Algolia in San Francisco, California offers enterprise search as a service.
$0
per month 10,000 search requests + 1 Million records
Coveo Qubit
Score 7.3 out of 10
Enterprise companies (1,001+ employees)
Qubit, now from Coveo (acquired October 2021) uses visitor history data to understand different user segments and serve personalized messages to segments using JavaScript. It is available as either a managed or self-service model. Data is collected using Qubit's own Universal Variable data model, or by integrating the user's existing model via our API. It combines quantitative data with qualitative visitor feedback to give Qubit users the ability to detect areas for optimization.
Using…
N/A
Pricing
Algolia
Coveo Qubit
Editions & Modules
Build
$0
per month Up to 10,000 search requests + 1 Million records
Grow
$0.50
per month per 1,000 search requests
Algolia Recommend
$0.60
per month per 1,000 Recommend requests
Premium
Custom
per month Customized pricing
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Offerings
Pricing Offerings
Algolia
Coveo Qubit
Free Trial
No
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
Pay as you go, scale instantly, or upgrade anytime for advanced features and capabilities.
Algolia offers a wide range of capabilities that can benefit any business by addressing their specific requirements. Integrating with this platform is seamless, and their extensive knowledgebase and training resources are highly valuable for both developers and UI users. We have already witnessed the advantages of this product and are eagerly anticipating future enhancements as we continue to expand our platform, with Algolia as our primary tool for enhancing our search experience.
Coveo Qubit is a very helpful platform mainly for organizations that need to provide a solid business model before carrying out any implementation or new functionality. In addition, it is a very good tool to generate changes and show different content to different types of clients, with their personalization and segmentation criteria.It is ideal for simultaneous testing and customization, only one of these activities individually is not recommended.
Qubit platform uses solid testing algorithms and delivers reliable reporting and analytics of testing campaigns. The dashboard section is easy to use and provides a good high level overview of the core campaign metric performances.
On-boarding and implementation of Qubit technology was painless and well handed throughout the entire process even with more complicated platforms.
Turn-around time for development and testing of campaigns is extremely fast. This enables the business to have a much higher throughput of tests and allows for quick validation of ideas rather than having to wait for months before a test is ready to go live on production site.
Recent pricing model changes made Algolia considerably more expensive. I understand that companies change their models all the time, but my plan almost doubled in price overnight. They let me keep my legacy plan for as long as I wanted, but I had already outgrown it, so a small increase in demand caused big price spikes. It's still cheap for what it is though.
The documentation is generally good, but sometimes hard to navigate. I was trying to find examples of how to combine geo-queries with normal ones, and I couldn't find an example, but it wasn't actually hard to figure out.
Some of the advanced features can be hard to understand at first. This isn't really a con, as it just means Algolia is loaded with features, but I was a bit overwhelmed the first time I tried to customize an index.
While they do work very closely with us, especially our success manager, more involvement on a technical level or a dedicated engineer, would be a great advantage. We develop a lot of experiences in house and, like all companies that dev in house, we have our own way of working. A dedicated engineer that got to know us better as well and understood how we work could only help. Sometimes, a few errors can get through QA due to this.
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.
Qubit is currently providing resources and support we do not have internally. Our relationship managers are exceptional and I feel well informed and well supported by their team. The tool is nice, but our contacts from the company are the real reason to maintain our relationship. They work hard for clarity and continue to help us push for additional opportunities.
Algolia has a good interface and they have done some improvements. However, some non technical users have a challenging time in the use for the first days of learning. But once the main aspects are learned is a straight forward operation
Very simple user interface, built on top of advanced functionality, makes the platform easy to use. The team at Qubit are also very open to feedback and introduce new and useful features fairly often. On the reporting side, the inbuilt dashboard reports are good for a top-level view of test results, and Qubit have made a lot of their output data available should you wish to run your own analysis
I would say that the Qubit account managers are always available for any request. We have a lot of different promotions that could always do with last minute optimizing or changes and Qubit can be relied on to get this changes up and running in an impressive amount of time, so that we don't need to patch live or wait for the next IT sprint. Invaluable to our business.
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.
Technology is good for A/B testing and personalisation - allowing any team with a dedicated developer to create test relatively easily and to report/analyse them in a fair amount of details. Some advanced features, especially on the set up of test cells, are dearly missing. Unfortunately, new features are often not free of bugs... Also, support is sub-par, which means new features are realised without proper documentation, example or training (but of our Qubit counterparts and internally).
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
Qubit are supportive and flexible in providing support. They are happy working out of usual hours, even on weekends and if I have any doubts about the set up of an experience they’re quick to respond and willing to check my work. On particularly big revenue days they monitor our account and they’re quick to identify and problem solve any issues.
The training was great, but would be great to have a script or PDF with some explanations of the qubit JS layer. Without the script you can just try to learn on your own, so the training is not as powerfull as it could be. On the other hand - would be great to have training related to reading statistics or personalisation.
Implementation couldn't be easier. All we needed to do was insert the tag. (easy) and set up the data layer. (dev required) This was pretty smooth in comparison to some of the other tools we use on our site, and was done in less than a day. Note : Data needs to be collected for a set period of time before you can accurately rely on the data that you are receiving. This is normal though with everyone else that we have used
While AWS's offering is a typically cheaper solution, it requires a lot of work to gain any of the core features of Algolia. The cost of dev time and long-term maintenance would be more than the costs incurred with Algolia, which is why it made the most sense financially. On the engineering side, we could give our stakeholders access to Algolia to adjust the indices themselves, which would allow us to focus on other work.
At the time of taking the product, we found no comparable alternatives. Since then, the product has only grown from strength to strength, so it still does not have any comparable competitors that offer both the technical product and business knowledge that Qubit can. Google appear to offering a competing product which may be one to watch in future, and something for Qubit to keep an eye on
Overall is a scalable tool as the environment and the backend functions are the same and many things are done directly on the tool so without the need of further specific developments. However some things could be improved such as documentation for integration that could help in doing whitelabel solutions
Our requirements change throughout the year like most E Commerce retailers. At Christmas and Peak we're dealing with around ten times the usual traffic on the site. Qubit had no problems with this at all, tests continued to fire, and stats were still reported accurately. I don't think that it is the most server intensive .js anyway, but we have seen no issues at all.
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.
