Autocomplete

Have you ever started typing a search and before you finish, the perfect suggestion appears? You click it, saving yourself several keystrokes and immediately getting results. That’s autocomplete, and it’s one of those features that seems like magic when it works well.

Autocomplete is the dropdown list of suggestions that appears as you type in a search box. Type “run” and it might suggest “running shoes”, “running watch”, “running shorts”. You can click any suggestion to immediately search for it, saving time and effort.

This might seem like a small convenience, but autocomplete dramatically improves the search experience, especially on mobile where typing is slow and tedious.

Why autocomplete matters more than you think

Let’s say you sell sports equipment. A customer starts typing “runni…” and stops. They’re not sure exactly what they want, maybe running shoes, maybe running gear in general. Without autocomplete, they have to finish typing, search, browse results, maybe refine their search.

With good autocomplete, they see suggestions immediately: “running shoes”, “running watch”, “running clothes”, “running accessories”. They spot “running shoes” and click. Instantly, they’re looking at exactly what they wanted, without finishing their query or browsing through broad results.

This is the power of autocomplete: it helps customers articulate what they want. Often, people don’t know the exact term to search for. Autocomplete shows them the options, guiding them to the right query.

Studies show that autocomplete increases search engagement by 20-30%. More importantly, it reduces the time from “I need something” to “here’s what I want” from minutes to seconds.

How autocomplete learns what to suggest

Good autocomplete isn’t random, it’s showing you the most likely helpful suggestions based on several data sources.

First, it looks at your product catalog. If you type “blue”, it checks what products actually contain “blue” in their titles or descriptions. This ensures suggestions lead to actual results.

Second, it considers what other customers search for. If hundreds of people search for “winter coats” but only a few search for “winter jackets”, “winter coats” appears higher in the suggestions. Popular searches get priority because they’re more likely to be what you want too.

Third, sophisticated autocomplete learns from success. If many customers search for “waterproof jacket”, click on a specific product, and buy it, that query gets boosted. The system learns that “waterproof jacket” is a valuable search that leads to purchases.

Fourth, it can personalize. If you’ve previously searched for men’s clothing, suggestions might prioritize men’s products when you type something ambiguous like “shoes”.

All of this happens in milliseconds, creating suggestions that feel eerily accurate and helpful.

The mobile keyboard problem

Autocomplete becomes even more valuable on mobile devices. Here’s why:

Mobile keyboards are small and awkward. Typing “comfortable running shoes for beginners” on a phone keyboard is tedious and error-prone. But typing just “comf…” and seeing “comfortable running shoes” as a suggestion? Much easier. One tap and you’re done.

Mobile shoppers are often multitasking, browsing while commuting, watching TV, or doing other things. Quick, efficient search matters. Autocomplete turns a potentially frustrating 30-second typing session into a 3-second tap.

This is why good mobile autocomplete is essential. It’s not just a nice-to-have feature; it’s the difference between mobile search being usable versus frustrating.

Different types of suggestions

Autocomplete can show different types of suggestions, and the best implementations mix them strategically:

Query completions finish what you’re typing. Type “running” → see “running shoes”, “running watch”, “running shorts”. These help you articulate your search without typing the full query.

Product suggestions show actual products with images. Type “nike” → see specific Nike products with thumbnails. This is powerful because customers can sometimes skip the results page entirely, clicking directly on the perfect product from the dropdown.

Category suggestions guide you to broader sections. Type “men” → see “Men’s Clothing”, “Men’s Shoes”, “Men’s Accessories”. This helps customers who aren’t sure exactly what they want but know the general area.

Popular searches show what other customers commonly look for. This is valuable for discovery, customers might not know certain products exist until they see them suggested.

The best autocomplete mixes these strategically. Maybe show 2-3 query completions at the top, then 3-4 products with images, then 1-2 category links. This gives customers multiple paths to find what they want.

When autocomplete goes wrong

Poor autocomplete is worse than no autocomplete. Let me show you what that looks like:

Slow suggestions that lag behind your typing feel broken and distracting. You type “running shoes” but the dropdown is still showing suggestions for “run”. This disrupts your flow and makes you ignore the feature.

Too many suggestions overwhelm rather than help. Showing 20 options means customers have to read and evaluate too many choices. Keep it to 5-8 suggestions max.

Irrelevant suggestions make the feature useless. If you type “laptop” and see suggestions for completely unrelated products, you learn to ignore autocomplete entirely.

Suggesting out-of-stock products is frustrating. Customers click the suggestion, see the product is unavailable, and feel misled.

Getting autocomplete right means making it fast (under 50 milliseconds), relevant (based on actual data), focused (not too many options), and valuable (leads to results customers want).

Autocomplete as a learning tool

Here’s something interesting: autocomplete doesn’t just help customers search, it teaches them what language works in your store.

A customer might not know you sell “thermal underwear”. They start typing “warm under…” and autocomplete suggests “thermal underwear”. Now they know the right term to use. They’ve learned how to search your catalog more effectively.

This is especially valuable for specialized products with industry-specific terminology. Customers might call something by a colloquial name while your catalog uses technical terms. Autocomplete bridges this gap, showing them the “correct” terminology while still recognizing their natural language.

The analytics goldmine

Autocomplete generates incredibly valuable data. You can see what customers start typing but don’t finish, these abandoned queries suggest confusion or frustration. You can see which suggestions get clicked versus ignored, this shows which products or categories resonate with customers.

You can identify gaps in your catalog. If many customers search for “blue running shoes size 11” but you don’t stock that combination, autocomplete analytics reveal this missing opportunity.

You can spot trends early. If autocomplete shows “summer dresses” suddenly getting lots of queries, that’s an early signal of seasonal demand.

What this means for your webshop

Autocomplete is one of those features that customers notice when it’s missing or broken, but take for granted when it works well. That’s the sign of good design, invisible but valuable.

For your webshop, autocomplete means customers find products faster, with less frustration and fewer abandoned searches. It means mobile customers can shop efficiently despite small keyboards. It means customers discover products they might not have known to search for.

Modern search solutions like TextAtlas include intelligent autocomplete by default. It learns from your product catalog and customer behavior automatically, suggesting the most relevant queries without manual configuration. The suggestions get smarter over time as the system learns which queries lead to purchases.

From your perspective, it’s just another way your search becomes more helpful and drives more sales, with no extra work required.