Fullstory’s behavioral data platform helps technology leaders make better, more informed decisions by injecting digital behavioral data into their analytics stack. The technology's behavioral data transforms digital visit into actionable insights.
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Tableau Desktop
Score 8.3 out of 10
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Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
I chose Heap and Tableau as two potential competitors because these provide a similar type of insight (how are customers experiencing your app) but from a different angle. In general I find the large scale, less personal data from these type of analytics vendors to be more …
It was extremely useful in identifying places in our product where things weren't functioning, or where it looked like action was available to the end user but in reality, it was not and therefore caused lots of confusion. It doesn't help as much in other scenarios to see what catches a user's Eye or where they go if they leave our application as well as an actual in-person interview would help with eye-tracking software.
The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).
An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.
The ramp-up time to learn the entire product can take a little while. There are just so many absolutely wonderful tools and different ways to look at the same type of information that it can take a new user a few weeks to understand and then more time to master. However, FullStory has a ton of training resources to help with that! A lot of my own teammates have taught themselves FullStory through those training resources.
The UX of the product is totally wonderful, but there are tiny things that make getting to certain parts of the product slightly more challenging (like clicking into a modal in a modal). Sometimes buttons or links are placed out of my field of view, but those are minor things I notice because I work in UX.
It's been a phenomenal tool for us; every department that uses it has found something new and unexpected that it can do that they're really excited about. Even if we *only* used it for bug triage, it would be worth our time and money. The fact that we can use it for so many other things as well--gauging how customers interact and use our site, identifying UI problems, etc.--is above and beyond
Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
They have been overall pretty responsive and proactive. The tool is pretty straightforward to use. Most of the questions we have had to work with them on our how to use new features or adjust our integration to ensure we are gathering all the data from all of our tools.
Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems
To successfully implement FullStory, it is important to plan your implementation carefully by defining your goals and user segments. You should also use tags and filters to analyze your user data, train your team to use FullStory effectively, and use FullStory in conjunction with other analytics tools to get a more complete picture of your user's behavior. By following these tips, you can gain valuable insights into your users' behavior and experiences, and use this information to improve your website or application.
Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.
Smartlook is software that records users on a website and mobile app. Finding useful information within thousands of recordings is made quick and easy with features that help you accomplish this. I have chosen FullStory because it is easier to use and has more advanced features compared to Smartlook.
I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.
Tableau was acquired years ago, and has provided good value with the content created.
Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.
