TensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.
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Woopra
Score3 out of 10
Enterprise companies (1,001+ employees)
Woopra provides real-time customer analytics. It begins by tracking users across digital touch points (website, mobile app, help desk, marketing automation, etc.) and building a comprehensive behavioral profile for each user. These Customer Profiles are Woopra's building blocks, which are used to generate custom analytics reports, funnel analytics, retention analytics, and more.
TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
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
My rating of Woopra is the absolute best possible. I would recommend them to anyone looking for an analytics website that prefers a visual interface and a beautiful design. I have not encountered any problems using their app -- ZERO! Their integration with other marketing software, such as MailChimp, helps our company zero in on our marketing campaigns and gives us the information we need to make better choices. I LOVE Woopra and think they are the best out there! I have used other websites and there is no comparison!
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
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
Woopra tracks *individual users and customer accounts*. It cannot be understated how important this is. Google Analytics and other low cost solutions only sample users and provide aggregate data. For enterprise sales, this is critical. Likewise, for product managers trying to segment product usage by types of accounts, this is incredibly useful.
Woopra updates user analytics in real time. This is critical in a sales context as you want to be able to follow up quickly on opportunities. Likewise, it is useful for customer success as they can see usage in real time for an individual they are supporting.
Woopra has the most turnkey integrations of any web analytics solution on the market. By far the most useful are Marketo, SalesForce, and Slack, but there are several more we didn't tap into. While any solution worth its salt has an API, Woopra's integrations usually require a login and/or API key, and you are good to go. Here is the current list: https://www.woopra.com/appconnect/.
Woopra enables B2B product managers to track product and feature usage by revenue, not just clicks. Again, in a B2B context, this is critical, as there are high-value users and low-value users. Knowing the difference is critical.
Woopra's implementation is super simple. We were able to set it up with a couple of hours of one frontend developer and some help from our product intern.
Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
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
We just really like the tool. There are lots of us using it internally... from Product, to marketing, to customer service, to optimization team, to traffic acquisition, to Executives. Really helps us answer questions about how well things are going, and what is not going well.
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
The UI and reports are great overall. Creating reports just requires a few too many screens and clicks. Also dashboard tiles can't be resized. Both of these are easy items that are being addressed
Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
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
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
Compared to other products, the support was a small effort. We only had part time contributions from a product management intern and front end developer.
Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
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
Woopra is much easier to setup and use than Google Analytics. I've spent hours trying to create custom reports in Google Analytics. Woopra does not take this much time to get solid reporting for our site. If you need something that tracks marketing efforts then Google Analytics will likely be a better fit.
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
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
Really helped us begin to segment our users based on their engagement and retention.
Helped increase retention by about 1.5% after about 5 months of implementation (don't shoot the messenger if your team can't implement that quickly).
I felt like it had great potential to create a pipeline between sales and the CSM, but I had trouble getting the sales team to implement it properly as they had their noses deep in calls and emails (they struggle entering notes in SalesForces as well, so it's more a company specific problem).
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
