Convertro (discontinued) vs. Q Research Software

I am unable to answer this, as they have still not been able to provide data of any value after two years.

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

• Respond to emails

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

• No apparent end-to-end solution for implementation.
• Constant changes to implementation which has resulted in hundreds of hours of reworking the tagging setup.
• No universal tagging method.
• Numerous tags to be implemented based on a variety of data sources.
• After 2 years of working on implementation, data is still not being captured consistently.
• Convertro looks to us for solutions rather than providing any.

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

Visual IQ - much simpler and effective setup.

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

• The negative impact is the hundreds of hours my team has had to spend in facilitating Converto's constant changes.

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