Introducing new developer-friendly pricing
Hey there, developers! At Algolia, we believe everyone should have the opportunity to bring a best-in-class search experience ...
VP of Product Growth
Hey there, developers! At Algolia, we believe everyone should have the opportunity to bring a best-in-class search experience ...
VP of Product Growth
Eye-catching mannequins. Bright, colorful signage. Soothing interior design. Exquisite product displays. In short, amazing store merchandising. For shoppers in ...
Search and Discovery writer
Ingesting data should be easy, but all too often, it can be anything but. Data can come in many different ...
Staff Product Manager, Data Connectivity
Everyday there are new messages in the market about what technology to buy, how to position your company against the ...
Chief Strategic Business Development Officer
Done any shopping on an ecommerce website lately? If so, you know a smooth online shopper experience is not optional ...
Sr. SEO Web Digital Marketing Manager
It’s hard to imagine having to think about Black Friday less than 4 months out from the previous one ...
Chief Strategic Business Development Officer
What happens if an online shopper arrives on your ecommerce site and: Your navigation provides no obvious or helpful direction ...
Search and Discovery writer
In part 1 of this blog-post series, we looked at app interface design obstacles in the mobile search experience ...
Sr. SEO Web Digital Marketing Manager
In part 1 of this series on mobile UX design, we talked about how designing a successful search user experience ...
Sr. SEO Web Digital Marketing Manager
Welcome to our three-part series on creating winning search UX design for your mobile app! This post identifies developer ...
Sr. SEO Web Digital Marketing Manager
National No Code Day falls on March 11th in the United States to encourage more people to build things online ...
Consulting powerhouse McKinsey is bullish on AI. Their forecasting estimates that AI could add around 16 percent to global GDP ...
Chief Revenue Officer at Algolia
How do you sell a product when your customers can’t assess it in person: pick it up, feel what ...
Search and Discovery writer
It is clear that for online businesses and especially for Marketplaces, content discovery can be especially challenging due to the ...
Chief Product Officer
This 2-part feature dives into the transformational journey made by digital merchandising to drive positive ecommerce experiences. Part 1 ...
Director of Product Marketing, Ecommerce
A social media user is shown snapshots of people he may know based on face-recognition technology and asked if ...
Search and Discovery writer
How’s your company’s organizational knowledge holding up? In other words, if an employee were to leave, would they ...
Search and Discovery writer
Recommendations can make or break an online shopping experience. In a world full of endless choices and infinite scrolling, recommendations ...
Feb 23rd 2023 ai
You think your search engine really is powered by AI? Well maybe it is… or maybe not.
Here’s a dirty industry secret: some companies actually outsource the problem. Behind-the-scenes, people are manually writing rules and adjusting results to make it appear that it’s semantic search. It looks like AI search, they call it AI search, but it’s not really AI under the hood.
Real AI understands natural language and the intent behind queries. It’s like ChatGPT, but it’s trained on your data so it won’t deliver incorrect or misleading results. Plus, it looks like real search — a list of results and filters to help you find what you’re looking for. Under the covers are machine learning algorithms that can automatically unlock performance, improve search results, and significantly reduce the amount of work you need to configure search results. After all, if the search engine understands customer intent out-of-the-box, there’s much less for you to have to set up.
So, how can you know if it’s real semantic search or not? That’s where this guide can help. We’re here to separate the fakers from the makers! You know it’s fake AI search when…
With AI search, the only time you’ll need to add a synonym is for terms that are totally unique to your business. You won’t need to create synonyms for common vocabulary. If you need to add synonyms, that’s because it is still keyword search behind the scenes, not AI. Oh and note that for every synonym you add, there are dozens you won’t know about in the long tail that would automatically just work if you had real semantic search!
Why is it that your semantic search works great for English, but your French, Japanese, and German sites don’t perform as well? Vector search technologies work for any language. In fact, you can use semantic search technology with unstructured data such as images, audio, video, and it works remarkably well. If it’s underperforming in other languages, it might not be real semantic search.
Vector-based search handles common typos out of the box, so if your search engine is still confused that “vaccum” means “vacuum”, it’s likely fake AI.
Are you borrowing a keyword stuffing strategy from SEO circa 1998 to make sure your on-site search works? Then you’re probably not using AI search. Semantic search vectors understand the meanings of words so you don’t have to perform keyword stuffing or other unnatural search engine acts.
Many companies follow the 80/20 Pareto Principle by only optimizing results for top queries (head queries) on their site. Optimizing for the bottom 80% (long tail), lower-frequency searches is too time intensive, right? Well… it wouldn’t be at all time intensive if you had real AI which improves site search performance for all 100% of your long tail content.
Your search engine may hate it when visitors search for “affordable dress shoes” or “splitting headache remedies.” Searches like these confuse simple keyword-based search engines. Real AI based engines automatically understand these queries to return the right values.
The best way to ensure your customers get good search results is to write hundreds of custom corrective, or relevance, rules, right? For example, you might need to add a rule that explains to the search engine that “usb-c” “usbc” and “usb c” are the same things. Or that “dress shirt” means a fancy shirt, not a dress. With real AI search, relevance rules are a thing of the past.
AI is often called a “black box” or “opaque” because the predictive algorithms can be inexplicable. So, if a company can tell you exactly how their AI arrived at a result, it may be a warning flag. AI models are inherently extremely complex and often include millions, or even billions, of data points during inference. Frequently, they are not explainable. If they claim they are explainable, they need to be able to backup that claim by opening the black box and show which model is used, and how results are derived.
With real semantic search, you should be able to search for “a TV that doesn’t suck” or “a tea to help me chill”. In English, both of these terms are common slang and convey a feeling or tone. Keyword-only search engines will fail entirely, but semantic search engines will understand the sentiment used in many common phrases for different languages.
As the Harvard Business Review put it, “Poor data quality is enemy number one to the widespread, profitable use of machine learning.” Just because semantic search is amazingly smart, doesn’t mean it can make sense of a website’s poor structure, messy metadata, or mucky formatting. A real AI search vendor may need to work with you to ensure your site data is optimal for machine learning to do its magic.
Our combo keyword and AI-powered semantic search solution is coming soon. It includes end-to-end AI including natural language processing (NLP) on the front end, AI-powered retrieval, and Dynamic Re-ranking to automatically re-rank results based on your site’s data.
Incredible results, significantly less effort, no smoke and mirrors. Sign up to be notified when it’s available.
Powered by Algolia Recommend