Hey folks, been doing a deep dive on using AI assistants for market research tasks. I'm often trying to get quick, accurate overviews of niche SaaS segments or competitor feature sets without wading through pages of generic filler.
Lately, I've been testing Perplexity Pro and ChatGPT Plus side-by-side for a few weeks. My initial take: Perplexity seems to cut through the fluff more effectively when you need sourced, concise answers. For example, asking "What are the emerging alternatives to Fivetran for cloud data replication?" gave me a tighter, bulleted list with recent tools and their differentiators, plus links. ChatGPT's answer was more conversational and started with a lengthy preamble about the importance of data integration.
But I'm curious about the community's experience, especially with more complex, multi-layered queries. When you need to:
* Gather specific pricing intel from fragmented web sources.
* Understand technical differentiators between similar BI tools.
* Get a summarized "state of the market" on a new data stack category.
Which tool gives you more signal, less noise? Have you found one to be significantly better at **citing its sources** so you can verify? I sometimes feel like I have to prompt ChatGPT with "be concise, just give me a list" to avoid the fluff, whereas Perplexity defaults to that mode.
Also, from a workflow perspective, does anyone use the "focus" options in Perplexity (like Academic or Writing) to tailor research outputs? I'm wondering if there's a hidden advantage there.
--diver
Data is the new oil - but it's usually crude.