Elasticsearch vs. Kissmetrics

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.

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[Kissmetrics is well suited for the] abandon cart scenario to re-engage users on the purchase journey. Engaging users to personalized content using the visit metrics derived from the data captured at each digital touch points. [Implementing] website campaign and journey orchestration is easy. You get visitor profile to segment upon using different visit metrics and action.

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• 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.

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• The more events you track and properties you send along, the more you can see how specific users use your product/service. The user based timeline gives you a perfect start point to get in touch with users, because you can see where they get stuck.
• Tracking your traffic sources and how they influence conversions is awesome. You can get a perfect view of how much a traffic source contributes to revenue.
• Funnel reports give you more insights into micro and macro conversion steps and give you actionable data to work with.
• Customer support!

• Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
• Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
• Schema changes require complete reindexing of an index

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• Installing.... yes this is also a negative. While you can install and have the program running in minutes, if you use Unbounce, the form tracking process is quite complicated!
• Updates... I feel like the product updates have slowed a lot lately. Thankfully, the product functionality is so amazing that it hasn't impeded the use of it. However, it is still disappointing to see less frequent software updates.
• Occasionally clunky UI... there are a few reports that are really easy to mess up and leave you scratching your head on why it isn't showing you any data.

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We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.

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Price sensitivity and the different choices that now exist in the Analytics industry. I think it makes sense for us sometime this year to rethink our analytics strategy to see how we may leverage the best of GA (which has included lots of new features and updates the past years_, Kiss and other tools as need be

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.

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Right after login, you'll get to a dashboard which shows you a quick view on how your business is doing across the events you are tracking. There is no need to dig deeper than that unless you want to, in which case it's very easy to do so just by clicking on the metric on which you want more information. The interface is very intuitive.

The application was very rarely down; during the period we used the application, I can think of only two or three occasions in which the site was down. Notably, at no time was the the performance of our own site compromised as a result.

Speed improved dramatically as the service matured. Early iterations of the publicly-released application would occasionally provide slow processing of results, but those delays became much rarer occurrences during the last year that we used KISSmetrics. One of the more impressive views (which started out feeling more like a toy) is the live view of visits. Knowing that you could see, in real time, what events a user triggered, was gratifying and instructive.

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.

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Our front-line product support person (Mika) is great. She is responsive and great to work with.

However, the data accuracy issue described earlier is the reason for the low score here. This issue was escalated from front-line to support to level 2 technical support and then it disappeared into a black hole. Escalations, in general, do not go well. We get no response for days, or I have to chase things down. This is not acceptable. Marketing metrics are critically important to me and I need answers quickly. I cannot afford to wait around for days / weeks for a response.

Just to be clear, these comments only apply to escalated support issues.

Again, we were fortunate to work with KISSmetrics as they built their application, but Hiten, their CEO and founder, was incredibly helpful to me personally, and to our metrics-driven business as a whole, as we adopted their tool.

I loved this aspect of the product. It wasn't just that the documentation and online tutorials are great - which they are - the on-boarding process though was really stellar. Once you have set everything up, you get a welcome message followed by a step-by-step guide to get you started that is built right into the product interface. For example, the UI asks you to first do X, and then copy this code snippet and send it to your developer who will know what to do with it. When you come back after the first interaction with the product, it continues the process by explaining right in the UI how to track events etc. This kind of step-by-step approach is incredibly efficient. Although there are various forms of supporting documentation (PDFs videos etc) to support every step, you don't really need them. This approach means that you are up and running very quickly with virtually no training time or documentation consultation. Highly efficient process.

Do not mix data and master roles. Dedicate at least 3 nodes just for Master

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In order to build trackability down to revenue, there was quite a lot of work to integrate Kissmetrics with our software and internal process. We had to build the hooks so that Kissmetrics could call back into our software and billing system, etc.. However, we didn't need additional expertise to do this. Once you understand the API, and you own systems, making it work is not too difficult. We did not require an outside consultant or anything like that

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.

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Kissmetrics is a next-level step up for people who are used to getting their tracking and reporting from Google Analytics or Shopify's CMS. While HubSpot arguably has a better user interface, Kissmetrics certainly has the power and usability necessary to track important conversion data and help you make better marketing decisions.

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• 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.

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• Unfortunately for this client (small business) the cost of Kissmetrics was just too prohibitive. But it's obvious that for a larger company that can afford it, the data would be invaluable to gain more insight in how to gain more active users and orders for a funnel.
• The data provided really increases an understanding of how best to provide the right experience for the users...happy users equals increase in ROI.

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