ClickLearn vs. GroupHigh

Even though ClickLearn is quite a handy tool, it takes time to create new records, or more like modifying those to be suitable for use. Also, when I have had questions about ClickLearn and considering that the software is for generating for example manuals, I have struggled with finding solutions to cases from the ClickLearn site. For example how to enable/disable Assistant -functionality. Had two private sessions, with two different support persons, getting two different ways to do things. Not good.

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I'd say GroupHigh is well-suited for anyone who is looking for a mass amount of influencers with ranging topics. It's very helpful in finding an abundant amount of influencers with very specific topics. If you're looking for something with very accurate numbers, this probably isn't the best bet as I have found many discrepancies

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• Creating easy-to-follow work instructions.
• Provides different methods of delivery (text, video, try-me).

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• Segments influencers based on their blog topics.
• Allows me to create lists of different influencers. I love using this to help me pitch.
• Helps me find very specific influencers.

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• It would be nice to take a couple of seconds off screen capture

• My biggest problem with GroupHigh is that most times, their numbers are way off for the influencers. Sometimes, it tells me that an influencer has only 200 unique monthly visitors when they really have tens of thousands.
• I'd love if they had email addresses for all influencers.
• The UI can be a bit tricky to navigate at times.

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While Tracx can be useful in finding influencers based off of certain keywords, I find that GroupHigh is more reliable in providing an abundant amount of options for me to choose from. The UI for Tracx is also a bit trickier than GroupHigh so if I had to choose, I'd go with GroupHigh over it

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• Help is received faster.
• New customers created faster - Quoting faster made possible.

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• It's helped us source influencers so I'd say it helps us with KPI (key points of interest)

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info