Competitor research is necessary but painful. CompetitorLens monitors your competitors' public storefronts, detects what actually changed, and turns it into a short, evidence-backed brief written by AI: what moved and why it matters, without the manual grind.
Public data only · robots-respecting · we never write to your store.
The move that matters: BeanCo dropped a product you sell to $20.00 (you're $23.00). The rest is competitor-side context.
Written by CompetitorLens from evidence-backed signals. Advisory only. Nothing was changed or sent.
By the time it shows up in your conversion rate, it's days too late.
A rival undercuts your bestseller and you find out from your sales, days later.
Discounts and bundles flicker across many stores, impossible to watch by hand.
New competitor products appear without warning and eat your category.
Hero, CTA and guarantee copy quietly change and shift the buyer narrative.
Replace scattered, stale, manual checks with a system that remembers.
Price moves, stockouts, launches, promos, ad signals and website changes, monitored continuously and explained in one daily brief. Each fact comes from evidence; each carries an honest caveat when the data is thin.
See where a rival is cheaper on the same product, and where it's only a catalog-average difference, clearly labeled.
Know when a competitor drops or raises a price, with the before/after and the evidence to back it.
Get alerted when a competitor sells out (a window to capture demand), and when they're back.
Spot competitor launches in your next brief, not a month later, and catch quiet discontinuations.
See when a rival starts a sale, and when it ends, so you can counter, hold, or wait it out.
Catch new competitor campaigns from public ad signals. No private data, no guessed spend.
See when a competitor changes their pitch (hero, CTA, positioning), before/after, side by side.
Watch a rival expand or thin out their range over time, a breadth strategy you can match or counter.
Not just today's change. The pattern behind it: promo cadence, pricing trends, who moves first.
A deterministic engine decides what's true; AI writes the brief. Every claim links to its source, and when we can't be sure, we say so.
Public product feed · captured this morning · content hash on file.
A same-product claim only appears when we can confidently match the product. Otherwise we show catalog-level positioning and say so. No fake "matched SKU."
Paste competitor websites or accept suggestions. Public storefronts only.
CompetitorLens tracks changes to competitor products, prices, promos, stock, and website messaging, then turns the important ones into a brief you can actually use.
We compare the same product when we can confidently match it; otherwise we show category-level positioning.
A short daily, weekly and monthly brief: what changed, why it matters, every claim cited.
Advisory only. CompetitorLens informs your pricing and product decisions; it never makes them.
"I know I should watch competitors but I don't have time, and I find out too late." One brief a morning.
"I manually check a dozen sites; it's inconsistent and I miss things." Consistent, every day.
"I need to know about promos and launches to react, not read about them next month."
Monitor many client stores from one copilot, account-scoped per client. Built for catalogs that matter (e.g. cloth by weight/weave).
No. CompetitorLens only reads public competitor storefronts, the same pages any shopper sees.
No. There is no auto-repricing. CompetitorLens is advisory only. It informs your decisions, it doesn't make them.
No. We surface campaign signals from public sources only and never estimate private budgets.
We only make a same-product claim when we can confidently match the product. Otherwise we show catalog-level positioning, and we don't compare prices across currencies. We tell you.
A baseline appears after the first checks; weekly patterns after ~7 days; monthly trends and performance links after ~30 days.
No. The demo is fully synthetic and labeled as such.
Request private beta below, or open the live demo and read a sample brief first.
See the live demo