When crafting your query, it is important to carefully consider your desired target audience. You'll want to be sure that you've accurately defined your target audience so that you can confidently draw insights from the data collected during your study. Since it is so important to get your target audience right, we'll be going over in this article how to define your target audience.
Crafting your query in the Audience Criteria section:
When creating your project, you can start building your query by defining your desired target audience in the Audience Criteria section. In this section, you can specify a few key firmographics that we can query on including:
Location
Seniority
Job Title
Company Employee Range
Industry
Company Revenue
Department
Company
Previous Company
Key Terms
You also have the option of excluding based on these attributes. As you complete this section, you'll want to think about the type of information your ideal candidate might include in their LinkedIn profile.
After filling out this section and crafting your audience, you can generate a sample of 10 participants that match your query by clicking on "Preview Audience". From this view, you can see the estimated audience size of your query and review the sample set of potential participants by clicking into their LinkedIn profile pages.
When reviewing the sample set, you'll want to make sure that the query you crafted and the participants returned are representative of your desired target audience. Also, we recommend refining your query whether it's expanding the location or excluding an industry until you are completely satisfied with the generated Sample Audience.
Here are some additional points to keep in mind when defining your audience criteria:
Consider as many job titles as possible that would fit your ideal candidate
Refrain from listing management levels in the job title section
Include root words in the job title section. For example, include data, data science, and data scientist all in the job title section, then select upper management levels if you're looking to target Data Scientist with some seniority and decision-making authority
Query either on Company Size or Company Revenue, not both.
Some common mistakes users make when crafting queries:
1. Broadly defining their audience
In the example above, the job titles are too few and too general. If we were to query based on this broadly defined audience criteria, all higher-level management working within operations would match, which is too broad for most studies.
Recommendations:
Spell Out Key Words: Ensure you use full terms as well as abbreviations. For example, using "operations" and "ops" will better match how people list their job titles on LinkedIn.
Add More Job Titles: Include more specific job titles and focus on key terms that accurately describe your target audience (e.g. operations, analyst, coordinator, management, etc.).
Specify Industries: Narrow down your audience by specifying industries. This ensures you are targeting respondents most likely to qualify for your study.
By refining your criteria, you can achieve more accurate and relevant results for your research.
2. Vaguely defining their audience
Similar to the previous example, the audience criteria here are too broad. If we query based on this vague definition, all upper-level management could match, including those who are not the best fit for your study.
Recommendations:
Avoid Redundancy: Refrain from repeatedly specifying seniority levels in the job title section (i.e. manager, director, etc.)
Add Specific Keywords: Include more root words related to the specific roles you are targeting (e.g. HR Manager, Senior Software Engineer, VP of Sales)
By clearly defining your audience, you can ensure your study targets the most relevant participants.
3. Using an overly niche audience definition:
In this example, the job title is too specific, potentially filtering out participants who meet the criteria for your study.
Recommendations:
Broaden Job Titles: Use root words instead of overly specific job titles to expand the sample pool and reach all possible participants that fit your audience definition.
Example of a Clearly Defined Query:
In this example, we have taken the specific job title from the previous case and broken it down into root words likely to match our target audience. We have also added keywords to further refine our audience definition and prioritize participants proficient in Minitab and Stata.
Key Terms. What are they? How do you determine key terms?
Our search engine does fuzzy 'key term' matching in which it ranks respondents higher on those match keywords. When crafting your query, we typically recommend including between 2 and 5 key terms so that we can best target your desired audience. When selecting key terms to query on, it might be helpful to consider the type of information your target audience might include in their LinkedIn profile. i.e, AWS is an example of a good keyword for a targeting Software Engineer.
For example, let's say you'd like to interview Senior Data Scientists proficient in PowerBI. We'd recommend adding "PowerBI" as a key term so that prospective candidates that may mention 'PowerBI' in their LinkedIn profile will be first to receive an invite to your study. It is important to note that we do not exclude participants that do not mention key terms as they can still be proficient in PowerBI, however, there is just a slightly lower probability.