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Nectar AI

Customer insights designed for B2B teams

- 🛠️ Auto-collect and consolidate customer quotes/feedback from your existing stack - 🏛️ Create groups on based business needs, e.g. ARR, tenure, product mentions, sentiment - 🤩 Create and share insight reports with dollar value in mind

Top comment

Hey Product Hunters! 👋 Super excited to share how you can use Nectar to surface customer insights at rocket speed, and based on what your accounts are saying (not just individual users). Understanding the user is at the heart of every great product. Yet those building B2B experience an extra layer of complexity: accounts. A one-size-fits-all solution to building B2B product typically doesn’t work if you have customers of various sizes and values to the business. Customer XXL has different needs than Customer S, yet there maybe many more Customer S’s, and Customer M may soon become Customer L, etc At my last company, I moved from a consumer-first role to one that supported our B2B needs. I was surprised to learn that I had no idea about our different "larger" customer needs and dollar values, despite us sharing the same engineering resources. What makes qualitative customer data so challenging is the time it takes to read and organize it. Yes, I was also one of those PMs who read through hundreds of cancellation reason to better understand customer churn. Argh. In an ideal world, we should be able to compare qual data just like quant data. We should be able to sort, filter, visualize and measure customer quotes and feedback, just like we can with our fav analytics tool. 🥁 Drum roll. That’s why we decided to build Nectar to save teams time organizing qual data (avg. 80 hrs/month/team), and help them make product decisions based on business value. Here, our core features: - 🛠️ Auto-collect and consolidate of all customer conversations, and removes redundancies and noise. - 🏷️ Auto-tagging (3 kinds) each conversation to make assessments easier: 1) by topic, e.g. “checkout” or “onboarding”, 2) account properties, e.g. ARR, tenure, current pricing plan, and 3) score, e.g. “problem severity”, “sentiment”, “willingness to pay” - 🤩 Generate insights based on groups with set filters. For example you can ask: “What do my Swedish, Starter-Plan customers, that have been with us for 6 months, think about onboarding?” You can watch a demo of our v1 here: "https://youtu.be/GBrbY6t5xls?si=..." We're excited for this is our first public beta launch. You can try us out here: https://nectar.run/ Follow us (on PH) for updates. All other matters: [email protected] Thanks!

About Nectar AI on Product Hunt

Customer insights designed for B2B teams

Nectar AI launched on Product Hunt on May 13th, 2024 and earned 111 upvotes and 6 comments, placing #12 on the daily leaderboard. - 🛠️ Auto-collect and consolidate customer quotes/feedback from your existing stack - 🏛️ Create groups on based business needs, e.g. ARR, tenure, product mentions, sentiment - 🤩 Create and share insight reports with dollar value in mind

On the analytics side, Nectar AI competes within Analytics and Tech — topics that collectively have 793.4k followers on Product Hunt. The dashboard above tracks how Nectar AI performed against the three products that launched closest to it on the same day.

Who hunted Nectar AI?

Nectar AI was hunted by Robin Greenwood. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

For a complete overview of Nectar AI including community comment highlights and product details, visit the product overview.