Verified against Perplexity Pro · 2026-07-27
Build a living competitor-comparison table inside a Space instead of a one-off answer
A recurring competitive-research prompt designed to run inside a Perplexity Space, with fixed comparison columns and per-cell citations so the table can be safely re-run and extended round after round without losing comparability.
The prompt
Ready to copy — highlighted parts are example details you can swap.
This question is part of an ongoing competitive research project — treat it as one round of a comparison table that will keep growing across future threads in this Space, not a standalone answer to be optimized in isolation. OUR COMPANY / PRODUCT Northwind Analytics, a mid-market marketing attribution platform COMPETITORS TO COVER THIS ROUND Attribution.io, Ruler Analytics, Dreamdata COMPARISON DIMENSIONS (keep these exact column headers every time this is run again — do not rename, reorder, or merge them even if a different phrasing would read more naturally for this round) Starting price, Free tier, Attribution model type, G2 rating, Last major feature launch INDUSTRY CONTEXT B2B marketing attribution software, mid-market segment ($10k-$100k ACV) OUTPUT FORMAT A table: Competitor | Starting price, Free tier, Attribution model type, G2 rating, Last major feature launch — with one citation per cell, not one citation covering the whole row. If a cell cannot be filled from a verifiable public source, write "not publicly disclosed" rather than estimating a number and presenting it as fact, and rather than leaving the cell blank in a way that looks like an oversight instead of a deliberate gap. CONSISTENCY CHECK If any competitor in this round was also covered in a prior round of this same comparison (assume prior threads in this Space exist), briefly note whether anything in their row has changed since then, and flag if a number in this round looks inconsistent with what a prior round likely reported for the same dimension, so drift gets caught rather than silently compounding round over round. AFTER THE TABLE One paragraph: what changed about the competitive picture since the last obvious public update from any of these competitors — a product launch, a pricing change, a funding round, a leadership change. Flag anything time-sensitive or recently announced as provisional rather than settled, since recent announcements are the most likely place for a source to be wrong or incomplete.
Customize
Optional — swap in your own details for the highlighted parts above.
Why this works
Running this inside a Space rather than a one-off thread is the mechanic that makes the table durable: the Space's own instructions and thread history let you fix the comparison dimensions once and re-run the same shape of question in a new thread weeks later without redefining the columns from scratch, which is what turns a snapshot into a genuinely maintained comparison instead of a document that has to be rebuilt every time someone asks for an update. Requiring one citation per cell instead of one per row closes a specific failure mode of table generation — a single strong source about Competitor A's pricing can otherwise get silently reused to justify a claim about Competitor A's rating or Competitor B's pricing in an adjacent cell, because the model is filling in a grid pattern, not verifying each fact independently against its own source. Instructing 'not publicly disclosed' instead of an estimate matters because a competitive table that quietly fills every cell reads as more complete and more certain than the underlying public sourcing actually supports, which is worse for decision-making than an honest gap that flags exactly where more digging would be needed. The consistency-check step is the one piece that specifically exploits running this in a Space rather than a fresh thread: because the model can see prior threads in the same Space, asking it to flag a number that looks inconsistent with what a previous round likely reported catches slow data drift — a pricing figure that quietly crept from one round to the next without anyone updating it on purpose — that a single isolated run would have no way to notice, since it would have nothing to compare against.
What you get back
Attribution.io | $499/mo | No | Multi-touch, rules-based | 4.4/5 (G2, 210 reviews) | AI-assisted channel grouping, announced May 2026 Ruler Analytics | not publicly disclosed | No | First-touch + multi-touch | 4.6/5 (G2, 95 reviews) | not publicly disclosed Since the last round: Attribution.io shipped AI-assisted channel grouping in May 2026 — treat any competitive parity claim about "manual grouping only" as outdated after that date.
Verified against
Perplexity Pro Spaces + Sonar Pro (2026) · 2026-07-27
Changelog
- 2026-07-27 — Initial publish, verified against Perplexity Spaces with Sonar Pro search.
Need this built into your business?
If a prompt isn't enough — what Scult builds, built and maintained for you — that's Scult's day job.
EXPLORE WHAT SCULT BUILDS
