Distance Scores & Conversational Graph

InferenceCloud is built around a core technology called the Conversational Graph

For more information on how the graph works, where the data comes from and how it is analyzed then please see our more detailed technical documentation. Here we just focus on the essentials.

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InferenceCloud analyzes millions of conversations to understand the relationship between different topics, audiences and objectives.

We then measure distances across the graph to understand topic or message relevance.

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Here is what the graph looks like:

Topics that are closer to the audience (more to the left) are more relevant to your audience

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Topics that are closer to the objective (more to the bottom) are more relevant to achieving your objective

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So ideally the topics at the bottom left of the chart are the ones likely to be more sucessful.

Wait there’s more:

You don’t need to know this, but…

Opportunity spaces

In many cases we see areas where one distance score is significantly lower than another. These typically indicate opportunities, for example:

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A topic is very close to the audience, but not typically mentioned in the context of the objective = new opportunity for communicating and differentiating

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A topic is very far from the audience, but close to the objective = an opportunity to better focus the message, or consider how to make the message more relevant for a specific audience

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Need Help? Have a Question?

Have a look through our FAQ section or contact support directly via [email protected]

Understanding Strategy Explorer data

In many cases we see areas where one distance score is significantly lower than another. These typically indicate opportunities, for example: