How to test new tools without risking client trust

Using a “Test” campaign on LinkedIn Want to try different tactics without interrupting your funnel? Create a campaign to experiment with! Many companies know their ICP, but the current needs market doesn’t always align with your targeting. Ever wonder if targeting end users might be an effective tactic instead of just Decision Makers? Have a high-performing ad that you want to A/B test but know it wouldn’t be a clean test to add a new variation and run it against the ad that’s already been running for a while? Want to try getting creative with Skills & Interests but keep your main campaigns focused on your ICP build? That’s where a test campaign comes in. I set up this campaign initially to try different audiences and gauge their interest outside of my normal structure. Initially, I had asked ChatGPT what the ideal target audience was for one of my client’s offer. It deviated from their stated ICP, so I asked if I could test it, and they gave me the thumbs up. I ran it for a month, started honing in on the top-performing demographics of the test group, and saw an increase in results! We would also swap out ABM lists in the main campaigns, but instead of just dropping the older lists, I threw them in the test campaign to see if I could milk some additional results... And it did!! Conversions increased, and I even got one in Cold. One of our team members also suggested running A/B tests in a separate campaign. You have a high-performing ad, but if you just create a variation and run it, it’s starting at a different point and doesn’t have the same social engagement, so it’s not an apples-to-apples comparison. If you instead try different variations of that ad from scratch in your ‘Test’ campaign, you can get a cleaner comparison of how they perform, and based on the results, replace your previous ad with the top performer (that way, it keeps the social engagement and trust it’s built). It’s difficult to run these tests in your main campaigns because building a funnel and establishing trust takes time (and you don't want to disrupt that to test something). So, using a ‘Test’ campaign (even with a minimal budget) can help you gather data to improve your overall performance! Have any other methods of testing that you’ve found successful? Let me know in the comments!

Every month, I save my clients $1000s on AI tools they don’t need. Here's the brutal truth about AI spending: 90% of companies waste money on tools they'll never use effectively. Why? They skip the testing phase. Here's my simple 2-week framework to avoid this: Week 1: • Pick one small project • Document everything • Watch the actual results Week 2: • Look at the data • Run the numbers • Make decisions based on facts Not gut feelings. Not sales pitches. Just data. Last month, this framework helped a client realize they needed a $500 tool. Not the $50k solution they almost bought. Simple > Shiny.

Completely convinced the best teams right now aren’t waiting for perfect conditions. The world is moving waaay too fast. They're testing, refining, killing and scaling faster than anyone else using tools/tech that others are too scared/slow to try. We're continuously playing with tools at StealthX and iterating on our process to move faster and avoid analysis paralysis. Here's our current approach to testing tools we come across every week. Curious how others are doing this? I'd love to compare notes 😊 1. Find tools worth testing If someone finds an AI tool that could save time or improve efficiency, they drop a quick message in our chat. If it makes sense, I approve it instantly (no red tape, no waiting). 2. Get the tool, track it The person testing signs up and logs details in our "Radar", which includes cost, intended use, subscription renewal date, and who’s testing it. 3. Put it to work immediately No sandbox testing. We throw the tool into an actual project and see what happens. If it works well, we expand testing to others. If it doesn’t, we cut it fast. 4. Review, kill, or scale Every Friday we have a team innovation jam session where we review new tools tested that week, decide if we keep/kill them, and document anything we've learned for future reference. If a tool isn’t valuable, it’s canceled on the spot to avoid stacking unnecessary costs. 5. Keep budget in check We cap our monthly AI experimentation budget to keep things lean. If a tool proves its value, it might move into our long-term stack.. but only after discussion. This prevents “tool creep” and ensures we’re always optimizing for ROI. Why I think this works: 1. No waiting months to decide if a tool is worth using. 2. We only pay for what actually works. If it doesn’t add value, it’s gone. 3. We document everything. We’re not just testing, we’re learning and refining every week. Onward & upward! 🤘 — If you liked this post, check out my weekly newsletter https://lnkd.in/edqxnPAY

Your IT department should introduce the new tech, right? As a continuous improvement project manager, I like to keep my knowledge of tech up to date. Giving requirements to IT for them to decide the technology works to some extent, but knowledge can help shape requirements. When you know what is possible, you can find new ideas to make things better. For example, instead of asking for a KPI dashboard, I may choose to ask for a chatbot on my cell phone. When traveling to customers or suppliers - it may be easier to ask for the information vs. seeking it in a dashboard. Staying up to date doesn't mean going rogue. Here are some things to keep in mind... Understand IT Compliance and Security Protocols: before installing the latest and greatest, make sure the software meets the organization's IT compliance and security standards. Request a Sandbox Environment for Testing: To safely explore and test new technologies, ask your IT department for a sandbox environment. This isolated testing space allows you to play with new tools and software with minimal risk. Foster Collaborative Exploration with IT Teams: Engage in regular dialogues with IT experts to gain insights into the latest technological advancements, their potential applications in your projects, and the best practices for implementation. What do you think? should project managers lead the charge on new technology?