How To Use Notion's AI Features To Speed Up Competitor Research (Custom AI Blocks + AI Autofill)
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Use a custom AI block (or native AI chat) to generate a tailored list of 10 direct and indirect competitors based on business context.
Briefing
Notion’s AI features can turn competitor research into a fast, repeatable workflow by combining three pieces: AI brainstorming, AI-written competitor reports, and AI autofill that summarizes those reports into a structured database. The practical payoff is speed—adding a new competitor becomes a matter of dropping in a name and letting Notion generate the rest, then extracting key fields into a table for later review.
The workflow starts with generating a list of competitors. One approach uses a custom AI block inside the competitor database template: after entering basic business context (the example uses “bizway” as a business planning software), the prompt asks Notion to produce a bulleted list of 10 direct and indirect competitors. The output includes both direct business-planning competitors and indirect alternatives in the productivity space. A second approach relies on Notion’s native AI chat integration, where the user can ask for a list of 10 relevant competitors and Notion can draw on information already stored across the workspace to tailor the suggestions.
Next comes report writing for each competitor. The template includes a “new competitor” button that creates a new page in the competitors database and pre-wires a custom AI block to generate a competitor report automatically. For each competitor added (the example cycles through “LivePlan,” “Bplans,” and “PlanGuru”), the AI fills in structured sections such as key features, target market, active customer base and size, strengths, weaknesses, and pricing. The result is a consistent report format across competitors, without manually drafting each one.
Finally, AI autofill properties convert those pages into a clean, reviewable table. In the example, the competitors table has AI autofill fields left empty until an “update” action is triggered. Using a custom autofill prompt, Notion reads the competitor page content and extracts specific fields—such as value proposition, pricing, and customer base—while also using general AI knowledge when needed. The presenter notes accuracy won’t be perfect every time, but the goal is to streamline common research tasks and reduce the time spent on repetitive summarization.
Under the hood, the template is built around three Notion mechanics: a custom AI block with a reusable prompt for competitor report generation, a database template selected as the default when new pages are created, and a custom AI autofill property that extracts key data from each generated report. The takeaway is that competitor research can be operationalized as a system: brainstorm candidates, generate standardized reports, then summarize them into a database that can be reviewed and compared later.
Cornell Notes
The core idea is to use Notion’s AI tools to automate competitor research end-to-end: generate competitor lists, write structured competitor reports, and then extract key facts into a database table. The process begins by prompting Notion (via a custom AI block or native AI chat) to produce 10 direct and indirect competitors based on business context. A database template with a custom AI block then generates a full report for each competitor when a new competitor page is created. Finally, AI autofill properties read each report page and populate table fields like value proposition, pricing, and customer base. This matters because it turns a time-consuming research workflow into a repeatable system that speeds up updates and comparisons.
How does the workflow generate a list of competitors in Notion?
What makes competitor report creation fast once a competitor name is added?
How does AI autofill turn long reports into a usable table?
Why does the template require setting a default and configuring the add-page button?
What limitation is acknowledged about AI autofill outputs?
Review Questions
- What are the three stages of the competitor research workflow, and what Notion feature supports each stage?
- How do custom AI blocks differ from using Notion’s native AI chat in this process?
- Which table fields are populated via AI autofill in the example, and what triggers the autofill update?
Key Points
- 1
Use a custom AI block (or native AI chat) to generate a tailored list of 10 direct and indirect competitors based on business context.
- 2
Build a competitors database template that includes a custom AI block to generate standardized competitor reports for every new competitor entry.
- 3
Create a “new competitor” button that adds a new page using the database template so the AI report generation runs automatically.
- 4
Add AI autofill properties to the competitors table to extract key fields (like value proposition, pricing, and customer base) from each competitor’s report page.
- 5
Trigger AI autofill updates to populate empty table cells quickly, then review and correct outputs as needed.
- 6
Set the database template as the default for new pages to ensure consistent AI behavior across entries.