Birdeye is a reputation management and digital customer experience platform for local brands and multi-location businesses. Birdeye’s AI-powered platform is used by brands to engage with customers, drive loyalty, and excel in local markets.
$299
per month
Elasticsearch
Score 8.7 out of 10
N/A
Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
For businesses that have customers or clients or patients with several different locations, Birdeye is essential to help with the reviews and messages received through Google and other platforms. For businesses with only 1 single location, Birdeye could still be useful but wouldn't be as essential as it would be for other businesses.
Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.
As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
The sentiment feature is just okay. It requires custom adjustments and time to understand where it is working well and where it is not in order to get the most out of it, while other features require very little user input.
Social listening needs work. I often receive notifications for unrelated terms because of their similarity in spelling to my organization's name, so I don't use this feature.
Birdeye could have more built-in features to create digital content from the reviews.
Birdeye could also have additional reputation tools to strengthen GMB listings and to combat negative press. Review listings and rich snippets in search are great, but having a tool that measures and helps to improve overall brand health/search results would be amazing. My CEO isn’t looking at what is going right. He looks at what is going wrong. We may have thousands of positive reviews on Google, but the bad article with false information is still showing up on page one of search results. That makes for an unhappy CEO.
I think it is a good tool overall, there are some hiccups but what program doesn't have them. I think we should be notified of more things, specifically broken integrations. There have been instances where I don't notice for MONTHS a client it's having requests sent out because they are organically still getting reviews.
I think it is very easy to figure out very quickly by just playing around in the dashboard. If you have a question you can reach out to our contacts and they do a very good job of figuring out if or what is the problem and getting back to us fast.
To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
Support is really responsive for the most part. I don't feel like they explain it the best for people who aren't as tech-savvy. I have recently had trouble with a more difficult integration and it is hard to pinpoint who I need to reach out to.
We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.
Our choice of reputation management platform came down to two contenders, Birdeye and Listen360. Ultimately we chose Birdeye because of their ethical review gathering process. Listen360 had review-gating built in as part of their process, which is against Google's terms of service. We wanted to be very careful to gather reviews in an ethical way, and Birdeye was better for our needs.
As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.
We have had great luck with implementing Elasticsearch for our search and analytics use cases.
While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.
