Data analysts usually send an estimate or proposal after an intro call and a quick look at the client's data and goals. Clients compare how many deliverables are included, how the price is structured, and how much risk they carry if the data turns out to be messy. A clear scope and stated assumptions matter more than the lowest price.
When to use estimates: Use estimates to provide project quotes and get client approval before starting work. Once approved, convert your estimate to an invoice with one click to collect payment.
Create an invoice for payment collection
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Keeps the project tied to a decision and prevents open-ended requests to look at everything.
A spreadsheet of 5,000 rows and a database with millions of records are very different jobs.
Delays in getting credentials or exports are a common cause of missed deadlines and should shift the timeline.
States what you expect, such as consistent date formats and unique IDs, so major cleanup beyond that can be handled as a change order.
Names the dashboard platform, number of pages or visuals, report length, and file formats so both sides agree on what done looks like.
Limits open-ended edits and sets a timeline for client review.
Clarifies who owns the code and dashboards, who pays for licenses, and whether support after delivery is included.
| Service | Priced | Typical range |
|---|---|---|
| General data analysis and ad hoc reporting | per hour | $60-130 |
| Dashboard build (Tableau, Power BI, Looker Studio) | flat fee | $1,500-6,000 |
| Data cleaning and preparation | per hour | $50-110 |
| SQL query development and database reporting | per hour | $70-140 |
| Statistical analysis or predictive modeling | per hour | $90-175 |
| Monthly reporting retainer | per month | $800-3,500 |
| Survey or A/B test analysis | flat fee | $750-3,000 |
| Training session on dashboards or spreadsheets | per session | $250-800 |
Typical US ranges. Rates vary by region, experience, and job size.
If you have not looked at the actual files, give a range or a not-to-exceed figure and tie the final price to a data review. Fixed quotes made blind often lose money.
Cleaning and joining data often takes more time than the analysis itself. Estimate it explicitly and add a buffer of 20-30% if the data comes from several systems.
Present a basic option such as a single report, a standard option with a dashboard, and a full option with monthly updates. Clients often choose the middle tier and can see what each level adds.
Quote validity of 14 to 30 days protects you if the client's data or priorities change before they approve.
A short intro call and a rough range are normal to give for free. If the client wants a detailed scope based on reviewing their data, consider charging a small fee for a data audit, which you can credit toward the project if they proceed.
Include a change order clause in your agreement. When the client asks for new metrics, data sources, or extra dashboards, send a short written addendum with the added cost and timeline before starting.
An estimate is a good-faith approximation and a quote or fixed-fee proposal is a firm price. Label the document clearly, and state what could change the price, such as poor data quality or added requests.
Use the Data Analyst invoice template to bill the client, or convert this estimate once it's approved.
Data Analyst invoice template