JMP® is statistical analysis software with capabilities that span from data access to advanced statistical techniques, with click of a button sharing. The software is interactive and visual, and statistically deep enough to allow users to see and explore data.
$1,320
per year per user
Webtrends Analytics
Score3 out of 10
N/A
WebTrends provides an enterprise web analytics platform and, according to Forrester, has a strong focus on support for mobile and social channels and a very open platform. Webtrends competes directly with Adobe Site Catalyst, IBM Coremetrics. and comScore DigitalAnalytix.
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
Scenarios 1. If you want to use web server log files as input to your web analytics, then Webtrends will provides a good product, with great ease of implementation. Don't even think about being cheap on hardware, and make sure Webtrends runs on real servers, not in a VM environment. 2. If you want to use Data Tagging, similar to Google Analytics or Site Catalyst, Webtrends has a powerful product, just be prepared to pay. 3. If you are new to Web Analytics, but it is the strategic direction, start with Webtrends on Premises. Questions to Ask 1. What are you trying to accomplish? 2. Can you place a dollar value on the benefit that you expect/need from Webtrends? 3.Can you live with Webtrends running SaaS?
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.
Control privacy, data sharing and competitive industrial knowledge using Webtrends on premises
Great control over custom reports, custom dimensions and metrics
Flexible tool which allows multiple methods of data capture. To my knowledge it was the first tool with a Tag Builder / Tag Management function built in via a supporting website.
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.)
The big downside, the elephant in the room, is that it does not (as of right now) have on-demand segmenting, drilldowns, etc. You have to think of what you want in advance and create those reports then analyze some data. This is huge. You can, of course, re-analyze old data after creating new reports but you still have to wait. (This deficiency may become obsolete with the release of Webtrends Explore later this month (May 2014).)
It has fewer mature integrations with other products and databases than competitors do, although I'm told it works with SharePoint better than anything else does.
Its attribution modeling capability is behind Google Analytics'. In my humble opinion, this could be changed quickly if Webtrends would make some tweaks to its standard visitor history files (i.e. preserve the order in which past visits were sourced beyond the single most recent one, rather than storing all those past sources as a randomized list).
It doesn't incorporate statistical tests, confidence intervals, or statistical associations. However, this same criticism can be applied to its competitors (other than A/B Testing products). It's a tabulation program, as they all are. In this respect, web analytics tools as a group are relatively primitive. Sorry to bring this up as a criticism of Webtrends but it's my pet peeve about the whole industry and I just have to say it. (p.s. take advantage of the heavy-duty Webtrends Scheduled Export functionality to get really granular data that you can feed to a stats program to get significances.)
Although the documentation, help screens, phone support and the knowledge base have improved tremendously in recent years, there is still a pretty steep learning curve because it is different from the tools that entry-level users may have already been exposed to. This can be a shock and many users are alienated at first because they just don't get some of the fundamentals at first. I'd like to see much better help screens that are thoroughly interlinked with the KB and documentation. Having superb online support would make a world of difference with the adoption of this basically powerful tool.
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.
I would be willing to try Webtrends again AFTER some research from other users. I would need to see that users mention better and faster customer support on questions and issues that arise while using the software. The software is capable of vast and incredible things, but if it isnt properly set up and supported during use, it is just a big hassel and waste of everyones time and money.
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.
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
If I could give it a 0, I would. Not having an intuitive user interface made it impossible to convince non-analytic business users to use the tool on their own. Even as a seasoned analyst, frequent calls were needed to get what should be simple tasks done. Account managers don't understand the tool either, and have to refer you to technical support
The v9 admin interface and v10 reporting interface work as well as expected, but have a tendency to be pokey, especially for bulky reports and whenever you're connected to wifi. I much prefer using the REST API for all reporting for this reason, which simply dumps out the data and doesn't bother with the user interface.
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.
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
I once went on to Twitter to ask for help from my network of analytics people, and Webtrends themselves responded. They have been an excellent partner in making sure that their product is being used to the best of it's ability and I greatly appreciate that. Both Omniture and Google Analytics, do not have that level of support over social media
The in-person training was comprehensive enough to get you started, but I strongly recommend having a more experienced person when beginning with the tool.
Webtrends provides several free webinars over the course of the year, many of which I would expect to pay for. The people providing the webinars seem to have a good feel for real-world application of the product.
Careful planning and patience. Use a non-public test site to fine tune tags and reporting. Despite best laid plans, there will be surprises when you collect the data, run the analysis and begin generating reports using the tool. Perform a tag audit to ensure tags fire as desired.
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.
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
Webtrends has its work cut out for itself considering you have the behemoth Google Analytics and Google Analytics Premium having a strong offering and brand recognition for the price of free. After reviewing the paid service I'd suggest you start off with GA as a cheaper alternative that is just as robust, if not much more flexible in regards to the reporting and goal tracking needs for our company.
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
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).
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
Webtrends has had a positive impact on site visitation because it allowed us to understand the sources by domain for site traffic and find out ways to increase visits from those domains.
Webtrends has also allowed us to understand areas of optimization on the site, which has had a positive impact on the overall user journey on the site, likely leading to longer site duration and engagement.
