A shopper lands on your store and types "flowy midi dress for a wedding guest." Your search bar returns zero results. Or worse, it shows a random assortment of products that have nothing to do with what she asked for. She leaves. You paid to get her there.
This is what keyword-based search does. It matches words, not intent. And when your catalog has hundreds or thousands of products, the gap between what shoppers type and what your search returns is where revenue disappears.
If you've started looking at AI search apps, you already know the default Shopify search has limits. It runs on keyword matching, handles a handful of filter types, and gives you almost no data on what customers are actually searching for. The harder question is how to evaluate the AI search apps competing for your attention. There are over a dozen on the Shopify App Store, and their marketing pages all say roughly the same things.
Here are the five criteria that actually separate the good ones from the expensive disappointments.
1. Does it understand what your customers mean?
Most merchants skip this step entirely, and it's the one that matters most.
Keyword search matches the exact words a customer types against your product titles and descriptions. AI-powered semantic search is supposed to understand the intent behind the query. The difference matters when a shopper types "comfortable black shoes for standing all day" and your products are tagged as "cushioned support flats" or "ergonomic work shoes." Keyword search returns nothing. Semantic search should connect those dots.
When you're testing a search app, run these queries before you commit:
Start with a natural language phrase, not a product name. Something like "lightweight jacket for spring travel" or "gold earrings under $50." Does the app return relevant results, or does it choke on anything beyond two-word queries?
Then misspell a product name deliberately. Type "cashmeer sweater" or "earing" and see what happens. Typo tolerance sounds basic, but plenty of apps still fail this test.
Finally, search for an attribute that isn't in the product title. If you sell dresses and a customer types "v-neck," does the app know which products have v-necklines even if "v-neck" isn't in the title? This tells you whether the search understands your catalog beyond scanning text fields.
At PersonalizerAI, we train custom AI models on each merchant's specific catalog, order history, and customer behavior. The search learns the relationships between products, attributes, and how your customers actually shop. When someone searches "complete outfit for date night," the results factor in what your customers have actually bought together, not a keyword match against product titles.
2. How does the pricing actually work?
Search app pricing falls into three models, and which one you're on determines whether the app is a good investment or a slow drain.
Flat monthly fees are the most common. You pay a fixed amount regardless of whether the search drives any revenue. Common tiers range from $19 to $299 per month depending on your product count or traffic volume. Predictable, yes, but you're paying the same amount whether the app is performing or sitting idle. If your search conversion rate doesn't improve after installing it, you're still writing that check.
Per-query pricing charges based on how many search queries your store handles. This can work if you have low traffic, but it scales fast. A store with 50,000 monthly sessions might generate 15,000-20,000 search queries. At fractions of a cent per query, that adds up. During a holiday sale or a viral social post, your search bill spikes right when you can least afford surprises.
Then there's performance-based pricing, where you pay a base fee plus a commission on revenue the search actually generates. This is PersonalizerAI's model: $29.99 per month base, plus a percentage of the revenue our AI-driven search and recommendations produce. If the app doesn't drive revenue, your cost stays at $29.99. If it drives $10,000 in additional revenue, the commission reflects that. We only make more when you make more, which means our incentive is to make the search actually work.
Run the math for your store before you sign up for anything. Take your monthly sessions, estimate your search usage rate (typically 30-40% of visitors use site search), and calculate what each pricing model would cost at your current volume. Then calculate it at 2x volume, because that's where per-query pricing starts to hurt.
3. Can you actually verify what it's doing?
Attribution is where search apps get slippery.
Some apps use session-based attribution: if a customer searches for something and then buys anything during that session, the search gets credit. Others use view-based attribution: if a search result appeared on screen, it counts. Both methods inflate the numbers. A customer who searched "returns policy," then browsed for ten minutes, then bought a product she'd already saved in her cart... that's not a search-driven sale.
Click-only attribution is the standard worth demanding. The customer searches, clicks a result from the search, and purchases that product. You can verify this in your Shopify analytics because the click creates a traceable path from search to product page to checkout.
Beyond attribution, look at what analytics the app gives you. The metrics that matter: your zero-result rate (what percentage of searches return nothing), search conversion rate (what percentage of searchers buy), and revenue per search session. If a search app can't show you these numbers, you can't evaluate whether it's working.
PersonalizerAI's search analytics dashboard shows all three, along with the specific queries driving revenue and the ones returning zero results. You can see exactly which searches need attention and which are already converting. Click-only attribution means the numbers you see are the numbers that actually happened, and you can cross-reference them in Shopify.
4. What does setup look like, and will it slow down your store?
Two things merchants consistently overlook: implementation time and page speed impact.
Some search apps require developer resources to install. Custom API integrations, theme file edits, JavaScript configuration. If you're running a lean operation without a dedicated developer, a multi-day implementation is a real cost in time and energy, even if the app itself has a free trial.
Then there's speed. Search widgets that load synchronously can add 200-500ms to your page load time. That matters. Google penalizes slow pages in search rankings, and every 100ms of added load time costs you conversions. Ask any search app how their widget loads. The answer should be asynchronous, with no render blocking.
PersonalizerAI installs in about 30 minutes with no developer needed and loads asynchronously so it doesn't affect your page speed. If your Core Web Vitals are already tight, this is the kind of thing that matters more than the feature list.
5. Does search work alone, or with the rest of your product discovery?
Most search apps operate in isolation. They handle the search bar and nothing else. Your product recommendations come from a different app entirely, with its own AI model, its own analytics, and its own monthly invoice.
The problem is that search and recommendations are solving the same underlying challenge: helping customers find the right products. When those systems don't talk to each other, you get disconnected experiences. A customer searches for "navy blazer," finds one she likes, and the recommendation widget below the product suggests completely unrelated items because it doesn't know what she just searched for.
When search and recommendations run on the same AI, the data compounds. What customers search for makes the recommendations smarter, and what they buy makes the search rankings better. The customer gets a coherent experience instead of two systems guessing independently.
PersonalizerAI is built this way. Search and recommendations share the same AI layer, trained on your catalog and customer behavior together. You manage it all from a single dashboard, and you pay a single performance-tied bill.
Before you commit, run this test
Pick two or three search apps and run the same evaluation on each. Type five real queries your customers would use (check your existing search analytics or customer service tickets for ideas). Note the results for each query. Check the attribution method. Calculate pricing at your current traffic and at double your traffic. Time the setup. Check your page speed before and after.
You'll see real differences fast.
If you want to run this test with PersonalizerAI, you can start a free trial and be live in 30 minutes. Compare your zero-result rate and search conversion rate before and after. The numbers do the talking.