Nova Analytics (novadata.io) is a profit app for Amazon sellers that added an MCP connector. DataDoe is the Amazon data layer your AI reads and acts on, with Seller Central, Vendor Central and Amazon Ads joined in one schema and a team that answers in about 15 minutes.
Nova details from its pricing page and its DataDoe alternative page, read on 12 October 2026.
Before the feature rows, the part a comparison table rarely shows: who picks up when a number looks wrong, and who built the pipes underneath.
Our median first reply to a support email is about 15 minutes, from people who know SP-API, not a ticket bot.
Your account manager connects your accounts with you, checks the first numbers against Seller Central and stays your contact after onboarding.
DataDoe passed Amazon’s Public PII approval, so restricted buyer data such as ship-to addresses can be enabled for $49 a month on request.
Deltologic is an Amazon Partner with 30+ engineers that has shipped 200+ SP-API builds since 2020, so the pipes under your data are its day job.
The Amazon SP-API course and the DataDoe Academy video lessons cost nothing, whether or not you subscribe.
Each organisation gets one free 30-minute consultation a month with a Deltologic engineer, for schema questions, custom reports or an agent you are building.
The Nova column comes from Nova’s own public pages, read on 12 October 2026. The DataDoe column comes from our docs. Where Nova is ahead, the row says so.
| Feature | DataDoe | Nova |
|---|---|---|
| Amazon data | ||
| Seller Central | Yes | Yes |
| Vendor Central | Yes, with write Actions for purchase orders, shipments and Direct Fulfillment DataDoe ahead | Yes: its alternative page says 1P is live, while its homepage still lists Vendor accounts as on request |
| Amazon Ads | Sponsored Products, Brands, Display and TV, DSP and search terms; Amazon Marketing Cloud (beta, self-serve) | Ads console data, with Sponsored Products refreshed three times a day |
| Buyer data (PII) | Restricted PII under Amazon’s Public PII approval, $49 a month on request DataDoe ahead | Not offered |
| Marketplaces | All Amazon marketplaces | 23, by its own count |
| Changes on Amazon | ||
| Write Actions | Ads, listings, prices, A+ Content, orders and shipments, plus Vendor POs, ASNs and Direct Fulfillment. Invoices stay read-only. DataDoe ahead | Its page: “Nothing it writes acts on your Amazon account.” Its writes edit costs and tags inside Nova; its blog calls write mode a beta |
| Safeguards | Writes stay off until you enable them. Most AI clients ask before a change, you can preview it as a dry run first, and every change is logged | In-app edits show a preview you approve before they are saved |
| Profit and costs | ||
| Profit in an app | Yes: a Profit & Loss report at app.datadoe.com, plus Profit by Date and Profit by SKU & Date tables your AI can query | Yes: Cockpit, P&L, inventory, listing health and ads screens, built as the core of the product Nova ahead |
| Your own costs | Item cost plus shipping or inbound cost per unit, with a start date and supplier, by CSV or per SKU (seller accounts). How it works | Landed cost per SKU as a fixed cost or batch by batch, FBM shipping rates and a VAT category per SKU, editable from your AI Nova ahead |
| Freshness and history | ||
| How often data updates | Fresh daily, key tables intraday: orders six times a day, Ads, listings and FBA stock four times, Vendor POs every two hours. Finance tables update daily. Schedule | Orders and financial transactions hourly, Sponsored Products three times a day, FBA stock every eight hours Nova ahead |
| History on connect | About two years backfilled when you connect, recent data first | Up to 23 months on the first sync (24 on its MCP page) |
| Access | ||
| AI clients | Claude, ChatGPT, Gemini, Cursor, Codex, GitHub Copilot and any other MCP client, plus n8n and Zapier | Claude, ChatGPT and Gemini; Cursor named in its setup steps |
| Warehouse and API | 100+ tables in BigQuery at no extra cost, a REST API, and CSV, Excel or JSON exports DataDoe ahead | Data Share, plus scheduled exports to Sheets, Excel, BigQuery and Snowflake |
| Price | ||
| Plan | The Base Plan, $97 a month: unlimited connections, 10M data rows, 1 seat, 2,000 AI Tokens | From $49 a month for each Seller or Vendor account; custom quote for agencies Nova ahead for one account |
| Free trial | 14 days | 14 days |
Nova sources, all read on 12 October 2026: DataDoe alternative page, pricing, MCP page, MCP servers blog post. Nova’s figures are its own and we have not tested them.
Both let your AI write something. The difference is where the write lands.
“Nothing it writes acts on your Amazon account.”Nova, about its own assistant, on its DataDoe alternative page, read 12 October 2026
Writes stay off until you enable them. Most AI clients ask before a change, and you can preview it as a dry run first. Every change is logged.
Read the Actions docsAcknowledge 5 purchase ordersOne line rejected: the ASIN is out of stock
Submit the ASN for Tuesday’s shipment3 cartons, 2 POs
Create shipping labels for 18 ordersDue to ship today
Raise the budget on 2 campaignsOut of budget before 3pm on 5 of the last 7 days
Claude wants to run 4 DataDoe Actions
Optional dry run: 4 of 4 payloads valid. Nothing has reached Amazon yet.Nova’s DataDoe alternative page says its facts about us were checked on 28 September 2026. These three no longer match our public docs, checked again on 12 October 2026.
“DataDoe offers MCP, REST and BigQuery: a data layer without an app.”
app.datadoe.com opens on a Home dashboard of key numbers, with Reports that include a Profit & Loss tab, plus Exports and Actions. The MCP, REST API and BigQuery sit on the same data.
Features overviewOwn costs and fee reconciliation: “Not documented publicly.”
You upload item cost and shipping or inbound cost per unit, each with a start date, by CSV or SKU by SKU. Profit by SKU & Date and the order lines use it. Upload is for seller accounts.
Uploading COGS“100+ clean tables, refreshed daily.”
That line was ours, and it undersold the schedule. Orders refresh six times a day and show up within about an hour; Ads, listings and FBA stock four times. Finance tables are daily, where Nova is faster.
Data fetch scheduleMost of Nova’s page is fair to us, including Vendor Central, write access off by default and buyer data. We only list what our docs contradict.
Nova prices each Seller or Vendor account separately. DataDoe is one plan for every account you connect; what you size up is data rows and AI Tokens.
Nova lists “starting at” prices per account and no volume tiers; agencies get a custom quote (pricing, read 12 October 2026). DataDoe’s plan includes 10M data rows, 1 seat and 2,000 AI Tokens a month; extra rows are $49 per 10M and extra seats $29 (pricing docs).
They overlap less than the names suggest. Nova is built around a profit screen. DataDoe is built for AI that has to read across every Amazon account and then do something about it.
Each tool connects to Amazon through its own sign-in, so they never touch each other’s access. An AI client can hold both connectors at once and pull from whichever fits the question.

Two connectors, two separate Amazon sign-ins
Nova says the same on its own page: both tools “connect through Amazon independently” (novadata.io, read 12 October 2026).
Partly. Both connect Amazon data to AI assistants over MCP. Nova is a profit app first, with a connector added in 2026. DataDoe is a data layer: Seller Central, Vendor Central and Amazon Ads in one schema, which your AI can read and, when you allow it, change.
Yes. You upload item cost plus shipping or inbound cost per unit, each with a start date and an optional supplier, by CSV or SKU by SKU in the Inventory report. Order lines and Profit by SKU & Date use it. Upload is available for seller accounts.
Yes. app.datadoe.com has a Home dashboard of key numbers and Reports with a Profit & Loss tab, next to Exports and Actions. The same data reaches your AI through MCP, the REST API and BigQuery.
DataDoe is fresh daily, with key tables intraday: orders six times a day, Ads, listings and FBA stock four times, Vendor purchase orders every two hours, and finance tables once a day. Nova says it pulls orders and financial transactions hourly, so on finance it is faster.
DataDoe can: Ads, listings, prices, A+ Content, orders and shipments, plus Vendor purchase orders, ASNs and Direct Fulfillment. Writes stay off until you enable them. Most AI clients ask before a change, and you can preview it as a dry run first. Every change is logged. Nova's page says nothing its assistant writes acts on your Amazon account, and its blog describes a write mode in beta.
Both list Vendor Central and Ads data. DataDoe joins them with Seller Central in one schema, covers Sponsored Products, Brands, Display and TV, DSP and search terms, offers Amazon Marketing Cloud (beta, self-serve), and can act on Vendor purchase orders and shipments.
Nova starts at $49 a month for each Seller or Vendor account, with a custom quote for agencies. DataDoe is $97 a month for The Base Plan with unlimited connections, so from three accounts up DataDoe costs less. Data rows and AI Tokens are what you scale.
Nova names Claude, ChatGPT and Gemini, with Cursor in its setup steps. DataDoe works with Claude, ChatGPT, Gemini, Cursor, Codex, GitHub Copilot and any other MCP client, and with n8n and Zapier.
Yes. Each connects to Amazon through its own sign-in, and an AI client can hold both connectors. Some teams keep a profit screen in one and run Vendor, Ads and write work through the other.
DataDoe does. It passed Amazon's Public PII approval, so restricted buyer data such as ship-to addresses can be enabled for $49 a month on request. Nova does not offer buyer data.
Your account manager will connect your Seller and Vendor accounts with you, load your costs and check the first numbers against Seller Central.
Book a demoConnect Seller Central, Vendor Central and Amazon Ads in about 5 minutes. Free for 14 days, then $97 a month — with people who answer in about 15 minutes.
We use cookies to improve your experience and analyze traffic. By clicking "Accept", you agree to our use of cookies. Read the Cookie Policy.