Local News Audience Assistant

Introducing the CISLM Local News Audience Assistant, our customGPT that compiles case studies, best practices, Q&As, tip sheets, audio and video recordings and more around audience development from journalism support organizations.

There are so many excellent online resources on how journalists can experiment with growing their audiences in new ways, or utilize best practices from other news organizations. But often, finding the exact resource you’re looking for can be challenging.

We started with resources from 2018-onward that fell into four primary categories:

  • How do I grow my social media presence?
  • How do I build or grow my event strategy?
  • How can I reach and build trust with new audiences?
  • How do I grow my newsletter?

For those interested in a full list of resources, you can ask the bot nicely to export a CSV file of industry resources uploaded.

This is a Beta product, and we’re still working on building out our resource database. If you have any questions, feedback or want to chat more, please email CISLM Project Manager Sarah Vassello.

Methodology

Logo for the Local News Audience Assistant, featuring a central magnifying glass focusing on an open book. Surrounding icons represent various media types, including a microphone, camera, paper plane, smartphone, video camera, music note, chat bubbles, and more, arranged in a circular pattern on a light blue background, suggesting a diverse array of news and information sources.

Scope of the Local News Audience Assistant

    • Only using resources published in 2018 – onward
    • We’re not including research/studies in this chatbot
    • We did not include sponsored resources, such as events from conferences on utilizing a specific product or that featured panelists exclusively from one company. We did include sponsored panels that featured a variety of sources (extended outside of participants who sponsored the event) and were topic-based rather than product-based.

How we found resources

  • First: Finding guides, playbooks and resources using ChatGPT and BingAI to help us get a sense of how AI-powered tools work and to see what results easily appear
  • Second: Manually search and scan through each organization under “Industry Support” and “Trade Organization” and “Vendor, Consultants and Platforms” as defined on our journalism support AirTable database
    • We used key terms “audience”, “audience and community engagement,” “audience development”
    • We also manually dug through certain sections of the website. We looked first under any Resources category on an organization’s site, then looked through any Research category. We looked through the News category when most relevant. We prioritized org-unique information, not external info that was linked, but did include some relevant external resources linked when extremely relevant.

More on resources included in the Local News Audience Assistant

  • We focused more on easily implemented resources, such as how-to guides and “replicate our work” pieces rather than theoretical pieces.
  • It was important to us to credit the news organization that often partners with the support organization whenever possible.
  • We only included resources that are published in English, for now.
  • We tried to include only U.S.-based resources, for now.
  • While we had our four guiding questions to help us narrow down resources, our judgment was used to determine if a resource was applicable or not. If you know of a resource your org has published that isn’t included, please email us to chat more.

Local News Audience Assistant Source Tracker

The following organizations are in our database or are slated to be searched, and compiled from our Local News Support database. At this time, we’re compiling resources from “Industry Support,” “Trade Organization” and “Vendor, Consultants and Platforms” categories:

This database was compiled by CISLM Interns Twumasi Duah-Mensah, Shea McIntyre and Serena Sherwood and CISLM Project Manager Sarah Vassello

A special thank you to Center for Cooperative Media’s Joe Amditis for his guidance and his excellent guide, Beginner’s prompt handbook: ChatGPT for local news publishers, and our friends at Blue Sky Innovations, specifically Steven King for letting us experiment with his OpenAI account and Anthony DeHart for speaking with us.