Best Shopify Collection Sorting Apps in 2026, Ranked

The best Shopify collection sorting apps in 2026, ranked on a published 10-criterion scorecard: SellRank, rule-based apps, merchandising suites, native sorts and manual order. Check every score yourself.

Looking for the best Shopify collection sorting apps in 2026? This ranking scores every realistic way to order a Shopify collection against ten weighted criteria, publishes the weights, and shows the reasoning behind every number. The five options are SellRank, generic rule-based sorting apps, broad merchandising and search suites, Shopify's native sort options, and manual drag-and-drop. Our verdict comes first, the method follows, and every score can be checked on your own store.

Before anything else, the disclosure that should sit at the top of every list like this: LeelaRam Technologies makes SellRank. We built it, we sell it, and it comes first in this ranking. You should weigh the ranking accordingly. What we can do about that conflict is make the method public. Every criterion is written down with its weight, every score has a reason, and every reason is something you can test for yourself in an afternoon. So don't trust the ranking because we wrote it. Judge us on these criteria, and if SellRank falls short on any of them for your store, the scorecard will tell you so.

The verdict: the best Shopify collection sorting apps, ranked

Here is the short answer for anyone who won't read the full method. Scores are out of 100, weighted across the ten criteria described below. A category score is our judgement of a typical tool in that category. Individual tools inside a category vary, sometimes a lot, which is exactly why the criteria are published: score the specific tool you're looking at yourself.

1. 1SellRank: 90.4 out of 100. Composition, first-party data, verified writes into Shopify's own sort, a human override that survives every re-sort, and per-version proof of what each order did. It loses points on automation frequency, on the time its pixel needs to build engagement history, and on price against free options.
2. 2Generic rule-based sorting apps: 56.6 out of 100. Reliable, affordable automation of one rule per collection. They lose most of their points on proof, on composition and on data quality.
3. 3Broad merchandising and search suites: 55.0 out of 100. Powerful, and a sensible buy if you need search, filters and merchandising together. For the narrow job of ordering collections they cost more, touch more of the storefront and rarely prove the result.
4. 4Shopify native sorts: 46.8 out of 100. Free, fast, completely safe, and fine for small or stable catalogues. Very little ranking logic and no composition at all.
5. 5Manual drag-and-drop: 38.8 out of 100. Total control and zero cost in money, paid for in hours, and out of date the day after it is set.

The gap between first and second is large, and we want to be upfront about why. It isn't that the other options are bad at sorting. Most of them sort perfectly well. It's that three of the ten criteria, composition, proof and correctness checking, are areas where most of the field scores low, and they carry heavy weights because they decide whether a sorting change is still helping in month three. If you think those three matter less than we do, change the weights. The ranking section near the end shows how.

Why this ranking compares approaches, not brand names

Most 'best apps' lists name ten apps and give each a paragraph. We deliberately don't. Partly that's a rule we keep across everything we publish: we don't make claims about other companies' products, because feature pages change monthly and a stale claim about someone else's tool is unfair to them and useless to you. Partly it's that brand-by-brand lists age badly. The tool you read about this month may have a new plan, a new owner or a new approach next month.

Approaches age much more slowly. A tool that reorders the grid with a browser script will always carry the costs that come with that. A tool that sorts by one metric per collection will always struggle to give the first row and the tail of the page different jobs. A tool that doesn't keep versions will never be able to show you what one order earned against another. Once you know which approach a tool takes, most of its score follows. So we rank the approaches, and give you the questions that reveal which approach any specific app takes.

How the scorecard works

Each option gets a score from 0 to 10 on each of ten criteria. Each criterion has a weight, and the weights add up to 100. Multiply each score by its weight, add them up, divide by 10, and you get a total out of 100. That's the whole calculation. Nothing is hidden inside it.

• Criterion 1, order written into Shopify's own sort: weight 10.
• Criterion 2, where the data comes from: weight 10.
• Criterion 3, breadth of ranking logic: weight 12.
• Criterion 4, composition, meaning different rules for different parts of the page: weight 12.
• Criterion 5, a human override that survives automation: weight 10.
• Criterion 6, automation and scheduling: weight 10.
• Criterion 7, proof of what each order did: weight 12.
• Criterion 8, correctness and drift monitoring: weight 8.
• Criterion 9, setup effort and time to a first result: weight 8.
• Criterion 10, total cost at your size: weight 8.

The heaviest weights go to ranking breadth, composition and proof, at 12 each. Our reasoning: those three decide whether a new order is actually better than the old one and whether you can tell. Storefront safety, data, override and automation sit at 10 because they decide whether the tool is safe and usable day to day. Correctness, setup and cost sit at 8. They matter, but a tool that's cheap and quick to set up and still can't give you a better page isn't worth much.

Criterion 1: Is the order written into Shopify's own sort? (weight 10)

There are two ways to change the order a shopper sees. One is to change the order Shopify stores for the collection, so the page is correct from the first byte of HTML. The other is to leave Shopify alone and rearrange the grid in the shopper's browser with a script after the page loads, or to serve the collection through a separate search or listing layer.

A write into Shopify's native manual sort is invisible to the storefront. There's no script to load, nothing to flicker on a slow phone, and nothing a crawler or link preview can miss. Anything that reads the collection through Shopify's APIs, a headless front end, a product feed or a marketing tool, sees the real order. And when you uninstall, the last order simply stays. A browser-side reorder carries the opposite of each of those.

How to test it: open a collection with JavaScript disabled, or view the page source, and check whether the product order matches what the app shows. Then check what happens to that collection in the Shopify admin: if it's on Manual sort with the app's order, the write is native.

Criterion 2: Where does the ranking data come from? (weight 10)

A ranking is only as good as its inputs. There are three common sources. Shopify's own order data is exact for orders and revenue, but says nothing about views or add-to-carts. Google Analytics adds engagement data, but inherits whatever is wrong with the analytics setup, from consent gaps and ad blockers to a property that was configured years ago by someone who has since left. A first-party pixel installed through Shopify's Web Pixels API measures the storefront directly, with no theme edits.

The strongest setup is orders and revenue from Shopify, engagement from a first-party pixel, and analytics only as an optional way to fill in history. The weakest is a tool that depends on a single source you don't control, or one that's vague about where its numbers come from at all.

How to test it: ask the vendor, or read the help pages, for exactly where views, add-to-carts, orders and revenue come from. Then compare the app's order count for one product over 30 days against your Shopify admin. They should match.

Criterion 3: How broad is the ranking logic? (weight 12)

Best selling is one metric. Real merchandising needs several: recent orders and revenue, views and add-to-carts for products that haven't had time to accumulate sales, conversion rate for products that turn attention into purchases, margin and profit for the products you most want to sell, sell-through and days of stock cover for clearance, newness for arrivals, and review rating for gifting and social proof.

Breadth matters less for its own sake than for what it lets you avoid. A tool that can only rank by sales will keep promoting last month's winners and burying anything new. A tool that can blend several metrics into one score, and handle the edge cases honestly, such as tiny samples and missing costs, lets each collection follow the signal that matters for it.

How to test it: list the ranking options in the app's dropdown. Then ask two edge-case questions. What does a product with one view and one order score on conversion rate? And what does profit read for a product with no cost per item? A tool that answers '100%' and 'an estimate' will mislead you.

Criterion 4: Can it compose, or only sort? (weight 12)

Sorting applies one rule to the whole page. Composition gives different parts of the page different jobs. The first row has to convert, so it should be in-stock products that are selling right now. The next few rows should make the page feel alive, so they can hold fresh arrivals that people are looking at. The rest of the page can follow steady revenue. Out-of-stock products belong at the end.

That's how a merchandiser thinks about a shelf, and it's hard to express with one ranking. You need slices of the page, each with its own conditions and its own order, filled top-down, with a rule for what happens when a slice doesn't have enough matching products. Our full explanation is in the article on percentage-slot merchandising.

How to test it: try to set up 'the first 20% is in-stock bestsellers from the last week, the next 20% is new arrivals from the last 30 days, the rest is by revenue'. If you can't express that in one rule, the tool sorts but doesn't compose.

Criterion 5: Does a human override survive automation? (weight 10)

Data doesn't know that a campaign starts on Monday, that one product photographs beautifully, or that a supplier has quietly discontinued a line. So every automatic order needs a human override: pin this product to the top, push that one to the end, put this one at position seven.

The override is only useful if it lasts. An automatic re-sort that wipes a merchandiser's pins teaches the team not to trust the tool, and within a month the automation gets switched off. The test is whether pins and placements survive every recompute, and whether the preview shows which positions were set by hand.

How to test it: pin a product, trigger a re-sort, and check it's still pinned. Then check whether the tool shows you where the rules alone would have placed it.

Criterion 6: Automation and scheduling (weight 10)

A good order goes stale. Stock changes daily, demand shifts weekly, and campaigns start and end on dates. Automation means the order is recomputed from fresh numbers on a rhythm without anybody opening the app. Scheduling means a planned order can go live at a date and time, and the previous order can come back automatically when the campaign ends.

The details decide whether this works for a real calendar. Does the schedule run in the store's own time zone? What happens to a run missed during an outage? Can you stage a change as a draft without touching the live order? Can you roll back to any previous order in one step?

How to test it: set up a sale order as a draft with a go-live date tomorrow and a revert date the day after. Check that the live order doesn't change until tomorrow, and that the old order returns on its own.

Criterion 7: Can it prove what each order did? (weight 12)

This is the criterion that separates most of the field. Every sorting app promises a better order. Very few can show you, in numbers, whether the new order beat the old one. If conversion rose the week you changed the order, was it the order, the season, a newsletter or the ad budget?

The honest answer needs attribution: every published order kept as a version, and the collection's daily views, add-to-carts, orders and revenue attributed to whichever version was live, shown side by side. It isn't a controlled experiment, and a tool shouldn't pretend it is. But it turns a feeling into evidence. We covered the measurement side in full in the article on proving a collection order change worked.

How to test it: publish two different orders a week apart and ask the tool which one did better. If the answer requires exporting data into a spreadsheet and lining up dates by hand, the tool doesn't prove anything.

Criterion 8: Correctness and drift monitoring (weight 8)

Two failure modes matter here. The first is a write that doesn't land exactly as previewed: pushing an order into Shopify means translating a sequence into a list of moves, and a small mistake shifts every position after it. The second is drift: someone changes the sort in the admin, a bulk edit reshuffles positions, or another app writes its own order, and the collection quietly stops being what you published.

Good tools read the order back after every push and confirm it matches, and check on a schedule that Shopify still holds the order. Bad ones assume success and never look again.

How to test it: after a sync, change a collection's order by hand in the Shopify admin. Does the app notice? How long does it take? Can you restore the intended order in one click?

Criterion 9: Setup effort and time to a first result (weight 8)

The best tool on paper is worthless if it needs a developer, a theme edit and a week of configuration before the first collection changes. We score the path from install to a live, reordered collection: permissions, theme changes, data setup and the number of decisions needed before you see a preview.

How to test it: time it. Install, pick your busiest collection, and see how long it takes to get a previewed order live on the storefront.

Criterion 10: Total cost at your size (weight 8)

Price includes the subscription, the plan tier your collection count forces you into, and the hours your team spends. A free option that costs a merchandiser four hours a week isn't free. A cheap app that needs a developer to install isn't cheap. A free plan that's a trial in disguise doesn't help you decide.

How to test it: count the collections you'd actually want ordered by rules, find the plan that covers them, and add a realistic estimate of the hours the option needs every month.

The full score table, criterion by criterion

Here is every score behind the totals. The format is SellRank / rule-based apps / merchandising suites / native sorts / manual order. Each is out of 10, and each option's reasoning follows in its own section below.

• 1. Order written into Shopify's own sort (weight 10): 10 / 7 / 4 / 10 / 10.
• 2. Where the data comes from (weight 10): 9 / 5 / 7 / 4 / 0.
• 3. Breadth of ranking logic (weight 12): 9 / 6 / 7 / 2 / 0.
• 4. Composition (weight 12): 10 / 5 / 7 / 0 / 3.
• 5. Human override that survives automation (weight 10): 9 / 6 / 7 / 2 / 10.
• 6. Automation and scheduling (weight 10): 8 / 7 / 7 / 6 / 0.
• 7. Proof of what each order did (weight 12): 9 / 2 / 3 / 0 / 0.
• 8. Correctness and drift monitoring (weight 8): 9 / 4 / 5 / 8 / 5.
• 9. Setup effort and time to first result (weight 8): 9 / 8 / 4 / 10 / 7.
• 10. Total cost at your size (weight 8): 8 / 8 / 3 / 10 / 7.
• Weighted totals out of 100: SellRank 90.4, rule-based apps 56.6, merchandising suites 55.0, native sorts 46.8, manual order 38.8.

Two things jump out. First, the native options score full marks on storefront safety, and native sorts win outright on setup and cost. That's deserved, and it's why they remain the right answer for some stores. Second, proof is where the whole field is weakest. If you remove criterion 7 entirely and rescale, SellRank still leads, but its gap to second place narrows from about 34 points to about 29. That's worth knowing: our lead rests partly on a feature we think matters a lot, and you may weigh it differently.

1. SellRank: why it ranks first (90.4)

SellRank is the Shopify collection sorting app we build at LeelaRam Technologies. Its engine began on a live jewellery store, where collection order had a visible effect on sales, and was then generalised to work on any catalogue. Here is how it scores, criterion by criterion, including the points it drops.

• Native write, 10: SellRank switches a collection to Manual sort and writes the computed order into Shopify. Nothing runs in the shopper's browser, so there's no script, no flicker and nothing for crawlers to miss. On uninstall the last order stays.
• Data, 9: views and add-to-carts come from a first-party pixel that installs itself through Shopify's Web Pixels API the first time the app opens, counting aggregates per product per day with no customer identifiers. Orders and revenue come straight from your Shopify orders. It drops a point because a new pixel needs days to build history, and the GA4 import of up to 90 days of engagement history is only on Scale and Max.
• Ranking breadth, 9: 19 ranking strategies, including views, add-to-carts, orders and revenue over 7 or 30 days, conversion rate, estimated profit, margin, review rating, sell-through, days of stock cover, newness, price, discount, inventory units and a rank-normalised Balanced score. Conversion reads zero below five views, and profit reads zero where cost per item is missing, instead of guessing. It drops a point because profit and margin need the Scale plan and cost data.
• Composition, 10: percentage slots, each with its own conditions and ranking, filled top-down, with a slot's shortfall passed to the next, an 'everything else' order and out-of-stock parking.
• Human override, 9: pins, demotions, drag-and-drop and exact positions that survive every recompute, with the preview showing where the rules alone would have placed each product. It drops a point because pinning is switched off on the store-wide global rule; to curate a collection by hand it needs its own smart sort.
• Automation, 8: daily or weekly re-sorts at an hour in the store's own time zone, with missed runs caught up the same day, plus drafts, scheduled go-live and automatic revert. It drops two points because re-sorts run daily at most (you can still press Sync now any time), and scheduling needs the Grow plan.
• Proof, 9: every published order is kept as a version, and daily views, carts, orders and revenue are attributed to the version that was live. It's attribution, not a controlled experiment, and SellRank says so, which is why it's a 9.
• Correctness, 9: the move planner is verified on 78,240 cases, every position is read back from Shopify after each sync, and an hourly health check flags drift. One-click re-sync from a drift alert comes with Scale and Max.
• Setup, 9: install, open, pick a collection, preview, sync. No theme edits and no code. The setup guide puts it at about five minutes.
• Cost, 8: a permanently free plan on one collection with the full editor and one live sync, then Grow at $29 a month, Scale at $69 and Max at $249, with a 7-day free trial on paid plans and two months free on yearly billing. It drops points against the native options, which cost nothing.

Who SellRank is right for: any store where the first row of a collection decides the day, which on phones is most stores with more than a couple of dozen products per collection. It's especially strong for catalogues that mix stocked and made-to-order products, stores that run regular campaigns, and teams that need to show someone evidence that a merchandising change worked.

Who it isn't right for: a store with one small collection that never changes, where Shopify's own sort is free and fine. And stores looking for search, filters or per-shopper personalisation. SellRank orders the products inside a collection; every shopper sees the same order, which is what makes the result measurable and indexable.

2. Generic rule-based sorting apps (56.6)

This is the largest category: apps that automate one sorting rule per collection, such as bestsellers over a window, newest first, in-stock first or a price order, and re-run it on a schedule. Many do that job well and cheaply. The category earns second place because it genuinely beats manual and native options on automation and ranking breadth, and because many tools in it write into Shopify's own sort.

• Native write, 7: many rule-based apps write into Shopify's manual sort, some reorder elsewhere. Check each one.
• Data, 5: most rely on Shopify's order data alone, sometimes with analytics for views. Few measure engagement themselves.
• Ranking breadth, 6: typically sales, newness, stock and price, sometimes more. Conversion, profit and stock cover are less common, and edge-case handling is often undocumented.
• Composition, 5: 'push out-of-stock to the bottom' and 'pin these to the top' are common; independent slices of the page with their own rules are much less so.
• Human override, 6: pinning is common; whether pins survive every re-sort varies.
• Automation, 7: this is the category's strength. Scheduled re-sorts are the point of these apps. Drafts, go-live dates and automatic revert are less common.
• Proof, 2: very few keep versions or attribute results to each order.
• Correctness, 4: read-back after a push and drift monitoring are rarely mentioned.
• Setup, 8: usually quick.
• Cost, 8: usually affordable.

Who a rule-based app is right for: a store that wants one simple rule, such as 'bestsellers from the last 30 days, sold-out at the bottom', applied automatically, and doesn't need to compose the page or prove the result. If that's you, the category will serve you, and SellRank's own single-metric smart sorts do the same job if you want room to grow into slots later.

3. Broad merchandising and search suites (55.0)

These are larger platforms where collection merchandising is one module among search, filtering, recommendations and sometimes personalisation. They're often capable, and for a store that needs all of those things together, buying one suite can be simpler than buying several apps.

• Native write, 4: many suites deliver their ordering through their own search or listing layer rather than Shopify's stored collection order. That's a design choice that suits search, but it means the order may not exist in Shopify itself.
• Data, 7: usually rich, often from their own tracking.
• Ranking breadth, 7: usually broad.
• Composition, 7: boosting and burying rules are common, sometimes with slot-like controls.
• Human override, 7: usually present.
• Automation, 7: usually present.
• Proof, 3: analytics are common, but attribution of results to specific published orders is less so.
• Correctness, 5: when the order lives in the suite's own layer, drift in Shopify matters less, but read-back of a Shopify write is rarely the point.
• Setup, 4: more to configure, and often theme or storefront integration work.
• Cost, 3: typically priced for a larger feature set than collection ordering needs.

Suites finish third by a narrow margin, and for some stores they should finish first. If your real problem is search and filtering, and collection ordering is secondary, score a suite on search criteria, not on ours. For the narrow job of ordering collections, a suite is more tool, more storefront footprint and more cost than the job needs.

Who a suite is right for: larger catalogues with a search problem, teams that want personalisation, and stores with the budget and staff to configure a platform. It can sit alongside SellRank if the suite's collection pages read Shopify's stored order; check that before running both.

4. Shopify native sorts (46.8)

Every Shopify collection can be set to Best selling, Alphabetical, Price, Date or Manual. They're free, they're built in, and they can't break anything. For a small store with stable demand, Best selling is a perfectly reasonable default, and we'd rather say so than pretend otherwise.

• Native write, 10: by definition.
• Data, 4: Best selling uses sales history only, with no window you control, no views and no stock awareness.
• Ranking breadth, 2: a handful of fixed orders, none of them conversion, margin, sell-through or stock cover.
• Composition, 0: one rule per collection, no slices, no conditions.
• Human override, 2: switching to Manual gives you control, but then nothing automatic runs.
• Automation, 6: Best selling and Date update by themselves, which is real value. There's no scheduling.
• Proof, 0: nothing.
• Correctness, 8: there's nothing to drift from, because Shopify computes it. It's not a 10 only because you get no alert if someone changes a collection's sort setting.
• Setup, 10 and Cost, 10: nothing to install, nothing to pay.

The biggest weaknesses in practice: a sold-out hero product can sit in position one, last year's winner can outrank this week's breakout, and a new product has no way to earn a place. We cover each option and exactly where it breaks in every Shopify collection sort option explained, and compare them head to head with SellRank in the comparison of SellRank, Shopify best selling and manual sorting.

Who native sorts are right for: new stores with little data, stores with one or two small collections, and anyone who wants zero moving parts. When your first row starts showing sold-out products or last season's stock, it's time to move up.

5. Manual drag-and-drop (38.8)

Manual sort gives a merchandiser complete control. You can express any composition you like, because you are the composition. It costs nothing in subscriptions and it's perfectly safe. It's also the most expensive option on this list in hours, and the one that goes out of date fastest.

• Native write, 10: it's Shopify's own manual order.
• Data, 0 and Ranking breadth, 0: there's no data in the loop unless someone pulls reports and arranges tiles by them.
• Composition, 3: anything is possible by hand, but nothing is repeatable.
• Human override, 10: it's nothing but override.
• Automation, 0: nothing changes until someone changes it.
• Proof, 0: nothing is recorded.
• Correctness, 5: what you drag is what you get, but nobody tells you if a bulk edit or another app reshuffles it.
• Setup, 7 and Cost, 7: nothing to install, but real hours every week on any catalogue of size.

Who manual order is right for: a small edit, such as a home page feature of eight products or a lookbook collection, where every position is a creative decision. For anything bigger, a manual order is a photograph of one afternoon. If you're searching for an alternative to manual sorting on Shopify, the honest answer is automation with a human override, so the few positions that need a person keep one and the rest follow the data.

Who each option is right for, in one list

• SellRank: stores where collection order visibly affects sales, catalogues with a mix of stocked and made-to-order products, stores that run campaigns on a calendar, and teams that need evidence. Start on the free plan with one collection.
• Rule-based sorting apps: stores that want one simple automatic rule per collection and don't need composition or proof.
• Merchandising and search suites: larger stores whose main problem is search and filtering, with budget and staff for a bigger platform.
• Shopify native sorts: new or small stores, stable catalogues, and anyone who wants nothing to maintain.
• Manual drag-and-drop: small, creative edits where every position is a deliberate choice.

How to re-score this ranking for your own store

The point of publishing weights is that you can change them. Our weights reflect what we think matters for a typical mid-sized catalogue. Yours may differ, and the ranking should follow your priorities, not ours.

1. 1Write down the ten criteria and give each a weight that reflects your store. If you have no one to act on performance data, lower proof. If you run three campaigns a month, raise automation. Make the weights add to 100.
2. 2For each tool you're considering, score it 0 to 10 on each criterion using the tests described above, not the marketing page. Where you can't test something, score it low until you can.
3. 3Multiply, add, divide by 10.
4. 4Look at where the top two options differ by three points or more. Those are the criteria that should decide your choice, so test them hardest during a trial.
5. 5Re-score after a month of real use. A tool that scored well in a demo and badly in week four has told you something.

A worked re-scoring example (illustrative)

Here's how the weights can move the ranking. This example is illustrative, not a real store. Imagine a small beauty brand with six collections, stable demand, no campaigns and nobody who will look at analytics. They might weight setup and cost at 20 each, storefront safety at 15, data at 10, breadth at 10, override at 10, automation at 10, correctness at 5, and composition and proof at 0.

Run the same scores through those weights and the totals come out at 88.5 for SellRank, 73 for native sorts, 68.5 for rule-based apps, 55.5 for manual order and 50.5 for suites. SellRank still leads, largely because its free plan and five-minute setup score well on the criteria this store cares about, but Shopify's native sorts jump from fourth to second. For a store with those priorities, the free built-in sort is a perfectly defensible choice, and the scorecard is doing its job by saying so.

Now imagine a fashion brand with 60 collections, weekly drops and a founder who wants proof before renewing anything. Weight proof at 18, composition and automation at 15 each, breadth at 10, storefront safety, data and override at 8 each, and correctness, setup and cost at 6 each. The totals become 90.2 for SellRank, 55 for suites, 54 for rule-based apps, 40.6 for native sorts and 31.9 for manual order. Suites and rule-based apps swap places, and the native options fall well behind. Same scores, different store, different answer. That's what a transparent method should do.

What SellRank doesn't do, so you can rule it out quickly

• It doesn't personalise. Every shopper sees the same order.
• It doesn't do search or filtering. Your theme's filters and sort dropdown keep working on top of SellRank's order.
• It doesn't decide which products belong in a collection. Shopify's smart and manual collections still do that; SellRank orders them.
• It doesn't rank variants separately. It ranks products, rolling up variant sales, and treats a product as available if any variant can be bought.
• It doesn't re-sort more often than daily on a schedule. For anything in between, Sync now runs on demand.
• It doesn't read costs it doesn't have. Profit and margin need cost per item filled in on your products.

If any of those is a dealbreaker, the scorecard above already tells you which category to look at instead.

Questions that reveal any sorting app's approach in five minutes

You don't need to trust our category scores. Ask these of any tool, including ours, and its approach becomes clear quickly.

• Does the order live in Shopify's manual sort, or in a script or separate layer?
• Where exactly do views, add-to-carts, orders and revenue come from?
• Can the first 20% of a page follow a different rule from the rest?
• Do pins survive a scheduled re-sort?
• Can a sale order go live on a date and revert on its own?
• Is every published order kept as a version I can restore?
• Can you show me, per version, the views, carts, orders and revenue while it was live?
• Do you read the order back after pushing it, and tell me if it drifts?
• What happens to my collections if I uninstall?

Our longer treatment of how to evaluate a tool, with vendor questions, red flags and a trial plan, is in the Shopify visual merchandising software buyer's guide.

What would change this ranking

A ranking that can't be wrong isn't worth reading. Here's what would move ours. If rule-based apps commonly added version history and per-version attribution, their proof score would rise and the gap to SellRank would narrow sharply. If a suite wrote its order into Shopify's native sort and priced a collection-only tier, it would move up. If Shopify added windows, stock awareness and composition to its native sorts, the free option would become a much stronger competitor, and we'd say so. And if SellRank ever stopped verifying its writes or keeping versions, it should drop. We'll update this article when the categories change.

Our method, restated so you can hold us to it

• LeelaRam Technologies makes SellRank. That conflict of interest is why the method is public.
• We rank categories of approach, not named products, and make no claims about any specific competitor.
• Every SellRank score is based on features documented on the SellRank product page and setup guide, and can be checked on the free plan.
• Category scores describe a typical tool in that category. Individual tools vary.
• No review counts, ratings, install numbers or awards are used, because we don't have independent ones to cite and we won't invent them.

Try the top-ranked Shopify collection sorting app free

The quickest way to test this ranking is to test first place. SellRank's free plan has no end date: one collection, the full editor, live preview, pins, demotions and drag-and-drop, and one live sync to your storefront. Pick the collection you know best, read the preview, and score it against the ten criteria yourself. If it doesn't earn its place, the scorecard has told you what to look for instead. Install it from the SellRank product page, and follow the setup guide or the five-part SellRank tutorials if you'd like a hand.