Building good and long-lasting personas is complex and requires a little bit of finesse to get right. It is easy to forget that your audience may actually be a small niche and thereby too specific. Here are the most common mistakes according to our users: 

Using too many Filters

A good persona is often simple and shouldn't be overly specific. There are times when you want to be specific, for instance when trying to source data for a manual outreach campaign, but in  most of the cases you will simply exclude the majority of users that you could target, if you too many filters.

How to avoid:

One-by-one remove filters that are of lower priority or that are too restrictive, such as only targeting a single industry or a very small company size range. Often several similar industries fall into the same category. 

Not Keeping an Eye on the Persona Size

The personas app will constantly update the number of net new contacts and companies available to you. This will guide you whether you have already been too specific or broad.

How to avoid:

Keep an eye on the counts, and adjust accordingly.

Using Extremely Restrictive Filters

The personas app explicitly warns you of filters that are very restrictive, such as company revenue which is only available for publicly listed companies (anything else would be a guess).

How to avoid:

Watch out for the in-app warnings of highly restrictive filters - denoted by red info icons. Hover over the icon for suggestions. If there are alternatives, we often will guide you to them.

Excluding Overly Broad Keywords or Titles

Excluding simple titles or company keywords such as media may have more of a negative effect than you think. Often these exclusions will be single words or commonly used terms that apply to many companies or contacts.

How to avoid:

Be more specific about what you actually want to exclude. Include at least two words in your exclusions and make sure they aren't commonly used by companies you do want to target.

Using your Own Titles

Using your own titles can cause troubles unless you have an extensive list of titles that can be targeted, including all minor variations. 

How to avoid:

Ideally use the pre-defined departments. If those don't work, use the custom titles & seniorities and make sure you define them broadly. Typically manually selected titles should have at least half a dozen or more titles. To find alternative titles that fit that category, either check out the preview tab to see what other title keywords may fit your need or simply browse Linkedin for appropriate candidates to see what exact titles are commonly used.

Adding All Titles & Departments Into One Persona

A single persona should really only target a single department and/or similar seniorities. If you throw them all into a single persona, by definition they will all have different pain points and ways to address them. Executives by definition will have different pain points and language than staff-level employees. 

How to avoid:

Clone the persona and split them either by seniority or by department, or both. That way you can test and see what works, as well as tailor a specific message to them.

Targeting Very Few or Small Cities

Only going after very few or small metro regions is likely going to dramatically reduce the size of your audience, as one would expect. Unless these are really big metro areas, you can expect the count to be significantly smaller due to just that. 

How to avoid:

Don't be specific to a single metro area and instead try to target entire states. If you have to be location-specific add all variants or cities in those metro regions, for instance in addition to "San Francisco Bay Area" you may want to add San Jose and Oakland as locations as well.

The persona is very small but I still don't know why?

If you have built a persona with very few contacts and don't know what the most restrictive filters are, and/or the above approaches haven't helped or you need to identify what causes it, there's an easy solution.

How to avoid:

Clone the persona and simply remove what may be the most restrictive filters one-by-one. Wait for the count to be updated, and see how much it has changed. Continue until you've found the main culprits.

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