Crowdbooster (discontinued) vs. Tableau Desktop

Before recommending Crowdbooster, I'd want to know what goals they hope to accomplish with the software. Then I would want them to specifically identify what types of metrics would be most useful to their program. If they specifically need to report out on how many people in a certain location they reached, this isn't the right fit. If they are using other tools, there may be duplication. However, if they are currently using more budget-friendly solutions or just getting started with a new program, Crowdbooster is a perfect fit. It will help you to grow your program and is flexible enough to accommodate your needs.

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).

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• Timed social media posts - Crowdbooster provides the opportunity to schedule social media posts allowing you to work on other important social media tasks.
• Simply beautiful tracking - There are millions of ways to measure social media impact. Crowdbooster offers the most important and relevant measurements in simplified charts..
• Great UI - Crappy UI = crappy experience. Crowdbooster's UI is easy to navigate. It won't take months to learn where all the buttons are.

• 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.

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• The ranked order of twitter followers and the number of "tweet impressions" did not help that much. Those "tweet impressions" were not really an estimate of how many people were actually reading my tweet. It was simply a sum of followers of the person retweeting a tweet and the sum of all followers from a subsequent retweet of the initial retweet. All this told me was the best case scenario I could expect if ALL followers of a person that retweeted saw my tweet. This is not a true measure of "twitter footprint" – since the “signal to noise” ratio in Twitter is very low.
• There was no system in place to track "clicked links" for links embedded in tweets and/or facebook wall posts. Hootsuite did a good job of this – but only for twitter.
• The list of recommended times to tweet were always "on the hour" (i.e. 10 a.m, 1 p.m.). Never were the times ever at "half past the hour" etc. An independent study that I did on my own using Google Analytics (and campaign links using google's URL builder) helped me determine that my optimal "Tweet time" during the week is 3:30 p.m. ET. More importantly, the recommended times seemed to be roughly the same on the weekends - which I find strange given that social media behavior does change on the weekends.
• Occasionally, in my facebook ranked table of "loyal fans", I would see people in there that had not "liked" or "commented" on a post for months at a stretch and the "look back" period of the table was only around 7 days or so. Hence, I occasionally had to question the accuracy of that table.

• Pricing should be more user-friendly and usage-driven
• Making edits to the production reports is fairly tough and has a vast scope of additional capabilities
• Tableau Desktop should be able to differentiate itself from the Tableau server else there is no major meaning of two different products being offered

Simple to use and a great value for what it offers. It has a simple but clean interface and it provides fantastic historical data you can use to measure your efforts online. By using a tool like Crowdbooster, you can see what is working with your audience and what isn't. From there, you can start tweaking your strategies

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.

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I found it fairly intuitive and easy to use. The information is laid out cleanly, and the most important information appears at a glance on the home page. However, I have worked with other users who had a hard time switching between platforms and identifying where other information was buried. It's not always clear that something is a clickable button! The option to export results is also a bit buried, and not integrated with the date range option.

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

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I do not think it is as supported as it once was when it first arrived on the social media scene. It is an older platform whose main functionality may have already ran its course.

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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.

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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

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If you can demo a free trial, that is definitely the best way to see if this will fit your program's specific needs.

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.

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It is a platform that is singularly focused. It does not have a lot of the additions that come stock with other platforms such as robust reporting or deeper insights past schedule times. It is also a stand-alone platform and a lot of its primary functionality can be found in more encompassing platforms.

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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.

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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.

• Increased efficiency. I am able to generate useful snapshot reports in seconds. Particularly useful when you need answers fast (such as on a phone call).
• Peace of mind. I am able to compare the data in Crowdbooster to what is exported from Facebook and Twitter.
• Quicker, simpler evaluation of results. I am able to more easily compare impressions with engagement data to see what is working, and what should change. Particularly useful in day-to-day analysis.

• 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.

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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