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Nearly every website can benefit from a great search experience to improve discoverability of contents and products for users. Yet, most businesses don’t have the expertise or development resources to build an onsite search engine from scratch. Search APIs enable companies of any size to craft a robust search experience without overextending resources.
In this article we’ll walk through some of the main qualities to look for when choosing a Search API.
Search APIs are software components that allow developers to seamlessly introduce search capabilities to websites and applications. They provide backend tools for indexing documents, querying various types of data, managing cluster configurations, viewing search analytics, and more.
Though not all Search APIs offer them, quality libraries, software development kits (SDKs), and documentation can guide developers through search implementation, greatly improving the developer experience.
Search APIs can be leveraged for a wide range of use cases. Imagine, for instance, you’re developing an e-commerce website that has a large catalog of products with different brands, sizes, colors, prices, etc. You’ll need a specialized tool to structure, store, and manage your data and help users quickly find exactly what they need. This is where Search APIs come in. A developer can feed the entire catalog into a Search API and invoke it from the website, in a couple of lines of code.
The benefits don’t stop there, though. Companies that are utilizing off-the-shelf website or e-commerce shop builders can often plugin to these APIs with little to no coding required. For example, Algolia has plugins with Shopify and Magento that can be setup with just a few clicks so even non-technical users can set up a powerful search application.
Search APIs are the best way to minimize time to market while maximizing return on investment. This means you can provide your users with the best possible search experience with the least possible effort. A few additional benefits to using a Search API include:
With a cleanly separated Search API, you have the flexibility of running the software anywhere — inside your product through libraries, in separate microservices, or in a separate cloud. Search-as-a-service companies like Algolia provide hosted solutions so that you can let its team of experts run and manage the service and allow you to really focus on your business rather than maintaining infrastructure.
Developers, business managers, and end users all benefit from the robust features and seamless implementation Search APIs provide.
Here are 7 key elements to look for when choosing a Search API to maximize the benefits and experience for your stakeholders.
For most businesses, downtime in service leads to major losses in both customer experience and revenues. Your service needs to be available when your customers want it. However, scaling a complex distributed system such as a search engine is a hard task that often leads to technical errors that cause request failures.
Therefore, it’s important to understand the levels of reliability that a Search API and its backing systems can provide. Some important factors to look at are request latencies statistics — such as mean, median, and 99th percentile — and service uptime.
For example, a quality service may provide an SLA with uptime of at least “99.999%” (known as “five nines”). This means that the system can lose no more than one request out of 100,000. This should ensure your customers are unlikely to have trouble interacting with the service, and if they do, it should recover quickly.
Speed is a crucial part of rewarding search experiences. The faster and more responsive the search, the better your ability is to hold your users’ attention. Search APIs should reduce latency in the search experience as much as possible.
Humans can perceive latencies as low as 20 milliseconds, and many users will get frustrated if a request takes over a second. Ideally, users should receive results in about 100 milliseconds or less, including both server processing time and network transfer time. There are a number of factors that can influence this — data transfer size, server optimizations, database indexes, and so on. You should evaluate request latency statistics for the Search APIs you’re considering. These can help you understand the reliability of the service, gauge the responsiveness of the system, and predict the impact the end-user experience.
Due to sites like Amazon and Google, users have high expectations for the usability of search. These systems are highly tuned to provide fast and easy results to users with minimal effort. Because of this, all businesses need to be able to provide a comparable level of service and not force users to take any additional steps that could leave them frustrated and risk losing them to a competitor.
Sites need to provide a user experience that adheres to patterns users are accustomed to. Search APIs can help you seamlessly implement UI elements and features, such as autocomplete, federated search, and more, to boost the search experience. Further, user data can be used to personalize these results to further increase the chance that users can quickly find relevant content. All of these points influence how users feel about the level of service and ultimately whether they convert.
Anytime you’re sending data from your business to a third-party, you should be careful that the vendor has safeguards in place to ensure that there are no leaks or misuse. This is important to reduce your personal liability and keep your customers and business safe.
For hosted search services, you can review their terms of service and privacy policies to understand what they’re doing with your data, what the retention periods are, who they’re able to share it with, and so on. These are particularly important if you’re sharing sensitive information such as customer data or personally identifiable information (PII).
From a technology perspective, you can also review their certifications (such as SoC 2 or ISO27k) to see that they’re following best practices for data security, encryption, and other infrastructure-level protections.
Optimizing search is an ongoing and iterative process. Ensuring a high level of relevance is key to engaging and satisfying end-users. Search APIs should come with search analytics capabilities, which are very useful for understanding and monitoring user behavior over time and refining relevance.
With analytics, you could discover users may use language and expressions that you weren’t expecting. Or, you may find that there’s demand for certain types of products or content that you’re not currently offering that you can adjust to meet your customers’ needs. In addition to analyzing specific keywords and queries, it can be useful to monitor aggregate metrics such as click-through rates or occurrences of “No Results” pages. This allows you to tune your search parameters and configurations to best meet the use cases and ensure they’re working well over time.
Search APIs significantly reduce the complexity of building a search application, but developers still need appropriate documentation to guide them through their use. For example, a single endpoint may have dozens of required and optional parameters that can be used to modify the results. The API provider must list what these fields are, what their preconditions and requirements are, and what the expected results will look like. Documentation empowers developers to troubleshoot and guide themselves without having to connect to a product support.
In addition to API documentation, it can be useful to have tutorials and implementation guides. These help both developers and non-technical users to quickly get started using the API and also guide them on how to handle various common use cases to ensure consistency and quality. For most websites, the implementations follow common workflows and therefore a robust set of examples can ensure that developers do so in the best possible way.
Many APIs provide simplicity without visibility. Developers can use the API but cannot see the logic and design that guides search ranking. This effectively makes the Search API a black box, and developers suffer a loss of control. That is, if the results are not desirable, developers don’t know how the system should be used or configured differently to fix the problem.
A white-box approach reveals the logic of how the API to the user, without adding additional complexity in development. For a Search API, this means that developers and business analysts can easily see and modify the ranking and relevance rules so that they can be easily modified to business specifications. This affords an environment where you can A/B test various changes to search configurations and use analytics to determine success.
Search APIs are one of the rare software services that target developers, decision makers, and end users. Developers benefit from a seamless developer experience, allowing them to leverage the Search APIs in the way that best suits their existing platforms. Decision makers can rely on the security and privacy of their data and the general reliability of the service. And end users benefit from a fast, natural, and transparent search experience.
Search, however, is a complex experience to develop and perfect. A solid API with robust developer libraries and SDKs can help to significantly ease the process. Empower your developers and minimize time to market with Algolia’s hosted Search API. It boasts libraries for building production-ready user interfaces in 10 programming languages, complete documentation, and live support.
Learn even more advanced search features to improve the user experience and increase conversions in our eBook “7 ways to get more out of Algolia search.”