Shopify App Store Intelligence: Rivals and Reviews

Pick a Shopify app category and find out who leads it, who is actually growing, what they charge, and what merchants complain about — read from the public App Store listings.

No API key, no login, no proxy.

What does this do?

Every app in the Shopify App Store shows a star rating, and nearly all of them show 4.8 or better. That number tells you almost nothing: it cannot tell a category leader coasting on eight years of reviews from a newcomer pulling ahead this month, and it certainly will not tell you what the unhappy merchants are unhappy about.

This Actor reads a category, then for each app reads its listing and its reviews twice: the recent stream, for how fast it is growing, and the one and two star reviews specifically, for what is going wrong.

flowchart LR
    A[Category or search] --> B[App listings]
    B --> C[Rating, price tiers,<br/>launch date, developer]
    B --> D[Recent reviews<br/>growth rate]
    B --> E[1-2 star reviews<br/>complaint themes]
    C & D & E --> F[Ranked: who leads,<br/>who moves, what hurts]

Who is it for?

You are	You use it to
A Shopify app developer	See what rivals charge, and read the complaints they have not fixed
Thinking of building an app	Find a category where the leaders are disliked for something specific
An agency choosing apps for clients	Pick on evidence rather than on a 4.9 everyone has
An investor looking at ecommerce tooling	See which apps are gaining reviews fastest right now

What data do you get?

One row per app:

Field	What it is
name, developer, launched, url	Who makes it and since when
rating, ratingCount	The public star rating and how many reviews it rests on
freePlan, priceTiers, lowestPaidPrice, highestPrice	Every monthly price on the listing
position, whyPosition	Leader, challenger, established or niche within the set analysed
momentum, whyMomentum	How fast it is gaining reviews against its rivals
reviewsPerMonthRecent / Lifetime	The recent rate, and the all-time average
reviewRateVsOwnHistory	Recent rate ÷ lifetime rate, as a number
recentUnhappySharePercent	Share of the recent stream that was 1-2 stars
complaints, praise	Themes, each with a count and a real quote
starsOfReviewsRead, reviewsRead, negativeReviewsRead	Exactly what the numbers were computed from

Example: product review apps, September 2026

App	Position	Momentum	Reviews	Complaints found
Judge.me	leader	fastest growing (54/mo)	47,262	Bugs (2), Hard to set up (1), Missing features (1)
Loox	challenger	average (7/mo)	9,648	—
AG Product Reviews	established	average (9/mo)	3,160	Bugs (3), Missing features (1), Uninstall leftovers (1)
Ali Reviews	established	average	—	Uninstall leftovers (3), Bugs (2), Pricing (1)
Junip	established	below average (5/mo)	1,155	Support slow (1), Bugs (1)

Judge.me has forty-seven thousand reviews and is still collecting them faster than anyone else in the category. That is the fact a 5.0 star rating hides, and it is the one that should decide whether you enter this category at all.

How the numbers are made, and what they are not

• Install counts are not public. Review volume is the only available proxy for scale, and review velocity for growth. That is said on every row rather than dressed up as "installs".
• Momentum is measured against rivals, not against the app's own past. An earlier version compared each app to its own lifetime average and graded all eight apps in a category "stalled" — mature apps accumulate their lifetime average during the years the whole store was growing. A measure where everybody loses tells a competitor nothing, so the benchmark is now the median recent rate of the set.
• Position is relative to the apps analysed, never a claim about the whole Store. "Leader" means most reviewed in this run.
• Themes are keyword matching, not comprehension. Each theme counts reviews containing known phrases and quotes one of them, so every number can be checked against a real sentence. It is described that way in the output itself.
• The complaints are fetched deliberately. A five star app's recent pages contain almost no unhappy merchants — the first version of this Actor found no complaint themes at all. The one and two star reviews are now requested directly, which is why complaints appear even for apps rated 5.0.
• recentUnhappySharePercent is about the recent stream only. It sits next to negativeReviewsRead, which comes from the filtered pass and will usually be a much larger number. They measure different things on purpose.

Popular category reports

Ready-made runs you can open and start, or copy as a starting point:

• Best Shopify Apps, Ranked by Real Reviews
• Shopify Product Review Apps Compared
• Shopify Email Marketing Apps Compared
• Shopify SEO Apps Compared
• Shopify Upsell and Bundle Apps Compared
• Shopify Dropshipping Apps Compared
• Shopify Shipping Apps Compared
• Shopify Store Design and Page Builder Apps
• What Merchants Complain About in Shopify Apps
• Fastest Growing Shopify Apps
• Shopify App Pricing Comparison
• Shopify App Competitor Research
• Shopify Store Management Apps Compared
• Shopify Sales Channel and Marketplace Apps
• Shopify Currency and Translation Apps

Pricing

$0.01 per app analysed and $0.002 per page of reviews read. A run with reviews switched off is only charged the first.

Twenty apps with three pages of reviews each costs about $0.30. The same twenty apps without reviews costs $0.20.

Input

Setting	What it does
App category	Which App Store category to analyse, from the main ones and the popular subcategories
Specific apps	Optional. App names from their store URL, or full links. Overrides the category
Search term	Optional. Analyse whatever a search returns, for example "abandoned cart"
Maximum apps	How many to analyse, most reviewed first
Read reviews	Off gives a plain, cheaper ranking with prices and ratings only
Review pages per app	About 10 reviews per page; three is enough for the rate and the common complaints
Minimum total reviews	Skip brand new apps with nothing to read

Integrations

Runs on a schedule and connects to Google Sheets, Slack, Zapier, Make or your own code through the Apify API. Run it monthly against your category and the complaint themes become a backlog of things your rivals have not fixed.