JMP vs. Kissmetrics

It is perfectly suited for statistical analyses, but I would not recommend JMP for users who do not have a statistical background. As previously stated, the learning curve is exceptionally steep, and I think that it would prove to be too steep for those without statistical background/knowledge

[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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• JMP is designed from the ground-up to be a tool for analysts who do not have PhDs in Statistics without in anyway "dumbing down" the level of statistical analysis applied. In fact, JMP operationalizes the most advanced statistical methods. JMP's design is centred on the JMP data table and dialog boxes. It is data focused not jargon-focussed. So, unlike other software where you must choose the correct statistical method (eg. contingency, ANOVA, linear regression, etc.), with JMP you simply assign the columns in a dialog into roles in the analysis and it chooses the correct statistical method. It's a small thing but it reflects the thinking of the developers: analysts know their data and should only have to think about their data. Analyses should flow from there.
• JMP makes most things interactive and visual. This makes analyses dynamic and engaging and obviates the complete dependence on understanding p-values and other statistical concepts(though they are all there) that are often found to be foreign or intimidating.
• One of the best examples of this is JMP's profiler. Rather than looking at static figures in a spreadsheet, or a series of formulas, JMP profiles the formulas interactively. You can monitor the effect of changing factors (Xs) and see how they interact with other factors and the responses. You can also specify desirability (maximize, maximize, match-target) and their relative importances to find factor settings that are optimal. I have spent many lengthy meetings working with the profiler to review design and process options with never a dull moment.
• The design of experiments (DOE) platform is simply outstanding and, in fact, the principal developers of it have won several awards. Over the last 15 years, using methods broadly known as an "exchange algorithm," JMP can create designs that are far more flexible than conventional designs. This means, for example, that you can create a design with just the interactions that are of interest; you can selectively choose those interactions that are not of interest and drop collecting their associated combinations.
• Classical designs are rigid. For example, a Box-Benhken or other response surface design can have only continuous factors. What if you want to investigate these continuous factors along with other categorical factors such as different categorical variables such as materials or different furnace designs and look at the interaction among all factors? This common scenario cannot be handled with conventional designs but are easily accommodated with JMP's Custom DOE platform.
• The whole point of DOE is to be able to look at multiple effects comprehensively but determine each one's influence in near or complete isolation. The custom design platform, because it produces uniques designs, provides the means to evaluate just how isolated the effects are. This can be done before collecting data because this important property of the DOE is a function of the design, not the data. By evaluating these graphical reports of the quality of the design, the analyst can make adjustments, adding or reducing runs, to optimize cost, effort and expected learnings.
• Over the last number of releases of JMP, which appear about every 18 months now, they have skipped the dialog boxes to direct, drag-and-drop analyses for building graphs and tables as well as Statistical Process Control Charts. Interactivity such as this allows analysts to "be in the moment." As with all aspects of JMP, they are thinking of their subject matter without the cumbersomeness associated with having to think about statistical methods. It's rather like a CEO thinking about growing the business without having to think about every nuance and intricacy of accounting. The statistical thinking is burned into the design of JMP.
• Without data analysis is not possible. Getting data into a situation where it can be analyzed can be a major hassle. JMP can pull data from a variety of sources including Excel spreadsheets, CSV, direct data feeds and databases via ODBC. Once the data is in JMP it has all the expected data manipulation capabilities to form it for analysis.
• Back in 2000 JMP added a scripting language (JMP Scripting Language or JSL for short) to JMP. With JSL you can automate routine analyses without any coding, you can add specific analyses that JMP does not do out of the box and you can create entire analytical systems and workflows. We have done all three. For example, one consumer products company we are working with now has a need for a variant of a popular non-parametric analysis that they have employed for years. This method will be found in one of the menus and appear as if it were part of JMP to begin with. As for large systems, we have written some that are tens of thousands of lines that take the form of virtual labs and process control systems among others.
• JSL applications can be bundled and distributed as JMP Add-ins which make it really easy for users to add to their JMP installation. All they need to do is double-click on the add-in file and it's installed. Pharmaceutical companies and others who are regulated or simply want to control the JMP environment can lock-down JMP's installation and prevent users from adding or changing functionality. Here, add-ins can be distributed from a central location that is authorized and protected to users world-wide.
• JMP's technical support is second to none. They take questions by phone and email. I usually send email knowing that I'll get an informed response within 24 hours and if they cannot resolve a problem they proactively keep you informed about what is being done to resolve the issue or answer your question.

• 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!

• In general JMP is much better fit for a general "data mining" type application. If you want a specific statistics based toolbox, (meaning you just want to run some predetermined test, like testing for a different proportion) then JMP works, but is not the best. JMP is much more suited to taking a data set and starting from "square 1" and exploring it through a range of analytics.
• The CPK (process capability) module output is shockingly poor in JMP. This sticks out because, while as a rule everything in JMP is very visual and presentable, the CPK graph is a single-line-on-grey-background drawing. It is not intuitive, and really doesn't tell the story. (This is in contrast with a capability graph in Minitab, which is intuitive and tells a story right off.) This is also the case with the "guage study" output, used for mulivary analysis in a Six Sigma project. It is not intuitive and you need to do a lot of tweaking to make the graph tell you the story right off. I have given this feedback to JMP, and it is possible that it will be addressed in future versions.
• I've never heard of JMP allowing floating licenses in a company. This will ALWAYS be a huge sticking point for small to middle size companies, that don't have teams people dedicated to analytics all day. If every person that would do problem solving needs his/her own seat, the cost can be prohibitive. (It gets cheaper by the seat as you add licenses, but for a small company that might get no more than 5 users, it is still a hard sell.)

• 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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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

JMP has been good at releasing updates and adding new features and their support is good. Analytics is quick and you don't need scripting/programming experience. It has been used organization wide, and works well in that respect. Open source means that there are concerns regarding timely support. Cheap licensing and easy to maintain.

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

The GUI interface makes it easier to generate plots and find statistics without having to write code. The JSL scripting is a bit of a steep learning curve but does give you more ability to customize your analysis. Overall, I would recommend JMP as a good product for overall usability.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

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.

Support is great and give ease of contact, rapid response, and willingness to 'stick to the task' until resolution or acknowledgement that the problem would have to be resolved in a future build. Basically, one gets the very real sense that another human being is sensitive to your problems - great or small.

Incentivized

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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 have not used your online training. I use JMP manuals and SAS direct help.

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

MS Excel with AnalysisToolPak provides a home-grown solution, but requires a high degree of upkeep and is difficult to hand off. Minitab is the closes competitor, but JMP is better suited to the production environment, roughly equivalent in price, and has superior support.

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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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Independently Invited by TrustRadius

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• ROI: Even if the cost can be high, the insights you get out of the tool would definitely be much more valuable than the actual cost of the software. In my case, most of the results of your analysis were shown to the client, who was blown away, making the money spent well worth for us.
• Potential negative: If you are not sure your team will use it, there's a chance you will just waste money. Sometimes the IT department (usually) tries to deploy a better tool for the entire organization but they keep using the old tool they are used too (most likely MS Excel).

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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.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info