AI Marketing Analytics
Paste or upload campaign data. Get CAC, ROAS, funnel drop-off and retention, charted.
Nothing sends until you start, and you can change anything afterwards.
What you get
- Text in the chat Copy it wherever you need it. Keep chatting to adjust the tone, length, or wording.
How it works
- Paste your numbers or upload a CSV or Excel file of campaign, funnel, or customer data. Any column names work; askROI tells you how it mapped them.
- askROI's Data reports tool computes the metrics in Python from your data, shows the headline numbers and a chart in the chat, and explains what to act on. Ask for a spreadsheet and it adds one with every breakdown and the formulas used.
- Copy the numbers into your report, or keep chatting to compare periods, test a budget shift, or dig into one channel.
What people use it for
- Channel budgeting see which channels return the most revenue per dollar before you move budget.
- Funnel diagnosis find the one stage where most people drop out, overall or by segment.
- Retention see how many customers from each signup month are still active or buying months later.
- Board and client reports get CAC and ROAS figures with a chart and a plain explanation of each.
Questions
Which metrics does it calculate?
From campaign data: customer acquisition cost, return on ad spend, click through rate, conversion rate, and cost per result by channel or campaign, with totals built from summed spend and revenue rather than averaged ratios. ROI needs profit, so it is reported only when you give a margin, gross profit, or cost of goods; revenue minus ad spend alone is not ROI. From funnel data: each stage's conversion from the stage before and from the top, its drop-off, and the stage with the biggest loss. From customer data with dates: cohort retention, and lifetime value when revenue per customer over time is there.
What data does it need?
Numbers pasted in the chat, or a CSV or Excel upload with any column names. It maps your columns to each metric and states the mapping. A metric is left out, with the reason, when the data behind it is missing, for example ROAS without revenue.
How is this different from general AI data analysis?
The data analyst profiles any dataset: column summaries, missing values, duplicates, outliers, and correlations. This tool computes the business metrics you ask for and shows how each one was calculated.
What does it not do?
It does not connect to your ad platforms or analytics tools, so it only works on the data you give it. It measures what happened in that data; it does not forecast future results or model multi-touch attribution.