Low-volume credentialing programs serve a distinct and critical role in the industry. These programs often focus on specialized or emerging fields, providing credentials that address niche needs. However, their smaller candidate pools and limited resources bring unique challenges (e.g., increasing awareness of their programs with constrained budgets) that demand a targeted approach to optimize their use of resources.

While much of the recent focus has been on using generative AI (e.g., ChatGPT, Gemini, Claude) to expedite test development activities such as item generation, generative AI can also be used by low-volume programs to enhance their marketing efforts to increase engagement within an industry and increase adoption of needed credentials within a profession. Although these tools can benefit any credentialing program, they can be especially impactful for low-volume programs, where saving time and money is of the utmost importance.

2 Ways Generative AI Can Help Low-volume Credentialing Programs

1. Conducting Regular Market Research to Stay Connected

A deep understanding of the needs and expectations of the candidates, employers and industry leaders is essential to tailoring communication on the importance of a credential to a profession. Low-volume programs I have worked with know this but struggle to find the resources to properly conduct the research needed to gather the information. This often leads to market research being shoehorned into other unrelated research being conducted for program development (e.g., job task analysis surveys), which can impact on the ability to gather valid data for both purposes by increasing survey length. 

Rather than attempting to combine market research with exam validation research to kill two birds with one stone, generative AI can save time by creating an initial draft of a market research survey as well as focus-group or interview questions. It can also then be used to summarize survey comments and focus group discussions, making it easier to analyze data and uncover actionable insights.

Below is an example of a generative AI prompt using the RACE framework to draft a market research survey. As with any generative AI output, all survey drafts created by generative AI should be rigorously reviewed and refined by humans before being administered.

Example Prompt

• Role — Act as a market research expert with specialized knowledge in professional certifications and credentialing.
• Action — Develop a 20-question market research survey.
• Context —  The goal is to help a credentialing program manager understand how current and prospective certificants perceive the credentialing program and identify improvement areas. The target audience is current and prospective certificants of the credentialing program. The survey should capture insights regarding the credential’s perceived value, motivations or barriers to obtaining/maintaining it, preferred program format, pricing expectations and overall brand reputation. The objective is to create a survey that is both easy to complete and yields actionable insights to refine the program’s offerings and marketing strategy.
• Execute — Structure it in a logical flow: screening/warm-up, core questions on perceptions and program details, and demographic questions. Include a variety of question types (e.g., multiple choice, Likert scale, open-ended). Provide clear, concise question wording and specify instructions or responses.  For lower ratings, please ask for the reason for the low rating. The survey should be professional, concise, and easy to understand.  The tone should be neutral and objective, avoiding any leading or biased language.

Here is the sample output generated by the prompt above. While pricing and demographic questions likely need to be customized for your specific credential, and other questions need to be refined, this draft serves as a strong starting point.

You can further improve upon generative AI outputs by asking follow-up questions. For example, I forgot to ask for descriptive anchors for each point on the rating scale. To get this information, I asked a follow-up question: “For each rating scale in the survey, please suggest descriptive anchors for each point (e.g., 1 = Not at all aligned, 5 = Highly aligned) based on best practices.” A sample response to that follow-up question is included here.

It is important to note that generative AI produces different outputs even when given the same input (i.e., prompt) using the same model (e.g., ChatGPT), a variability known as non-determinism. Therefore, even if you use the exact same prompt as above, you’ll likely get a slightly different survey. Also, different generative AI models (e.g., ChatGPT, Gemini) will produce different outputs due to variations in their training data and other factors. It's important to experiment and — as always — thoroughly review the output for biases and accuracy.

2. Increasing Your Marketing Efforts to Grow Your Program

Creating marketing content can be time-consuming, and yet it’s important for low-volume programs to consistently and effectively market their credentialing programs to communicate their importance and keep stakeholders engaged. Luckily, social media and generative AI make this easier than ever before. First and foremost, credentialing organizations must determine where their candidates spend their time online, so they know where to market to them (e.g., Linkedin, Facebook, Twitter/X).

Generative AI can help you draft social media posts, blogs, ebooks, white papers and email campaigns tailored to specific audience segments. For example, I frequently use generative AI to initially draft social media posts for Linkedin such as this one.

I even used it recently to help create an eBook, "10 Marketing Tips for Certification Programs." While I devoted 8-10 hours to refining the draft, it still took far less time than if I had written the entire eBook from scratch.

In addition, some low-volume programs have benefited from mission-based marketing. This approach involves aligning all marketing and communication efforts with the core mission of the organization. For example, the National Certification Commission for Acupuncture and Oriental Medicine (NCCAOM) successfully used mission-based marketing to support its recertification rates. By emphasizing the societal impact and the advancement of professional practice, NCCAOM encouraged practitioners to maintain their credential and educated the public on the importance of seeking care from certified professionals.

For low-volume programs, a clear, mission-driven message can foster a stronger sense of credential value and broader stakeholder support.

Effectively implementing mission-based marketing requires putting the organization's core purpose and values at the center of its marketing efforts. Generative AI can help in a variety of ways. For instance, it can adapt the same mission-driven message to diverse audience segments (e.g., candidates vs. employers vs. consumers) or platforms (e.g., Linkedin vs. Twitter/X). This saves time and effort while maintaining a clear mission focus in every piece of marketing content.

Below is an example of a prompt for creating Linkedin posts related to mission-based marketing for a fictitious certification:

Example Prompt

• Role: You are an experienced social media copywriter specializing in LinkedIn content that sparks high engagement.
• Action: Craft a compelling LinkedIn post
• Context: The target audience is <INSERT TARGET AUDIENCE e.g., ABC Certified Healthcare Practitioners>, <INSERT PURPOSE OF THE POST e.g., the purpose of the post is to encourage them to maintain their certification by emphasizing public safety, evidence-based practices, professional excellence, and improving patient outcomes>
• Execute: The post should be around 150–200 words. Start with an attention-grabbing hook or statement. Use short paragraphs or bullet points for easy scanning. Include at least one question to spark engagement and encourage comments. Provide at least one actionable tip readers can implement. Tone should be professional yet personable — imagine you’re speaking to colleagues you admire and respect. Invite readers to share their own experiences, insights, or advice in the comments. Include 2–3 relevant, non-generic hashtags (e.g., #ProfessionalDevelopment, #CareerTips)

Tip: Providing example content, if available, can help further define the desired style, tone and context. For instance, adding an example of a witty tweet or a compelling LinkedIn post to your prompt can guide the LLM to create content that more closely matches your vision. The prompt example can easily be customized to create other types of content (articles, blogs, white papers) for other kinds of platforms (Twitter/X, Facebook).