Data to AI™ / Claude/Marketo
Get lead flow, MQL quality and scoring answers from Marketo in Claude, so marketing ops prepares the pipeline review in minutes instead of rebuilding smart list exports.
Better answers, fewer tokens.
Claude
Which lead sources brought the most new leads in September, and how well are they scored?
Webinar brought the most new leads, 1,240, with an average Lead Score of 46. Paid Search added 980 leads but scored lower, at 21 on average.
| Lead Source | Leads | Lead Score |
|---|---|---|
| Webinar Leads | 1,240 | 46 |
| Paid Search Leads | 980 | 21 |
| Trade Show Leads | 410 | 38 |
Leads covers records whose Created At falls in the source's date window; Lead Score is averaged per source, not summed.
Adobe Marketo Engage is a marketing automation platform for email, lead management and scoring. Dataddo extracts one flexible Marketo dataset: pick the Leads or Activities object and the fields you need, including custom lead fields from your instance, so marketing ops can ask about lead flow and engagement in plain language.
Count Marketo leads by Lead Source with a Created At in September, add the average Lead Score per source and compare it with August.
Before the monthly marketing review, the marketing ops manager gets the source ranking from Claude and spends the meeting on budget shifts instead of reconciling exports.
Of the leads created this quarter, how many reached each Lead Status, and what Lead Score did they have when sales rejected them?
Marketing and sales leadership see whether the scoring threshold sends too many weak leads to reps, and agree on a new threshold with numbers on the table.
Use the dataddo server to pull last month's Change Score activities with Campaign Id and Attributes, and write scoring/changes-by-campaign.csv.
A marketing analyst runs Claude Code next to the scoring notebook and commits the file, so the next scoring rule change is backed by what each campaign actually did.
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.
Serve governed business data to Claude, ChatGPT and other AI tools over MCP.
$10.49/month
per seat
3 seats minimum
Flexibly deploy Dataddo in any cloud or hybrid environment.
Custom
We have a payment model that works for you
| Without Dataddo |
With Dataddo
|
Outcome for you | |
|---|---|---|---|
| Lead source reporting | Marketing ops builds a smart list, exports it, pivots Lead Source and Lead Score in a spreadsheet and pastes the result into the chat. | Claude reads the Leads object with Lead Source, Lead Status and Lead Score straight from the latest extraction. | Lead review without exports |
| Scoring history | Score changes are visible one lead at a time in the activity log, so nobody can say which campaign moved the numbers. | The Activities object carries Change Score rows with Campaign Id, Activity Date and the type-specific Attributes. | Scoring changes explained |
| Custom lead fields | Custom fields from your instance are missing from standard reports, and readers of an export guess what each column means. | Dataddo lists the lead fields your Marketo instance exposes, including custom ones, and you pick them when creating the source. | Your own fields included |
| Team access in Claude | Each marketer keeps a personal export, so lead counts differ depending on who pulled them and when. | A Claude Team or Enterprise Owner adds the connector once, and every marketer signs in with their own Dataddo account. | One lead count for the team |
| Token consumption | Claude spends tokens exploring raw Marketo 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 Marketo datasets marketing teams use most, with their real field names. Claude queries them by name through the Dataddo semantic layer.
| Dataset | Metrics and attributes |
Ask Claude
|
|---|---|---|
| Leads: source and status |
|
Which Lead Source brought the most new leads last month, based on Created At? |
| Leads: company and contactability |
|
Which Industry and Country account for most of the leads we created this month? |
| Activities: email engagement |
|
How many Open Email and Click Email activities did each Primary Attribute Value get last week? |
| Activities: forms and web visits |
|
Which form, by Primary Attribute Value, had the most Fill Out Form activities this month? |
| Activities: scoring and data changes |
|
Which Campaign Id triggered the most Change Score activities last month? |
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 →Create a Marketo source in Dataddo, authorized with your Marketo domain, Client ID and Client Secret, and pick the Leads or Activities object with the fields you need. Attach it to a Claude destination or AI Model, then connect Dataddo Data Access from the Claude connectors directory and sign in.
Your Marketo domain plus a Client ID and Client Secret. Create them under Admin > Integrations > LaunchPoint with New, then View Details. The account behind the service needs at least admin-level access.
Yes, as two sources. Each Marketo source extracts one object, Leads or Activities, so create one of each and attach both flows. Claude can then combine them through Lead Id.
Each run reads leads whose Created At falls in the source's relative date window. To give Claude older leads or activities, run a full data re-sync with a wider range once.
Yes. Signed in with your Claude account, Claude Code loads the Dataddo connector, so you query Marketo leads and activities from your terminal while you work in a repository.
No. Claude queries extracted data through the semantic layer by entity and field name. Dataddo never accepts SQL from the model, and nothing is written back to Marketo.
Yes. Claude shows the connector's tool permissions, and you choose per tool whether Claude may use it freely or must ask you first, for example before a refresh.
