Situational Factors

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Situational Factors are also known as Complexity Factors. The purpose behind them is to capture more precise information about what kinds of external forces might have contributed to a specific respondent answer a questions, or group of questions, in a specific way. This is powerful information when trying to articulate the characteristics of a group belonging to a needs-based segment. Without them, it becomes difficult to create a persona that your marketing team can locate.

Using AI to Discover Complexity Factors 💰

Prompt

System

Set the temperature to {{temp}}.

Act as a(n) {{end user}} who is {{job}} {{context}}. Disregard context if it is not supplied.

Goal

List {{n}} situations a(n) {{end user}} could find themself in that would make {{job}} more challenging? Use the perfect experience as a baseline.

The situation will be rated by survey respondents on a scale of 1 through 5, where 1 will be the worst case and 5 being the best case.

Example

The following is an example:

| Situations/Complexities | 1 | 2 | 3 | 4 | 5 |

| --- | --- | --- | --- | --- | --- |

| Limited budget - Having a restricted budget for hiring market research firms or purchasing data can limit the depth and breadth of research conducted. | None | | | | Extensive |

In the example above, “Limited Budget” should be “Budget level for the research.” Only rating level 1 and 5 require a value. In this case, 1 is “None” and the other extreme is “Extensive.”

Therefore, the outputted result should be:

| Situations/Complexities | 1 | 2 | 3 | 4 | 5 |

| --- | --- | --- | --- | --- | --- |

Each situation could need different worst case and best case language. You will need to think that through carefully.

Output the table as a markdown code block so it's easy to copy.

Variables

End user:

Job:

Context:

n: 20

temp: 0.1

Using AI to Discover Complexity Factors 💰