Data to AI™ / ChatGPT/Microsoft Ads
Check monthly budget pacing, market returns and campaign types in a ChatGPT conversation that reads scheduled Microsoft Advertising reports, with each lookup confirmed by you.
Better answers, fewer tokens.
ChatGPT
Which campaigns lost the most impressions to budget last month, and were they profitable?
Brand Search lost 38% of eligible impressions to budget while returning 6.2 per unit of spend, so it is the clearest case for more budget. Generic Search lost less and returned far less.
| Campaign Name | Spend | Impression Lost To Budget Percent | Return On Ad Spend |
|---|---|---|---|
| Brand Search Campaign Performance Report | $4,100 | 38% | 6.2 |
| Generic Search Campaign Performance Report | $9,800 | 21% | 1.9 |
| Performance Max Campaign Performance Report | $6,300 | 12% | 3.4 |
All three columns come from one Campaign Performance Report with Monthly time aggregation, so the shares are not averaged from daily rows.
Microsoft Advertising (formerly Bing Ads) runs paid search campaigns across Bing and Microsoft's partner network. Dataddo extracts its reports, from account and campaign down to keyword, search term and ad, with the attributes and metrics you pick for each report type.
Run data_status on the Microsoft Ads budget flow, then list each Campaign Name with Monthly Budget, Month To Date Spend and yesterday's Daily Spend.
You confirm each tool call, see that yesterday has loaded, and get a projected month-end figure per campaign, so overspend is caught in the middle of the month instead of on the invoice.
From the Geographic Performance Report, rank each Country by Return On Ad Spend for the last quarter and show the three cities with the most Spend in each.
ChatGPT turns the geographic report into a short list of markets to scale and cities to bid down, and drafts the location targeting notes in the same conversation.
In the Campaign Performance Report, compare Spend, Conversions and Cost Per Conversion by Campaign Type for the last 60 days.
The answer shows whether Performance Max campaigns add conversions at a fair cost or simply take budget from search campaigns, which frames the next budget split discussion.
Data to AI™ is priced per seat, like the AI assistants your team already uses, with ~25% off on annual billing. Need tailored contracts or volume pricing? Talk to us about Enterprise.
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| Without Dataddo |
With Dataddo
|
Outcome for you | |
|---|---|---|---|
| Pacing data in the chat | Someone exports the budget view, uploads the file, and the pacing answer is only as recent as that upload. | ChatGPT reads Monthly Budget and Month To Date Spend from the scheduled Budget Summary Report, and data_status tells you when the last run finished. | Pacing on current spend |
| Control over each lookup | An uploaded export shares every account and column at once, including data the question never needed. | Developer mode asks you to confirm every tool call, and individual Dataddo tools can be switched off in the app settings. | You approve every query |
| Campaign type coverage | Performance Max results are missing from keyword-level exports, so a comparison with search campaigns is incomplete. | The Campaign Performance Report carries Campaign Type and holds Performance Max data, so ChatGPT compares both on the same metrics. | No campaign type left out |
| Token consumption | ChatGPT spends tokens exploring raw Microsoft Ads columns, sampling rows and retrying until it understands the data. | Field definitions and relations are supplied up front, so the model skips the exploration and goes straight to the answer. | Fewer tokens per answer |
| Answer quality | Prone to wrong joins, invented fields and numbers that are hard to check. | Answers grounded in defined fields. In the Dataddo benchmark, 78.5% of questions were answered correctly, against 65.5% with plain CSV files. | Better answers |
The Microsoft Ads datasets marketing teams use most, with their real field names. ChatGPT queries them by name through the Dataddo semantic layer.
| Dataset | Metrics and attributes |
Ask ChatGPT
|
|---|---|---|
| Campaign Performance Report |
|
Which campaigns lose the largest Impression Lost To Budget Percent while still converting well? |
| Keyword Performance Report |
|
How does Cost Per Conversion differ by Delivered Match Type for our top keywords? |
| Search Query Performance Report |
|
Which search terms convert well but are not yet their own Keyword? |
| Ad Performance Report |
|
Which ads have a high Ctr but a Conversion Rate below the ad group average? |
| Budget Summary Report |
|
At the current Daily Spend, which campaigns will overspend their Monthly Budget before month end? |
| Professional Demographics Audience Report |
|
Which Job Function Name segments take the most Spend without converting? |
| Geographic Performance Report |
|
Which cities by City spend the most with below-average returns? |
We asked 43 pre-registered questions of three real datasets - Google Search Console, HubSpot deals and Google Ads - and delivered the same rows to the same model in four ways. Only the data layer changed.
of questions answered correctly - the best of the four delivery methods tested
fewer confidently wrong answers - 14.0% of runs against 24.0% and 26.3%
more correct answers on messy CRM data - better on 8 questions, worse on none
Same model, prompts and rows in every condition; 759 graded runs, ground truth frozen before any run. On Google Search Console alone, documented CSV files did as well as Data to AI™ - the advantage comes from messier data such as HubSpot deals.
Read the benchmark →Extract the Budget Summary Report and Campaign Performance Report with a Microsoft Ads source in Dataddo and attach them to a ChatGPT destination or AI Model. In ChatGPT, switch on developer mode, create the Dataddo Data Access app with https://headless.dataddo.com/mcp-data and OAuth, sign in, then select it in a chat.
Pro, Plus, Business, Enterprise and Education, because the connection uses developer mode, which runs on ChatGPT web only. On Business and Enterprise a workspace admin may need to allow developer mode first.
Developer mode confirms every tool call before it runs, so you see each query against your ad data. You can also switch off Dataddo tools you do not want ChatGPT to use.
As current as the last run. Each run re-reads the relative date range, for example the last 7 days, and replaces that window's data. Ask ChatGPT to run data_status to see when the flow last finished.
Yes. Time aggregation is set per source as Daily, Weekly, Monthly or Hourly. Create one source per aggregation you need and attach each to your ChatGPT destination or AI Model.
The Microsoft Ads API does not support every mix of attributes and metrics. In the Account Performance Report and Ad Group Performance Report, some attribute columns and impression share columns are mutually exclusive.
Only if they are in the extracted data. A source starts from its relative date range, so run a full data re-sync with a wider range to load earlier months for ChatGPT to compare.
