Kissmetrics vs. MongoDB

[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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If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.

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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!

• Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
• You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
• Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.

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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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• An aggregate pipeline can be a bit overwhelming as a newcomer.
• There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
• Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.

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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

I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.

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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.

NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.

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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.

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.

Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.

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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.

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

While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.

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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 [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.

• 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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• Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
• You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB