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Our Editorial Guidelines

Our Editorial Standards

Our goal is to make the software selection process transparent and easy for B2B buyers. Content forms the backbone of that mission. As such, we employ rigorous editorial standards to ensure everything we write is accurate, objective, helpful and insightful.

We use a set of internal quality metrics that measure the accuracy of our information and emphasize sound reporting techniques, such as using credible sources and supporting claims. Each piece of content is subject to multiple rounds of fact checking to further ensure the information is reliable.

Our content team relies heavily on internal research and data, coupled with further external analysis. This approach allows us to compare and recommend products in a fair and unbiased way.

Helping readers and answering their questions is our top priority. Our approach to content can be summed up as, Write for humans, not algorithms.

We aim to provide our readers with unique insights. To that end, we regularly collaborate with internal and external subject matter experts (SMEs), including members of our Thought Leader Program. The expertise and firsthand experience of all our SMEs informs our approach and allows us to cover topics in a credible and authoritative way.

Our writing style and voice follow what we call the 5 C’s: clear, concise, credible, contextual and compelling. Each piece of content is crafted and edited through that lens. Our internal guidelines are also designed to ensure maximum readability.

How We Use AI

Our editorial stance on AI generated content is simple: there s a place for using it, provided we maintain the proper checks and balances.

Whenever AI is part of our content process, we include multiple human touchpoints to ensure the final product is the highest quality. All research and content that involves AI is thoroughly reviewed, fact checked and edited for accuracy and tone.

Below are the main ways we use AI in our content creation lifecycle:

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To assist with research:

We treat AI primarily as a research assistant. Applications range from finding use cases, examples and statistics to synthesizing research, analyzing industry reports and investigating our audience s core needs for each topic.

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To analyze data:

We use AI to summarize qualitative and quantitative data, including but not limited to user reviews of products, publicly available product information and internal data.

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