Nebius Customer AtlasNot affiliated · Research by Not affiliated · By @anthonybs
Not affiliated with Nebius · Independent research by @anthonybsSee changes
AllHeatseeker

Heatseeker

Market testing and product research

How they use Tavily

In August 2024, Heatseeker product manager Razii Abraham described using Tavily to research customers’ companies and classify them as B2B or B2C. The Python workflow used Tavily’s API to cross-reference public internet sources by company name, then passed company and product information to GPT-4o for classification. Tavily shared the account publicly.

The task supported new user engagement initiatives because business-model classifications were missing from Heatseeker’s database. Abraham said the approach eliminated manual categorization without burdening the engineering team. He also said the workflow maintained data privacy by using public information. The classifications helped Heatseeker tailor content and resources to users’ business models.

Sources

1 source

Product manager’s company-classification workflow

23 Aug 2024 · Tavily / Razii Abraham · Web page

Heatseeker product manager Razii Abraham describes a Python workflow using Tavily’s API to research users’ companies and GPT-4o to classify them as B2B or B2C. The classifications supported user engagement initiatives and removed manual categorization without burdening the engineering team. Abraham says the workflow maintains data privacy by using public information.

Open original source
Product manager’s company-classification workflow23 Aug 2024 · Tavily / Razii Abraham · Web pageHeatseeker product manager Razii Abraham describes a Python workflow using Tavily’s API to research users’ companies and GPT-4o to classify them as B2B or B2C. The classifications supported user engagement initiatives and removed manual categorization without burdening the engineering team. Abraham says the workflow maintains data privacy by using public information.

Company context

heatseeker.ai

Heatseeker makes an AI customer research platform for marketing, insights, product and growth teams. Its main tools combine live market experiments with synthetic personas built from customer data and observed behavior. Teams can test product concepts, audience segments, positioning, messages and advertising creative through campaigns on Meta, LinkedIn and TikTok. They can also question simulated customer audiences and compare predictions with real responses. The platform brings these results together to help businesses choose products, campaigns and market strategies before committing larger budgets.

Heatseeker — Platform

Documented financing · private company

AmountUndisclosedHearstLab investment and first seed close
· Heatseeker press release

Seed target: $5M. First-close amount: undisclosed.

Next, A–ZHedy AI
← Explore all customers

Heatseeker

Market testing and product research · Workplace tools

How they use Tavily

In August 2024, Heatseeker product manager Razii Abraham described using Tavily to research customers’ companies and classify them as B2B or B2C. The Python workflow used Tavily’s API to cross-reference public internet sources by company name, then passed company and product information to GPT-4o for classification. Tavily shared the account publicly.

The task supported new user engagement initiatives because business-model classifications were missing from Heatseeker’s database. Abraham said the approach eliminated manual categorization without burdening the engineering team. He also said the workflow maintained data privacy by using public information. The classifications helped Heatseeker tailor content and resources to users’ business models.

Sources

1 source

Product manager’s company-classification workflow

23 Aug 2024 · Tavily / Razii Abraham · Web page

Heatseeker product manager Razii Abraham describes a Python workflow using Tavily’s API to research users’ companies and GPT-4o to classify them as B2B or B2C. The classifications supported user engagement initiatives and removed manual categorization without burdening the engineering team. Abraham says the workflow maintains data privacy by using public information.

Open original source
Product manager’s company-classification workflow23 Aug 2024 · Tavily / Razii Abraham · Web pageHeatseeker product manager Razii Abraham describes a Python workflow using Tavily’s API to research users’ companies and GPT-4o to classify them as B2B or B2C. The classifications supported user engagement initiatives and removed manual categorization without burdening the engineering team. Abraham says the workflow maintains data privacy by using public information.

Company context

heatseeker.ai

Heatseeker makes an AI customer research platform for marketing, insights, product and growth teams. Its main tools combine live market experiments with synthetic personas built from customer data and observed behavior. Teams can test product concepts, audience segments, positioning, messages and advertising creative through campaigns on Meta, LinkedIn and TikTok. They can also question simulated customer audiences and compare predictions with real responses. The platform brings these results together to help businesses choose products, campaigns and market strategies before committing larger budgets.

Heatseeker — Platform

Documented financing · private company

AmountUndisclosedHearstLab investment and first seed close
· Heatseeker press release

Seed target: $5M. First-close amount: undisclosed.