Parse.ly is a content optimization platform for online publishers. It provides in-depth analytics and helps maximize the performance of the digital content. It features a dashboard geared for editorial and business staff and an API that can be used by a product team to create personalized or contextual experiences on a website.
$499
per month
Q Research Software
Score 10.0 out of 10
N/A
Q Research Software, a division of Displayr, offers a predictive analytics application for marketers, designed to be easier to use by automating correct statistical to use, drag-and-drop interface for building models, and the ability to read many types of files (e.g. SPSS data files) and able to output the desired file type for presentation, with graphics.
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Pricing
Parse.ly
Q Research Software
Editions & Modules
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Offerings
Pricing Offerings
Parse.ly
Q Research Software
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Required
No setup fee
Additional Details
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Community Pulse
Parse.ly
Q Research Software
Features
Parse.ly
Q Research Software
Web Analytics
Comparison of Web Analytics features of Product A and Product B
Parse.ly is a great tool for publishers who want to track engagement and audience behaviour across websites. With Parse.ly, we can easily track metrics like pageviews, time spent on page, and scroll depth to see which content is resonating with our audience and optimize our content strategy accordingly. Our marketers found Parse.ly to be an excellent tool for tracking the effectiveness of our campaigns. We can use Parse.ly to track metrics like referral sources, conversion rates, and engagement by audience segment to see which channels and tactics are driving the most engagement and conversions.
We use Q for quantitative data. If you know what you are doing it can still take a bit of time to manipulate your data into the most suitable format for the software to help you. But it is time well spent because once it's set up, Q makes the analysis a breeze. We use it for producing data tables, word clouds, significance testing, audience segmentation and coding of open-responses.
The pricing model is a little restrictive for smaller teams that only really need one license but have to buy a 2nd to help out modest users/users learning the ropes.
Learning the basics can take quite a bit of time but they offer plenty of free resources that help you through it step-by-step
As an employee, this is difficult for me to comment as I am not directly funding or making these business decisions. However, it is a tool many get on with for surface level data that is useful to editorial teams.
The Parse.ly platform is very user-friendly and easy to use. User management is simple, and reporting setup only takes a few minutes. They provide very helpful documentation for implementing the scripts on your site and have great customer support to help with custom development such as implementing their content recommendation engine.
I rate this question this way solely because I haven't requested any support. I feel where I will eventually get support would be when we take Parse.ly up on some training that is being offered. We are looking to do that at some point after the first of the year and when our schedules support it.
Parse.ly does pretty well compared to Chartbeat, particularly when it comes to historical information and analysis options that are easy for employees to use after some short training. The onboarding for Parse.ly is intuitive, and the scheduled reports take away basically all of the inconvenience associated with regular metrics reviewing. But Chartbeat wins in its social audience tracking because it can source traffic to a specific social post, which can show you exactly how your audience is coming to your content and where you need to put your content to be sure you get that audience.
We still use Excel in order to use Q, but all the analysis happens in Q. No need to learn formulas or reformat spreadsheets. Q does all the heavy lifting.
Sometimes in meetings our editorial director will point out stories that didn't perform well. To us, that means readers don't really care about the topic, so we'll pivot away from writing about that in the future. That might not be "business objectives" though.