Factiva vs. Parrot Analytics

Factiva is particularly useful when I work on securities litigations involving shareholder lawsuits -- i.e. shareholders who bought and sold shares during a specified class period when the company was misrepresenting, for example, its financials. Specifically Factiva is quite useful in helping me understand what company events were known by the market and when they were known. Factiva has also been useful in helping me on various research studies. It is less relevant for other types of litigation that I work on (i.e. Patent litigation, etc).

Incentivized

It is well suited for products where there are a lot of users at scale performing and interacting with the platform. Also where businesses need to take informed decisions based on mass users performing actions at scale. Therefore demand analytics tools like Parrot can be a real boon for such businesses. It is less appropriate for those who are not having users at that scale. Scale is very important I believe and analytics can be even more powerful once we have a lot of data on our hands.

Incentivized

• Putting broad swaths of news in one place
• Organizing information
• Constant updates

Incentivized

• In-depth Demand Analytics of core features.
• Proper recommendations of features.
• Popularity tracking of the core data that we have and mapping with users.

Incentivized

• Lengthy setup for searches
• Repeated articles appear frequently
• Unannounced interface changes were unpleasant surprises

Incentivized

• Audience behaviour dataset can be improved.
• Demand tracking for features can have more metrics to get even more granular.

Incentivized

Each of the tools I have described share the same kind of premise: the main thing they do is source and collect media content. Then to varying degrees they run filters against this content and produce a range of data visualisations and ways of slicing the data and content. Factiva's strength lies more in the sourcing of content than in the manipulation of the results (much like the others do with more sophisticated dashboards and visual interpretations). We chose it because of the integrity of its sourcing breadth. It doesn't matter so much about the display of results because the source material you're working with isn't as dynamic as say social media.

Incentivized

• We were able to capture data metrics by almost 25% more as compared to another analytics tool we previously used.
• Recommendations of new data grew by at least 15%.

Incentivized