Algolia offers AI-powered solutions to improve online search and discovery experiences, with tools for business teams and APIs for developers that help to improve user engagement and conversions across websites, apps, and e-commerce platforms.
$0
per month 10k search requests + 100k records
Coveo Relevance Cloud
Score 8.0 out of 10
N/A
Coveo is an enterprise search technology which can index data on disparate cloud systems making it easier to retrieve. It has integrated plug-ins for Salesforce.com, Sitecore CEP, and Microsoft Outlook and SharePoint.
$600
per month
Pricing
Algolia
Coveo Relevance Cloud
Editions & Modules
Build
Free
per month Up to 10,000 search requests + 1 Million records
Grow Plus
Free / Pay as you go
per month 10K searches/month & 100K records included; $1.75 per extra 1K searches, $0.40 per extra 1K records
Grow
Free / Pay as you go
per month 10K search requests & 100K records included; $0.50 per extra 1K searches, $0.40 per extra 1K records
Elevate
custom
per year
Elevate
Custom
per year Custom search requests and records — volume-based discounts available
Base
$600
per month
Pro
$1,320
per month
Offerings
Pricing Offerings
Algolia
Coveo Relevance Cloud
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
Yes
Yes
Entry-level Setup Fee
Optional
Optional
Additional Details
Pay as you go, scale instantly, or upgrade anytime for advanced features and capabilities.
Algolia is both well-suited to replace Shopify's out-of-the-box search and to very large sites with millions of products in their catalog. Algolia provides a specialized solution that benefits from very large R&D budgets and ongoing investment. Algolia offers a more retail- and open-design solution than competitors such as Amazon or Google search, which offer fewer options and fewer features.
Coveo Relevance Cloud is a great solution to implement into Salesforce to provide Knowledge-Centered Support, Enhancements to a Customer Community, to provide sales aids, or to complement your customized app in Salesforce.
Users get instant feedback as they type, even with complex filters like brand, model, price range, and financing eligibility. This speed significantly improves engagement and reduces bounce.
A user searching for “Camry 2020” or even “Camary 20” still sees relevant Toyota Camry listings from 2020. This reduces friction, especially on mobile where spelling errors are common.
Algolia handles multi-faceted filters efficiently. For example, a user can filter by location, transmission type, color, or inspection status without any lag.
We fine-tune the ranking of search results based on what matters to our business—like prioritizing cars with higher margins or better availability in key cities.
We can experiment with different ranking formulas or UI variations to improve KPIs like lead conversion or time-to-first-interaction.
Better integration of features (ex. synonyms feature is great but isn't respected by their re-ranking product)
Tooling to reduce spam search queries being triaged by system/logged to analytics panels
More automated summaries of analytics (ie. recommend synonyms to add, trends noticed in search volume in specific areas of site, easier ways to leverage API vs using website UI)
It would be great if Coveo 6 allowed you to rebuild indexes from a certain subtree instead of needing to rebuild the entire tree to see changes. This functionality was added in Coveo 7 and is very useful.
In Coveo 6, integration with Sitecore is more difficult than one would expect. This integration is much improved in Coveo 7.
I have seen cases where an exception thrown when crawling a specific document will cause the indexing to stop completely. I believe this only happens in implementations using custom faceting but it could be handled more efficiently if the trouble document was skipped and the indexing could continue.
Relevancy ranking editor is good but not as powerful as GSA. GSA offers a self-learning scorer which automatically analyzes user behavior and the specific links that users click on for specific queries to fine tune relevance and scoring.
We've ran into issues on multiple clients with Sitecore items being indexed multiple times in Sitecore 7 and Coveo 7. The fix Coveo suggested was to upgrade our Sitecore version and Coveo but unfortunately this didn't resolve our issue. After months of testing we were finally able to resolve this by implementing our own CoveoItemCrawler to get around the issue (based on https://developers.coveo.com/display/public/SC201404/Items+in+the+Same+Language+Gets+Indexed+Multiple+Times;jsessionid=3C1A2AE33540E0A0B8BB52BA3A64AF70).
Integration with RabbitMQ in Coveo 7 seems error prone. We often see the error "The AMQP operation was interrupted" and on occasion, need to restart the Coveo service to get this operating again. In some extreme cases, we have also had to restart the server because of issues when attempting to restart the Coveo service.
Algolia is a great tool, we didn't have to build a custom search platform (using Elasticsearch for example) for a while. It has great flexibility and the set of libraries and SDKs make using it really easy. However, there are two major blockers for our future: - Their pricing it's still a bit hard to predict (when you are used to other kind of metrics for usage) so I really recommend to take a look at it first. - Integrating it within a CI/CD pipeline is difficult to replicate staging/development environments based on Production.
Algolia is very intuitive to use, especially the Merchandising Studio. The application provides a virtually seamless view of how product will appear on the frontend and making adjustments is fluid and reflects immediately online. Some slow-down occurs when you have a lot of rules enabled or are pinning / boosting a lot of product. But overall it functions very solidly.
Performance is always a major concern when integrating services with our client's websites. Our tests and real-world experience show that Algolia is highly performant. We have more extremely satisfied with the speed of both the search service APIs and the backend administrative and analytic interface.
It’s non existent. No tech support and no customer service… my application was blocked and is currently inactive causing huge business disruption, and I’m still waiting days later for a response to an issue which could be resolved very very quickly if only they would respond. Very poor from a company of that size
Algolia gives way more control for a non-developer than AWS Elasticsearch Service. Previously we'd have to have our developers make adjustments to site search relevancy, typos, prioritizing certain attributes over others, etc. but now the marketing and website team can do that themselves in the Algolia dashboard
Algolia has been a consistent product that works flawless with very few errors or downtime. With the plan options it’s very easy for us to scale especially with this usage pricing. We have 100% gotten our ROI on this product.
Users who had abandoned our product (attributing slow search speeds as the reason) returned to us thanks to Algolia
We used Algolia as our product's backbone to relaunch it, making it the center of all search on our platform which paid off massively.
Considering we relaunched our product, with Aloglia functioning as its engine, we got a lot of press coverage for our highly improved search speeds.
One negative would be how important it is to read the fine print when it comes to the technical documentation. As pricing is done on the basis of records and indexes, it is not made apparent that there is a size limit for your records or how quickly these numbers can increase for any particular use case. Be very wary of these as they can quite easily exceed your allotted budget for the product.
Quick to find things in a massive database when needed.
Results need to be more concise - sometimes we spend more time looking for the right file than if we were to just search amongst our own networks instead.
Coveo is not always the most useful but does its job when general information is needed.
