assumptions or calculations I should be particularly conscious 
about. If you see any mistakes you did, flag them. Do NOT edit 
anything.

Explain how this forecast model is built up. Take me through what 
the underlying assumptions are for revenue in each segment and how 
the calculations flow through the model practically.

You are presenting for the CEO. Provide a script explaining the 
outcome and approach of this model in a top-down way.

Walk me through the model and analyze the assumptions. Make a 
comment on each assumption on whether it's aggressive, reasonable 
or conservative. Search public sources to back up your analysis 
and add clickable links for me to review. When you're done, add 
10 due diligence/discussion questions for management based on 
the analysis.

I am considering to acquire this company. Generate 10 questions 
for management based on this financial model.