Bytesview made it easier for us to bring our customers to the forefront by introducing new customer-focused services based on their feedback.
The team is extremely friendly and helped us find innovative solutions to our problem
I've been using Bytesview for a few weeks now and I really like it! It is straightforward and easy to analyze the feedback data collected and gain a better understanding of our customer base.
The tool's data processing was simple, and the results were accurate.
BytesView's in-depth data analysis enabled me to extract personalized insights for my research project. They collected text data from various websites, translated user sentiment, and extracted various keywords for me, which was incredibly helpful during my research.
Moreover, their team was extremely helpful to me throughout the process.
Based on our record, Parse.ly Analytics should be more popular than BytesView. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
It is also not a task that a team of analysts, no matter how large or dedicated, could reasonably be expected to perform, at least not without outside assistance. Even for organizations that are in the business of selling competitive intelligence platforms (many of which are Bytesview customers), this is not a viable option. Source: about 2 years ago
News monitoring services, powered by a sentiment analyzer, and News API are more necessary than ever when every action of a company, its employees, brand ambassadors, or even the organizations with which it is associated is subject to scrutiny, which in turn undermines the financial stability of the company. Source: over 2 years ago
I've also seen parse.ly pop up a bit, I might try it to see if it's any decent. Source: over 1 year ago
Parse.ly | Python Data Engineers (NA) & Machine Learning Engineers (EU) | Remote | Full-Time | https://parse.ly Are you a Python programmer based in North or South America, interested in large-scale data processing (terabytes per month, petabytes in our archive), and making use of massively-parallel computing architectures, such as those behind Spark and Dask? Or, are you a Machine Learning Engineer in Western or... - Source: Hacker News / almost 3 years ago
Would be really useful (not to mention polite) if sources were cited when you do this. For example, I think the early points are from the parse.ly report. People might want to click through for context if you let them. Source: about 3 years ago
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