Your store has the right products, but customers still struggle to find them. Before replacing search, test a few real queries and separate what needs better product data, a settings change or a different shopping experience. Keep Shopify Search & Discovery if those fixes meet your needs; consider an app or custom work when a specific, repeatable requirement remains unmet.
1. Name the problem before choosing the tool
“Search is bad” is difficult to price or fix. “Someone searching for a particular fragrance sees the body wash before the perfume” gives your team something to investigate. Save the exact words, the expected product and what actually appeared.
Try the query in the suggestions shown while typing and again on the page reached by pressing Enter. Record the language, market and device. Ask your developer which system supplies each result: Shopify, an installed app or custom code.
Shopify already includes typo handling, so a misspelling doesn't automatically justify buying another search engine. Its search behavior documentation also distinguishes native search from third-party apps that control their own results. Test the system your customers actually use.
For an illustrative beauty store, start with a full product name, a common misspelling, a broad category and an exact shade. Agree what a useful result looks like for each. These examples and the worksheet below are my proposed evaluation process; the SwiftSearch decisions I describe are documented work from my own project.
2. Give the existing setup a fair trial
Choose products your team knows well. Check that their descriptions and attributes describe what the shopper is asking for, then review the settings relevant to the failure. Keep a record of the original result so you can tell whether a change helped.
Search & Discovery lets you promote selected products for particular terms and control how unavailable products appear. Shopify's search customization guide explains these controls and notes that theme requests can override result-type settings. A setting that appears ineffective may need a theme investigation before a replacement app.
For large catalogs, check the size of the affected collection separately from the whole store. Shopify's filter documentation says collections above 5,000 products don't display native filters. Consider whether smaller, useful collections would serve the shopping task before treating that limit as a reason to replace search everywhere.
If a filter is missing even on a small collection, use the metafield filter diagnostic checklist first. It helps separate theme support from missing product values. The buying decision becomes much clearer once you know which part is failing.
3. Separate the search engine from the shopping experience
Sometimes the right product appears, but buying it is awkward. A customer might need to choose a size without losing their query, or understand whether an add-to-cart action worked. Put that interaction into the brief instead of asking vaguely for “better AI search.”
In SwiftSearch, I built result cards with a variant picker and an add-to-cart action that hands off to the theme's cart drawer. The mobile panel confirms the addition with an Added state and a View cart link. Those are concrete interface decisions you can demonstrate without making a claim about revenue lift.
The loading cost matters too. SwiftSearch uses a 4.5 KB gzipped core and fetches its 18 KB interface when focus or hover signals search intent. My deferred search widget guide explains the implementation pattern; for a buying review, the useful question is whether the first search stays usable while that interface loads.
Ask for separate estimates when the work can be separated: improving the panel, changing matching or ranking, and maintaining the product data used by search. You may need one of those jobs. A proposal should explain why it includes the others.
4. Compare every option with the same worksheet
Use this table during a demonstration of your configured native search, a candidate app or a custom prototype. Replace the examples with actual products from your store. Mark an untested requirement as unresolved, rather than accepting a feature label as proof.
| Trial | What you want to see | What to record |
|---|---|---|
| Exact product and shade | The intended item is easy to identify | Query, product link and visible result position |
| Misspelled product name | A useful match without unrelated substitutions | Expected item and an example that must stay distinct |
| Broad category with filters | Shoppers can narrow to a useful assortment | Collection or search URL, selected values and result set |
| Mobile variant selection | The intended size reaches the cart | Selected variant, cart contents and confirmation |
| Product becomes unavailable | Results follow your agreed availability policy | Time of change, time checked and observed behavior |
| First search on a fresh visit | Typing, results and recovery remain usable | Device, connection conditions and any lost input |
For example, suppose a shopper chooses the 50 ml fragrance in a search card. A successful trial should show that exact variant in the cart and make the confirmation clear. Finding the fragrance family is only part of the task.
Add an operator check beside the shopper checks. Have the person who manages merchandising make one ordinary change and explain how they'd undo it. If every adjustment requires developer support, decide whether that arrangement fits your team's working day before approving it.
5. Make custom control earn its upkeep
A custom project is worth exploring when you can name the behavior you need and show why the options you've tested don't meet it. That might be a particular ranking rule or a tightly integrated buying interaction. Describe the rule with example products and expected results so it can be accepted or rejected objectively.
In SwiftSearch, I gave an add-to-cart five times the weight of a click and used a seven-day half-life so older engagement loses influence. That is one documented ranking design, not a universal recipe. If you need comparable control, ask how the proposed system will keep relevant products visible and let your team inspect unexpected ordering.
Require a maintenance plan alongside the demonstration: who investigates stale products, how failed updates are noticed, what support covers and how the previous search experience can be restored. Ask for those responsibilities in the proposal, without assuming an app or custom build removes them.
Agree what the reporting means as well. I chose line-item attribution in SwiftSearch so an order containing both searched-for and browsed products credits only the searched-for line. When comparing dashboards, ask what gets credit and which shoppers the tracking can observe; a larger reported total alone doesn't establish a better search experience.
6. Start with the searches you can explain
Choose a small set of queries your team can judge confidently. Fill in the worksheet as you test your current setup, then write down the remaining failures. That record is useful whether you keep Search & Discovery, trial an app or commission a focused change.
If you'd like help turning those failures into a scoped project, send the worksheet through my Shopify search and merchandising enquiry page, or book a call. Bring your store URL, current search provider and the products you expected to find.