Parse.ly vs. Q Research Software

For people working in online media, or digital content creators, the platform could help them understand their audience and allow them to interact with them in a user-friendly way. Since the digital media industry is booming, Parse.ly can allow the user and the content creators to meet each other's demands and reduce redundancies and bombard the users with unnecessary content.

Incentivized

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.

Incentivized

• Real-time metrics are great and help us decide what content to follow up on.
• Audience segmenting is key, helps us determine where we're strong and where we're not.
• Historical metrics are also helpful in helping us see what readers come back to overtime, which drives decisions about what content to devote more resources to producing.

Incentivized

• Produces really easy to view tables
• Automatically applies significance testing to data, helping the user spot trends
• Create and insert your own variables and filters to help manipulate the data

Incentivized

• Traffic source. I would like to be able to find the exact social media page a view comes from. Now I can only tell which platform.
• I would like to be able to compare traffic more than one year ago. Now I'm limited to one year.
• Some more customization of reports (or maybe more training).

Incentivized

• 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
• Too be honest, I don't have too many complaints

Incentivized

Cost is always a factor when considering any renewal, so we will always see how that compares to other offerings, but we have been pleased with the functionality from Parse.ly. Importantly, it has engaged news teams, and writers can easily assess their own performance--it is not just a management tool. This wider take-up makes it more likely that we would renew.

Incentivized

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.

Incentivized

Seems to be more bugs than I encounter in Google Analytics, but Parse.ly is always very quick to answer my questions or fix something. It seems like most of my issues are due to communications around my requests being outside of the package we pay for with this tool (i.e., only two years of data).

Incentivized

Parse.ly excels in providing detailed insights into how users are interacting with specific pieces of content, allowing us to make data-driven decisions about content strategy and optimization. Its real-time reporting also provides us with immediate feedback on the effectiveness of content changes, which is particularly important for content-heavy sites that need to iterate quickly.

Incentivized

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.

Incentivized

• 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.

Incentivized

• Time saving - not exaggerating when I say we can do at least 10x the amount of analysis than we could without it
• More thorough insights obtained from our data sets
• Makes data engaging to other stakeholders

Incentivized