Matrix Group International

Tag: AI

  • Using AI to Power Smarter Membership and Marketing Strategies

    Using AI to Power Smarter Membership and Marketing Strategies

    Let me be blunt: if your AI strategy is focused on writing blog posts faster, generating social captions, or drafting catchier emails, you’re thinking too small.

    Yes, AI can absolutely help with those things. And yes, it can save your team time, but that’s not where the real value is. The real opportunity lies in using AI to rethink how your association operates: how you engage members, how you drive revenue, how you design experiences, and how you make decisions.

    That’s the shift from tactical AI to strategic AI. And for associations, it’s a big one!

    Tactical AI Improves Output. Strategic AI Is Transformational.

    Right now, most organizations are applying AI at the end of the process. They’re using it to write an email, draft a blog post, summarize a report, or clean up meeting notes. There’s nothing wrong with that; those are useful applications, and they can save time.

    But when you use AI at the beginning of the process, you start improving the strategy itself. Instead of asking AI to write a renewal email, you can ask it to help you rethink your renewal strategy. You can explore which members are most at risk, when outreach should happen, which messages are likely to connect, and which channels are most effective. You can look at the full member journey and ask where friction exists and where intervention could make a difference.

    That’s a very different use of AI. At that point, you’re not just improving the content, you’re improving the entire content strategy.

    From Reporting to Intelligence

    Most associations are rich in data, but poor in insight. They have no shortage of reports about renewal rates, meeting registrations, email performance, website traffic, and course attendance. The problem is that most of those reports tell you what already happened and stop there, when what you need to know is what’s likely to happen next. 

    That’s where AI can be especially useful. It can help associations move from reporting to intelligence by identifying patterns, surfacing risk, and helping teams act earlier. For example, AI can support:

    • Renewal risk scoring, so staff can prioritize the members who may need attention now, before it’s too late
    • Engagement trend analysis, so early signs of disengagement don’t go unnoticed
    • Event attendance prediction, so planning decisions are based on likely behavior rather than instinct
    • Signal detection, so staff can spot changes in member behavior before those changes show up in a year-end report

    That’s where the conversation gets more strategic. If you knew three months earlier that a member was at risk, what would you do differently?

    From One-Size-Fits-All to Personalized Experiences

    For years, many associations have delivered broad, generalized experiences because personalization felt too difficult or too expensive. Everyone got the same onboarding. Everyone saw the same website content. Everyone received roughly the same messaging. That’s not really a member experience; that’s just content distribution. 

    AI makes it easier to tailor the experience based on what members care about, how they behave, and where they are in their professional journey. That could mean:

    • Personalized content recommendations on your website
    • New member onboarding journeys based on job role, title, industry experience, and so much more
    • Tailored messaging, based on your generation cohort (i.e., talk to GenZ differently from GenX), interests, and engagement history

    Imagine a member logging in and seeing content that actually reflects what they care about. That’s not a future-state idea. That’s achievable now. 

    From Mass Messaging to Smarter Communication

    Mass emails are now remarkably easy to draft and send out. But just because content is easier to produce with AI, doesn’t mean that you should be messaging more. Quite the opposite, actually. The more messages we send, especially the ones that aren’t highly tailored or personalized, the more ineffective they become. 

    What AI can do, when used well, is help your team communicate more intentionally by improving segmentation, timing, and relevance. AI can help staff:

    • Identify disengaged members and trigger re-engagement
    • Surface topic interest and follow up with relevant content
    • Flag highly engaged members who may be ready for volunteer leadership, committee outreach, or a more personal touch from leadership.

    That’s a much better use of AI than simply flooding your members with more emails! 

    From Staff Tool to Member Value

    Most organizations are still thinking about AI as an internal productivity tool. That’s a good start, but what if AI became part of your member value proposition?

    Here are some of the things Matrix Group clients are working on in this area:

    • An AI-powered knowledge assistant
    • A compliance or standards guide
    • A career pathway tool
    • A skills gap analyzer

    For many organizations, this is the next step. Not just using AI behind the scenes, but building it into the member experience in a way that strengthens your association’s value proposition.

    If time and budget weren’t constraints, what would you build for your members?

    One More Shift: From Publishing Content to Owning Answers

    Associations also need to think about how AI is changing the way people discover information. People are no longer searching and clicking through pages of links to find the answer they’re looking for. They’re asking a question in Google, ChatGPT, Gemini, or even your site search and expecting a direct response in a succinct, complete narrative, not a list of links. 

    That shift has real implications. It means your content can’t just exist. It has to be structured in a way that makes your expertise easy to find, easy to interpret, and easy for answer engines to cite.

    So here’s the question: when someone asks an answer engine about your industry or profession, does your association show up in the answer?

    AI answer engines like Gemini, Claude, and ChatGPT prioritize:

    • Clear questions and answers
    • Structured content
    • Plain language
    • Accessible expertise

    This is where AEO and GEO come into play. Is your content structured to provide the AI answer engines with the answers that people are looking for? What content should be public and what content should be members-only?

    So Where Do You Start?

    This can feel like a lot, because it is.

    Moving from tactical to strategic use of AI isn’t about adding one more tool to your stack. It’s about rethinking how your association works: across membership, marketing, education, research, volunteer management, and so much more.

    The good news? You don’t have to do everything at once. Start with one area:

    • Membership renewals
    • New member onboarding
    • Event engagement
    • Content strategy

    Pick an area where better intelligence, better personalization, or better decision-making could improve results for your organization, then ask a better question. Not “How can we use AI?” but “How could we redesign this process, this experience, or this strategy so it works better for members and for the organization?”

    At Matrix Group, this is exactly the work we’re doing with associations every day. Not just helping teams use AI to move faster—but helping them:

    • Rethink member journeys
    • Identify opportunities for personalization
    • Connect systems to enable smarter experiences
    • Uncover new ways to deliver value and drive revenue

    We know that for associations, the goal isn’t just efficiency. The goal is a stronger, more relevant, more valuable association. And AI, used strategically, can help you get there.

    So I’ll leave you with one final question: 

    Are you using AI to do what you’ve always done, just faster?
    Or are you using it to become something better?

  • You Don’t Need an AI Strategy — You Need a Business Strategy Supported By AI

    You Don’t Need an AI Strategy — You Need a Business Strategy Supported By AI

    Everywhere I turn, someone is talking about their “AI strategy.” But here’s the truth: you don’t need an AI strategy. You need a business strategy, and AI should support it.

    Too many organizations start with technology. They chase tools, trends, and buzzwords before they’ve clearly defined the problems they’re trying to solve. That’s backward.

    Here’s how we believe you should think about AI:

    Start With the Problem, Not the Tool

    Don’t start by asking, “What can AI do for us?” Start by asking, “What problems are we trying to solve?” Every Thursday morning at 9am, there is an open meeting that anyone from the Matrix Group staff can attend. At first, we focused on AI learning, but we have shifted to talking about:

    • Where are the inefficiencies in our operations?
    • What repetitive tasks eat up staff time?
    • Where are members, customers, or employees frustrated by friction in their experience?
    • What tools or processes need re-engineering?

    Then, we solve! 

    I highly recommend holding regular meetings like this, where you discuss pain points, inefficiencies and missed opportunities. Once you’ve identified the pain points, prioritize them. Make a list of the top five challenges you need to address this year. Then, and only then, start exploring how to optimize and automate.

    AI Might Be the Solution—or It Might Not

    AI is powerful, but it’s not magic. Sometimes the solution involves AI. But sometimes the solution is a better database search, a better process for collecting data, better processes, new integrations, or clearer communication.

    Be open and curious about what’s possible with AI, but stay grounded in your goals. The right question isn’t, “How can we use AI?” It’s, “How can we work smarter, faster, and better?”

    And don’t forget to ask your vendors what they’re doing with AI. Many are already building AI into their systems — CRMs, AMSs, CMSs, and marketing tools — so you may already have AI capabilities available to you that solve some of your pain points.

    Successful AI Adoption Is More Than Tools

    Even if AI is part of the solution, success depends on people and process just as much as, if not more than, the technology at play. Successful AI adoption requires:

    • Executive buy-in. Leaders need to be curious about AI, understand what it can do, and use it themselves.
    • Process ownership. Who owns innovation in your organization? Who will manage these projects and ensure they actually move forward?
    • Ongoing support. AI isn’t “set it and forget it.” You’ll need to maintain, refine, and evolve your solutions over time. 

    In my experience, it takes at least six months for a new initiative or process to stick. If you lose focus after just a few months, you’ll be amazed by how quickly your organization drifts back to the old way of doing things. Keep following up, stay curious, and insist on ongoing tweaks and adjustments to the execution plan.

    The Bottom Line

    AI is an incredible tool, but it’s not a strategy. Your business strategy needs to come first.

    When you start with your goals, your pain points, and your priorities, you’ll identify the right opportunities to automate, streamline, and enhance what you already do best.

    And when AI supports that strategy rather than driving it, you’ll see real results.

  • Why Every Association Needs an AI Policy

    Why Every Association Needs an AI Policy

    Last month, Kevin Ordonez and I presented at .orgCommunity’s Solutions Day in Schaumburg, IL. Our session was focused on the AI journeys of associations. We asked attendees—mostly association CEOs, CIOs, and COOs—a series of questions about how their organizations are approaching AI.

    One statistic really stuck out: only 57% of respondents said their organization has an AI policy.

    Only 57%! That means that, for more than half of all associations in the room, it’s the wild west when it comes to staff usage of AI tools.

    And, believe me, your staff are using AI. Whether it’s ChatGPT, Microsoft Copilot, Grammarly, Canva, or one of a hundred other tools, your team is tapping into artificial intelligence to write, summarize, code, design, and more, whether or not you have an AI policy in place.

    So, Why Is an AI Policy Critical?

    1. Your Staff Are Already Using AI

    AI use is already happening in your organization, with or without your knowledge. Without a policy, that usage is likely unmonitored and inconsistent. Worse, it’s happening without any constraints or ethical guardrails.

    2. A Policy Sets Guardrails for Responsible Use

    At Matrix Group, we have a clear rule: confidential data must not be used with AI tools unless explicitly approved. This includes staff, member, and client data.

    An AI policy outlines which tools can be used, how they should be used, and what’s off-limits, especially when it comes to security, confidentiality, and compliance.

    3. It Reinforces Accountability

    AI tools are just that—tools. They can assist, accelerate, and even inspire, but at the end of the day we are still responsible for the final outputs. Whether it’s a blog post, a report, a financial analysis, or even code, the person using the tool must own the final result, and an AI policy can help keep your staff accountable.

    4. It Encourages a Healthy Culture of Innovation

    When staff know that leadership supports smart AI adoption, and has established boundaries for how to use it, they’re more likely to experiment in meaningful, responsible ways. A policy encourages discussion and learning, instead of shadow use of AI.

    What Should Be in a Basic AI Policy?

    An AI policy doesn’t have to be long, or perfect, to be effective. Even having a simple, one-page policy can make a big difference for your association. If you don’t have one, make one FAST that at least states:

    • No confidential data to be used in AI tools, unless specifically authorized.
    • Staff must take responsibility for the accuracy, legality, and appropriateness of all AI-generated content.

    Once you have a basic AI policy approved and in place, you can work on expanding it. Here are a few areas to consider:  

    • Responsible Use: What can AI be used for? What can’t it be used for?
    • Approved Tools: Which AI platforms are sanctioned by your organization, and why?
    • Confidential Data Protocols: How should employees request permission to use AI tools with sensitive data?
    • Storage and Retention: Where will AI-generated outputs be stored? Are records policies for AI work the same as human-generated work? Or are they different?
    • Meeting Use: Is it okay to use AI notetakers in staff or board meetings? What about client meetings?
    • Ethical Standards: What does “ethical AI use” look like in your profession or industry?

    Don’t wait for a crisis or data leak to spark this conversation in your organization.

    Instead, start simple. Invite your team to discuss the tools they’re using, learn from their experiments, and then use that knowledge to build an AI policy that protects your organization and supports innovation.

    Does your organization have an AI policy? If so, what does it cover? If not, what’s holding you back?

  • Can AI Create Your Website?

    Can AI Create Your Website?

    AI tools like Canva and ChatGPT promise fast, DIY website creation, but are they good enough for organizations with complex needs? This post explores what AI can (and can’t) do when it comes to website design, development, and content. From the convenience of AI-generated layouts to the irreplaceable value of human expertise, discover when AI might be “good enough” and when it’s just not the right fit.

    I recently saw an ad about how Canva can create a website with AI minutes. Canva allows customers to select a template, create images, and have AI create the content.

    I am a big Canva fan, so I got curious. Is this really possible? I went to Canva.com and decided to try and create a website for the book I’m writing about associations. Canva has some impressive options, but let me tell you, I still didn’t have a website after 45 minutes. Why? Because the choices were too overwhelming, I couldn’t find something that looked unique enough for my taste and I don’t know the Canva controls enough to create something that matches my personal brand or the Matrix Group brand.

    What about someone who IS really good at Canva? Could they create a website in minutes? Maybe not minutes, but maybe a few hours? Today, the answer is probably yes.

    BUT, will it be any good? 

    Today, the answer might be, it depends. It’s possible that AI can create a website for you or your organization that is good enough. But here are some things to think about:

    AI Makes It Easier for the DIYer To Create a Website

    DIY (do it yourself) tools have always been great options for people and organizations that know exactly what they want. I used blogger.com to create a website for my personal podcast, KDramaChat.com. Is it amazing and unique? No, but it’s good enough. We’ve helped clients select a pre-built theme in WordPress for a conference and with a little setup, they were off to the races!

    But what if you need something more than a simple blog site or one-pager about something you’re fighting in Congress? Or a website that represents your entire organization, its values, its initiatives, and its impact?

    When It Comes to Website Redesigns, the Process Is Often THE Thing

    In my experience, our clients come to us because they have a vision or an inkling of what they want, but they don’t know how to get there.

    Often, a website redesign is a proxy for a conversation about who or what the organization wishes to become. So we use tools like interviews, analytics, mood boards, wireframes and design to help clients explore and ultimately decide what their end goal actually looks like. And many times, the conversations about what the website should look like, what content should get priority, and what the website should look like, have to be moderated by people who know how to achieve agreement between people of differing opinions. (My Project Managers excel at this.)

    Creating a Unique Brand Takes Time and Expertise

    I’m more and more impressed by what AI can do with images, videos and logos these days. BUT, more often than not, what AI creates needs to be massaged to make it better, to give the output authenticity, to make the designs have depth and personality.

    THIS depth and personality comes from skilled designers. At least for now, nothing beats the experience and eye of someone trained in design and branding. My designers absolutely use AI tools but they don’t rely on them exclusively. Sometimes they just need a little inspiration, sometimes AI gives them a base they can tweak into something fabulous, and sometimes they have to just do the work entirely on their own.

    AI Can Certainly Help Build a Website

    My front-end and back-end developers are increasingly using AI code generators to help them build out website functionality. Whether it’s a custom post type, a directory, or an integration with a membership database, the code generators have come a long way. We’ve seen great productivity gains in this area. The catch here is that we’ve had to train the code generators on OUR coding standards and our code repository, AND every developer is still responsible for reviewing their work and having others test it.

    AI-Generated Content Can Be Flowery or Soulless

    We joke at Matrix Group that we can often tell when content is AI-generated. AI loves to embark on things, or delve into things. Yeesh. Who talks or writes like that? I also find that AI content is often full of extraneous adjectives. The content might sound good, but it’s sometimes off brand, or way too flowery for my taste. Even worse, those adjectives can get us in trouble because they just aren’t true.

    Again, don’t get me wrong. I use AI tools for brainstorming and drafting, but what Gemini or chatGPT generates is never good enough, not for a writer like me, and, I suspect, not for my discerning and extremely professional clients. 

    By the way, I tried really hard to get AI to draft this blog post and it just couldn’t do it. I’ve had luck with other topics, but even when I provided detailed prompts and guidance, the end result sounded off. I guess some topics are still too nuanced for AI.

    So, Should AI Create Your Next Website?

    I don’t think so, and I hope not. I think we still need trained and experienced professionals to develop the strategy, create the design, build the site, and write the content that will compel people to read more, join, register, purchase, or otherwise engage. 

    AI is a great companion for creating the designs, programs and content that make up our websites today, but we should still be the leaders of these web development journeys.

  • What is Answer Engine Optimization (AEO)? 

    What is Answer Engine Optimization (AEO)? 

    Summary: Answer Engine Optimization (AEO) is the strategy of structuring your content so it becomes the direct answer to specific questions people ask through Google and voice assistants like Siri or Alexa. It builds on strong SEO practices and helps your content show up when there’s only room for one answer. For associations, AEO is a powerful way to get your expertise in front of the right people—especially as zero-click searches and AI-generated summaries become the norm. This post breaks down what AEO is, how it’s different from SEO, and how to start optimizing your content today.

    How we search, and how we get our answers, has fundamentally changed in the last few years. Heck, even in the last few months, thanks to Google’s AI Overviews. 

    We’ve all been trained to stop typing vague keyword combos and start asking real, specific questions into our favorite search engine. For example, instead of searching for “nursing license CE requirements,” you’re more likely to type (or say): “How many CE credits do you need to renew your nursing license in Virginia?” or “What are the continuing ed requirements for an RN in VA?”

    And what happens when you do that?

    Before late 2024, you’d see a list of links: sponsored ones first, followed by organic results. Now, more often than not, you’re served a single answer right at the top. Sometimes, the answer is just a snippet, sometimes it’s an AI-generated summary, sometimes it’s read out loud by a smart speaker while you’re elbow-deep in dinner prep.

    And most of us? We take the answer and move on. That’s why, by the end of 2024, nearly 60% of searches were zero-click, meaning people got what they needed without ever clicking through. And that’s after AI Overviews had only been fully rolled out for a few months!

    So what can you do to stay visible and relevant in this new, zero-click world? That’s where Answer Engine Optimization (AEO) comes in.

    What is AEO? 

    Answer Engine Optimization, or AEO, is the practice of structuring and optimizing your content so it becomes the answer when someone asks a question in a search engine like Google or to voice assistants like Siri or Alexa.

    Unlike traditional SEO, which aims to get you onto page one of search results, AEO helps you land the single, direct answer that shows up first, whether it’s a featured snippet, an AI Overview, or a voice assistant reading it aloud.

    In short, AEO is what helps you show up as THE answer, or the top answer to a user’s query.

    Does AEO Replace SEO?

    Not at all. Following SEO best practices is still incredibly important; search engines haven’t gone away, the results are just shifting. Search engines still rely on the same solid foundation you’ve (hopefully) been building all along: a fast, well-structured website, relevant backlinks, and high-quality content that’s written by people who know what they’re talking about. Google’s E-E-A-T framework (Experience, Expertise, Authoritativeness, and Trustworthiness) is still the gold standard for what “good” content looks like.

    AEO adds a new layer to SEO. It compliments and enhances the good work you’ve been doing for SEO, with an added focus of helping AI-powered tools pull the right answers from your content. This means writing clearly, anticipating questions, and structuring and organizing content in a way that makes sense to both humans and machines. 

    Think of it this way: SEO gets you invited to the party; AEO hands you the microphone.

    How Do You Optimize Content for Answer Engines?

    Good news: this doesn’t require starting from scratch or mastering some new technical magic. AEO is really about adjusting how you structure and present the content you already have, so it works for real people and the machines scanning for answers. 

    • Start with real questions. Your members aren’t typing in vague phrases. They’re asking complete, specific questions, so your content should reflect that. Use tools like Google Analytics, Search Console, or even the “People Also Ask” section in search results to find the actual queries people are using.
    • Match those queries in your headings. Use those natural-language queries as your H2s and H3s, just like the subheadings in this post. It helps search engines and AI tools understand what you’re answering, and it makes your content easier to scan.
    • Lead with the answer. Give the short, direct response first, ideally at the top of the page and within the first sentence or two under each question. Think of it as the takeaway upfront. Then, once you’ve answered it clearly, go ahead and expand with context and details.
    • Add FAQs to high-impact pages. Pages like membership, certification, and events are where your members have questions and are looking for answers. Adding a short FAQ section at the bottom is a great way to surface that info in an answer-friendly format.
    • Use schema markup. This step may require help from your web team, but it’s worth it. Schema helps search engines understand your content structure – especially FAQs, definitions, and how-to content – and makes it more likely you’ll show up in AI Overviews and voice results.
    • Think about how you write and structure your content. Use natural, conversational language, break up content into short paragraphs, bullet points, or numbered steps where appropriate, and always answer before you elaborate.
    • Surface your authority. Associations have deep, authoritative content that’s often buried in PDFs or behind logins, and AI can’t access that. Creating public-facing landing pages that summarize key insights and link to your gated resources is a great way to give search engines and AI models content they can index and cite without feeding your precious, protected content to the LLMs. 

    Why AEO Matters for Associations Right Now

    Answer Engine Optimization isn’t just a buzzword. It’s a response to how real people are searching today, and how AI is changing the way content gets found, surfaced, and quoted.

    For associations, it’s a huge opportunity. You already have the expertise, the credibility, and the authoritative content. AEO helps you make that knowledge more accessible – not just to search engines, but to the people asking specific, timely questions about your industry. 

    This is your chance to take what you already do well – education, advocacy, standards, guidance – and position your organization as THE authority in search and AI results. 

    Want to learn more about AEO and get your team up to speed? Matrix Group offers an AEO + GEO training tailored specifically for associations. You’ll walk away with a clear understanding of how this shift impacts your content strategy and exactly how to adapt your existing content to help you show up in voice and AI-driven search results.

    Get in touch to learn more and schedule a training! 

  • AI Note-Taking Part 2: Lessons from Five Months of Testing and Refining

    AI Note-Taking Part 2: Lessons from Five Months of Testing and Refining

    After five months of testing AI note-taking tools, Matrix Group discovered that the right tool is only part of the solution. Fathom worked well but didn’t match our workflows, so we built a custom GPT that better fit our needs. Still, adoption lagged until we refined the process, simplified formatting, and gathered ongoing feedback. Real value came when AI was aligned with behavior, not just technology. This blog post explains what we learned and how others can avoid common pitfalls.

    A few months ago, we shared how Matrix Group chose Fathom as our AI-powered note-taking app after testing multiple options. It was an exciting step in our AI journey—one that promised to make note taking more accurate and efficient, ensuring that key takeaways didn’t get lost in the shuffle.

    But as we started using Fathom more regularly, we ran into some challenges. Not because the tool wasn’t working—it was!—but because it wasn’t working for us in the way we needed it to.

    Our AI Notetaker Was Helpful, But Not Quite the Right Fit for Us

    When we first implemented Fathom, we were excited about how well it captured and summarized our meetings. The AI did exactly what it was designed to do—generate summaries, highlight key points, and pull out action items. 

    But as we started using it regularly, we realized that Fathom wasn’t quite working for us. Here’s where things got tricky: 

    • The way Fathom labeled action items didn’t quite align with how our team structures follow-ups. The AI was tagging both “to-dos” and “next actions,” but in a way that didn’t match our workflow, which meant our project managers had to do additional editing to make the notes truly actionable.
    • The formatting of the notes wasn’t translating well into our client extranet. This meant extra steps to clean things up before sharing them out with our clients.
    • We weren’t experiencing the time savings we expected. Instead of eliminating work, we found ourselves reworking AI-generated notes to fit our processes.

    These issues didn’t mean Fathom was a bad tool—just that it wasn’t the perfect fit for how we work. So, we started exploring ways to tailor AI-generated meeting notes more precisely to our needs.

    Could a Custom AI Note-Taker Work Better?

    We asked the big question: What if we wrote a custom GPT for note taking?

    Since we already used custom GPTs for other tasks and workflows, we were confident that a custom GPT could help us process meeting transcripts and generate notes formatted exactly how we wanted. And, it did! 

    We created a custom GPT that would take transcripts from Zoom, Teams and Google Meet and generate meeting notes that:

    • Listed the meeting attendees, grouped by organization
    • Organized the notes by topic; the notes were appropriately detailed (Fathom sometimes summarized discussions too much)
    • Listed the To Do items at the top and bottom of the notes
    • Used limited formatting so the notes could be sent through our company intranet

    This new custom notetaker was amazing. We rolled it out to the project managers and cheered when they said this notetaker was better than Fathom.

    Removing Friction Still Didn’t Solve the Problem

    A few weeks later, we discovered a problem: No one was using our new custom notetaker

    Why? The process required extra steps—logging into Zoom, downloading the transcript, uploading it to our custom GPT, and retrieving the notes. It was an extra layer of work that most people weren’t willing to take on.

    To make adoption easier, we assigned a team member to handle the AI note-taking process for everyone. The idea was simple: instead of expecting project managers to run the process, we’d do it for them and distribute the notes.

    Yet when we followed up, we realized something surprising: PMs still weren’t using the notes.

    Why?

    • The formatting was still too complex for our extranet.
    • The AI was summarizing too aggressively, stripping out details that were important for context.
    • Even with automation, there was no real buy-in.

    How We Finally Got AI Note-Taking Right

    It took five months of testing, tweaking, and getting feedback before we finally got the process right. We adjusted our custom GPT to balance summaries with key details, stripped out unnecessary markup, and made sure the process was as seamless as possible.

    But the biggest lesson? Tools alone don’t change behavior.

    For AI adoption to stick, there needs to be:

    • Ongoing feedback: We had to regularly check in to see what was working and what wasn’t.
    • Follow-through: Just setting up a tool isn’t enough. We had to make sure people were actually using it.
    • Authority to drive change: Someone with authority over the process needs to champion the change.
    • Iteration: Refinement takes time. Expect to make several changes along the way.

    Where We Are Now

    After months of refining, our AI note-taking process finally works the way we need it to. We’re getting the right level of detail, in the right format, and without creating extra work.

    But if there’s one thing we’ve learned, it’s this: AI tools (or any technology for that matter!) are never “set it and forget it.” They require tuning, testing, and continuous feedback to actually deliver value.

    We’d love to hear from you. Have you experimented with AI for note-taking? What worked and what didn’t? Let’s compare notes!

  • How to Customize ChatGPT to Avoid Overused AI Words

    How to Customize ChatGPT to Avoid Overused AI Words

    CEO Joanna Pineda and I have a running joke that whenever we see “delve” and “embark” used in the same paragraph (even better if it’s the same sentence) we wager a lot that AI was involved in the drafting.

    If you’ve been using AI tools like ChatGPT for content creation, you’ve probably noticed this, too. AI definitely favors certain words – tapestry, synergy, foster, beacon, treasure trove. And while there’s nothing wrong with these words, overuse of them (whether AI generated or not) can make people think your content is AI-generated, which can impact credibility.

    So how do you make sure ChatGPT avoids these words, or other words that don’t sound like you, when helping you to draft or edit content? We’ve been experimenting with this a lot at Matrix Group, and one of the most helpful techniques I’ve found is building and refining a personal word exclusion list. Here’s how to do it:

    Step 1: Identify Words You Want to Avoid

    The first step is to figure out which words don’t work for you and make a list of them. This can include words that are common in AI outputs AND words your organization likes to avoid—maybe they’re too corporate, too cliché, or just don’t match your brand’s voice. 

    A few ways to pinpoint words to avoid:

    • Look at past content. Compare AI-generated text to your own writing. Do you naturally avoid words like leverage or paramount? If so, add them to the exclusion list. 
    • Watch for AI patterns. If you keep seeing the same phrases pop up in AI responses, they’re probably overused.
    • Do some research. There are also many blog posts and Reddit threads that list overused AI words, some of which are industry-specific; these blog posts can be very helpful. 
    • Gut check. If a word makes you cringe every time you see it, it’s worth cutting, whether it’s commonly used by AI or not. 

    Way before AI, Matrix Group had a list of words that, while commonly used in our industry, didn’t match our brand voice, so we agreed to strike from our communications and marketing. Identify words like that, too!

    Here is a list of words that I personally exclude because they show up too often in AI-generated content AND are words I wouldn’t commonly use in my own writing:

    Delve, Embark, Synergy, Underscore, Foster, Groundbreaking, Game changer, Endeavor, Enlighten, Esteemed, Shed light, Tapestry, Treasure trove, Testament, Peril, Amplify, Beacon, Convey, Resonate, Interplay, Adhere, Paramount, Furthermore, Profound, Indelible, Bespoke, Cognizant, Encompass, Hitherto, Leverage, Realm, Utilize.

    Keep a running list of your “exclude” words in an easy to access place like a Google doc. 

    Step 2: Guide ChatGPT with Custom Prompts and Settings

    Once you’ve got your list, you have two ways to guide ChatGPT (or any AI tool) to avoid these words:

    1. Customize Prompts as You Go

    You can instruct your AI tool with every prompt:

    “Write a blog post about AI customization. Do not use the following words or derivatives of the words: delve, embark, synergy, utilize, leverage, foster….”.

    This method is great for flexibility, but it requires extra effort every time you prompt the AI.

    2. Set Permanent Exclusions (If Your Tool Allows It)

    Some AI tools allow you to set global preferences, which is a huge help. While ChatGPT doesn’t have a built-in “ban list” for words (yet), there IS a way to customize your account so that it avoids your list of words. Here’s how:

    Navigate to your account, and click on “Customize ChatGPT.”

    Scroll down to “Anything else ChatGPT should know about you?” and enter the following: 

    Avoid the following words and derivatives of these words:
    [Your Word List Goes Here]

    Save, and you’re done! 

    Step 3: Audit and Adjust Your Exclusion List Often

    Once you’ve built your exclusion list, the next step is staying flexible. It’s easy to get carried away and try to cut every word that feels even remotely “AI-generated,” but overcorrecting can be just as limiting as not correcting at all.

    Your list of banned words should be a living document, not a permanent rulebook. Check your list regularly. If your writing starts feeling too stripped down or bland, it might be because your exclusions list is too long. Or, if new patterns start creeping into your AI drafts, consider adding those words or phrases to the list.

    Here’s the balance we’ve found that works best:

    • Keep your global exclusions minimal. Save the big offenders (like delve and embark) for your always-off list.
    • Use prompt-level exclusions for everything else. When you want to avoid specific words in a particular piece of content, include those directions in the prompt instead of your default settings.

    Also keep in mind that even the best AI outputs will never sound perfectly you, because they’re not! Sometimes the best thing to do is simply edit words here and there to make them sound more like you, without having to ban certain words and phrases entirely. ChatGPT should help you draft your content, not write it in its entirety. In my experience, ChatGPT can get me started, but then I edit heavily to put heart back into my writing, and make it sound authentically me or authentically Matrix Group. 

    Remember, AI can be an amazing tool, but it works best when it reflects your brand’s unique voice. By identifying overused words and guiding ChatGPT to avoid them, you’ll get results that sound more natural, more original, and more you.

    Give it a try! Next time you generate content, test out a prompt that includes exclusions, and see how it changes the output.

    What words do you avoid in writing? Let’s compare notes!

  • Unlocking the Power of Your Data: AI-Enabled Reporting in MatrixMaxx 24.2

    Unlocking the Power of Your Data: AI-Enabled Reporting in MatrixMaxx 24.2

    Your association’s CRM holds incredible potential. It’s packed with data—membership renewals, event registrations, content downloads, and more. But let’s face it, traditional reporting tools often struggle to make sense of it all. Finding trends or creating reports that span the full breadth of your data often feels like an impossible task.

    That’s why we’re so excited about the latest release of MatrixMaxx, featuring AI-enabled reporting. This upgrade is more than just a new feature—it’s a new way of seeing your data.

    Imagine being able to see three years of company engagement trends at a glance. Not just transactional data, but a full picture of how organizations are interacting with your association. Or, zooming in to uncover detailed insights about how an individual member is engaging with your events, communications, and services. And when it comes to events—a key driver of both revenue and engagement for many associations—AI takes reporting to the next level. With tools like the Meeting Insight Report, you can now evaluate event performance holistically, identifying key trends and future opportunities with ease.

    These AI-enabled reports connect the dots across your data, giving you insights you’ve never been able to access before. Instead of manually constructing complex queries—or settling for surface-level reports—you can now rely on AI to highlight patterns, opportunities, and challenges automatically.

    Curious to learn more about the MatrixMaxx AMS and how it can help transform your data strategy AND your organization? Schedule a demo today!

  • 5 Critical Facts You Need to Know About AI

    5 Critical Facts You Need to Know About AI

    Artificial Intelligence (AI) is not just a buzzword—it’s a technological revolution transforming how we live, work, and innovate. From automating routine tasks to delivering groundbreaking insights, AI is becoming indispensable in today’s world. 

    But with so much hype and noise, it’s easy to feel lost in the excitement. What’s truly important, and what’s just marketing speak? Whether you’re exploring AI for the first time or looking to expand its use in your organization, understanding the key facts is crucial to making informed decisions.

    Let’s explore five critical insights that will help you harness AI’s potential with clarity and confidence.

    1. There Are No Regulations Around the Term ‘AI’

    One of the most important things to understand about AI is that the term itself is not regulated or validated in any way. Essentially, anyone can slap the label “AI-enabled” onto their product, even if it’s not using any true AI technologies. For example, a simple chatbot that follows pre-programmed scripts (“if A then B…”) may be marketed as AI but without true machine learning or natural language processing capabilities. A more sophisticated AI chatbot might employ generative AI to produce more natural sounding answers, access all the information the model was trained on, and use its prompts and specific documents to generate a response specific to the field chatbot is designed for. 

    It’s critical to ask the right questions when evaluating products or services marketed as AI-powered. What kind of AI are they using? Is it machine learning, natural language processing, or something else? Which core AI technology is it built upon? If you’re investing in AI, you want to make sure you’re getting access to the full power and potential that true AI systems provide.

    2. Generative AI (Like ChatGPT) Is Just One Type of AI

    Generative AI, the type of AI used to create text, images, and even code (such as ChatGPT), is currently getting the lion’s share of the attention. However, it’s important to know that generative AI is just one subset of a much broader AI ecosystem. “AI” is an incredibly broad term, encompassing everything from how Netflix recommends TV shows, to how a Roomba figures out where to vacuum, to the technology that powers self-driving cars. 

    The most common applications of AI are:

    • Machine learning, which helps systems learn from data
    • Natural language processing, which helps machines understand and generate human language
    • Computer vision, which enables machines to interpret and process visual data.

    While generative AI may be the most accessible for everyday use right now, it’s only a chunk of the iceberg. 

    3. There Are Only a Few Big Players in the Generative AI Space

    Although many companies claim to be revolutionizing generative AI, the reality is that just a handful of major players are truly leading the charge. Tech giants like OpenAI, Google DeepMind, and Anthropic are responsible for much of the core AI technology that drives today’s innovations. These companies are at the forefront of AI research and development, creating the foundational tools that countless others build upon. 

    While these big players provide the critical building blocks, a growing number of companies across various industries are using these technologies to create unique and specialized solutions. These smaller players may not be developing the core AI algorithms, but they are applying AI in innovative ways to solve real-world challenges in fields like healthcare, marketing, finance, and more. By customizing and adapting AI to meet specific needs, they bring even more value to the table, pushing AI into new and exciting directions.

    So when you’re evaluating genAI solutions, don’t be surprised or discouraged if the product is built on technology from these big players. In fact, that often means the solution is grounded in cutting-edge, reliable advancements. What matters is how that technology is being adapted and enhanced to deliver value to your organization. With that being said, you should absolutely ask what core AI technology is being used to power their systems. It matters!

    4. It’s All About the Prompt

    It’s been said many times about many things that your outputs are only as good as your inputs. The same is true for generative AI: the prompt, i.e., what you input into the AI system, determines the quality and relevance of the output you get back. This is why “prompt engineering” has become a new skill that’s highly valued in the AI space.

    For example, if you ask a generic question, you’ll likely get a generic answer. However, a well-crafted, detailed prompt can lead to more nuanced, sophisticated, and useful results. Experimenting with different ways to phrase your prompts and providing specific context can help you get the most accurate and helpful responses from generative AI. For a deeper dive into AI prompting, check out our recent blog post on Creating a Custom GPT (the same concepts from the post apply to standard prompting!)

    5. Don’t Trust, and Definitely Verify

    AI is a powerful tool, but even the most advanced systems can make mistakes. Whether it’s generating inaccurate information, misinterpreting data patterns, or offering biased results, AI is not infallible. That’s why verification is key. The best practice isn’t to assume AI’s outputs are always right—it’s to treat them as one step in your decision-making process.

    Generative AI tools like ChatGPT, for instance, can aggregate vast amounts of information, but they sometimes pull together half-truths or inaccuracies from multiple sources. Machine learning systems can misread data trends, and autonomous technologies, such as self-driving cars, have demonstrated their limitations. Whether you’re using AI for content creation, data analysis, or decision-making, always cross-check the results and ensure accuracy before acting upon them.

    Takeaways

    AI has the potential to revolutionize industries and transform how we work, but understanding its strengths, limitations, and how to use it effectively is key. Take the time to ask the right questions, experiment with different AI tools, and always verify your results. The future of AI is bright, and with the right approach, you can harness its power to drive innovation and efficiency in your organization. So dive in, experiment, and see how AI can enhance your workflows!

    To learn more about the ways that Matrix Group is leveraging AI, check out some of our other recent blog posts, and if you are curious about the custom AI solutions we are developing, contact our solutions team at solutions@matrixgroup.net 

  • How Creating a Custom GPT Can Help Automate Tedious Tasks and Save Time 

    How Creating a Custom GPT Can Help Automate Tedious Tasks and Save Time 

    I’m always on the lookout for ways to make life easier for myself and my clients. Recently, as I was using Chat GPT to summarize the transcript of my monthly MatrixMaxx AMS Q&A session, I realized that the process I use every time was the same. I could probably create a custom GPT to both make the process faster and also have the results be more consistent from month to month. And let me tell you—it’s been a game-changer. Hours of time saved, times 12 months a year, means a huge windfall of time for me to do more meaningful product work!

    This awesomeness didn’t happen overnight, though, so let me walk you through the process and share some key insights I picked up along the way.

    What is a Custom GPT?

    Custom GPTs are a no-code feature of ChatGPT, available to all paid accounts of ChatGPT, that lets users customize the chatbot according to the specific way they use it, instead of having to give full instructions everytime they engage in a chat. 

    Creating your own GPT allows you to enter all the instructions once and save it. You also do not need to be as familiar with prompt engineering techniques. You give the instructions in plain text, adding additional needs as you fine-tune the GPT and the builder produces the instruction prompt. It also allows you to enter sample documents to match tone and formatting.

    There are additional benefits of making your own GPT that I didn’t use in this case, but are good to know about, like using the knowledge settings of the GPT Builder. You can upload specialized knowledge like reports or other documentation that the GPT should pull from first, before going to the rest of the Large Language Model (LLM). This works like a personal library that you can query against. You can also add an API connection to an external database for even more knowledge to be included. 

    A note about your data: ChatGPT offers multiple levels of accounts.  Some of these will take any data you enter and add it to its LLM for future learning. The higher levels do not take your data and add it to the LLM, which is important if you are working with proprietary data. 

    At the time of writing this, the Free, and Plus account do add your data to the LLM. The Team, Enterprise, and API accounts do not. I use a Team account and I can share any GPTs I create with the other members of my team.

    Step-by-Step of Creating My Custom GPT

    Let’s walk through the nuts-and-bolts of how I created my GPT.

    • To start, I went to the “My GPTs” section in ChatGPT. I then clicked to “Create a GPT.”
    • The GPT builder will come up on the Create view and look something like this:
    • Start with the basic overview of what you want this GPT to do. You don’t need all the details at this point. You can add details and further instructions as you go. 
    • In my case, I started with:

    “This GPT is a Customer Success Manager specializing in web software, assisting users in summarizing and formatting transcripts from Q&A sessions. Summaries include main topics that were covered along with timestamps that each section stated.”

    • The builder will then ask you to name the GPT.
    • Next, it will suggest an image for your GPT.  You can either give instructions for it to create a different image, or you can upload your own. 
    • It will then ask a series of questions like “what should be emphasized or avoided?” But at any time you can start to give your own instructions. 
    • I copy and pasted previous summaries and told it to use them as examples. That added tone guidance to the GPT instructions. 
    • I even added specific formatting instructions like “include the starting timestamp immediately after the main topic areas” and “make the main topics formatted as <h2> with the details bulleted underneath.”
    • Finally, I gave it the instruction to always correct “matrix max” to “MatrixMaxx” as that is something the transcript always gets wrong. 

    At this point, you can go ahead and start using your custom GPT by engaging with the chat on the right. In my case, all I would need to do is paste the transcript into the chat.  But, if you want to get more granular, you can click on the Configure tab at the top.  For my GPT, it looks like this:

    You can see this is a more direct place to edit your GPT’s instructions. You can also see how it has distilled all the plain language instructions I gave it into one set of GPT instructions.  The instruction for my GPT now says:

    “This GPT is a Customer Success Manager specializing in web software, assisting users in summarizing and formatting transcripts from Q&A sessions. It emphasizes the clarity of the topics covered, ensuring users can easily identify each major topic. Summaries include clear timestamps placed immediately after each topic title, allowing users to navigate to key areas efficiently. The summaries follow the format where each topic title is formatted as an H2 header, and detailed descriptions of key points are provided in the body as bullet points. Timestamps are still placed immediately after each topic title. The GPT focuses on condensing key points, enhancing clarity, and organizing information in an accessible format. The length of detail matches a well-rounded but concise example format, as illustrated by the given session example. The GPT balances brevity and thoroughness, ensuring users receive concise but complete summaries. It provides suggestions on format and structure for better readability, while remaining professional and helpful in tone. When additional details are missing or unclear, it fills in the gaps without overstepping user intent, asking clarifying questions only when necessary. It can handle long transcripts and extract the most valuable insights efficiently. Additionally, when the phrase ‘matrix max’ appears in a summary, the GPT automatically corrects it to ‘MatrixMaxx’ to ensure consistency and accuracy in branding.”

    I can easily fine-tune things from here, or add additional instructions here or through the plain language builder on the create tab. 

    The Result

    My custom GPT exceeded my expectations. Now, not only do I not need to create the same prompt every month, but the results are much more consistent. Giving it the extra formatting instructions also saves time to get the summaries out of ChatGPT and onto our Support Center. 

    This is going to allow our team to amass our own prompt library without manually retyping specific prompts. We can create multiple GPTs that provide different specific outputs based on our prompts. Creating your own GPTs also lifts the burden of prompt engineering by building the prompt for you based on your plain language instructions. 

    And, if you think creating your own GPT is cool, checkout the GPTs available in the store that have been created by others. You can find these under the “Explore GPTs” section if you have a paid ChatGPT account. You will find GPTs by names you recognize, like WIX and Canva, and also by many other users who have found interesting uses for GPTs. 

    If you find a task that you do repeatedly that you think a Large Language Model like ChatGPT could help with, check out making your own GPT.