Why You Should Test New Ideas

Rapid testing is your secret weapon for making data-driven decisions fast. Unlike A/B testing, which can take weeks, rapid tests can deliver actionable insights in hours. This lean approach helps teams validate ideas, designs, and features quickly and iteratively. It's not about replacing A/B testing. It's about understanding if you're moving in the right direction before committing resources. Rapid testing speeds up results, limits politics in decision-making, and helps narrow down ideas efficiently. It's also budget-friendly and great for identifying potential issues early. But how do you choose the right rapid testing method? Task completion analysis measures success rates and time-on-task for specific user actions. First-click tests evaluate the intuitiveness of primary actions or information on a page. Tree testing focuses on how well users can navigate your site's structure. Sentiment analysis gauges user emotions and opinions about a product or experience. 5-second tests assess immediate impressions of designs or messages. Design surveys collect qualitative feedback on wireframes or mockups. The key is selecting the method that best aligns with your specific goals and questions. By leveraging rapid testing, you can de-risk decisions and innovate faster. It's not about replacing thorough research. It's about getting quick, directional data to inform your next steps. So before you invest heavily in that new feature or redesign, consider running a rapid test. It might just save you from a costly misstep and point you towards a more successful solution.

Progress begins when “I’m done” turns into “What else?” Here's why: You stopped too early, and that’s where the answer lives. Because progress isn’t an event. It’s a mindset. And it’s the foundation of real innovation. Too often, we treat testing like a checklist: ✔ Tried A. ✔ Tried B. ✔ Tried C. And when none of them work, we say: “We’ve exhausted the possibilities.” But here’s the truth: 🔎 You haven’t tested everything. 🔎 You haven’t looked between the lines. 🔎 You haven’t asked the question behind the question. Innovation isn’t about finding “the answer.” It’s about staying open-minded enough to see the answers that hide in unexpected places. The next breakthrough often comes when you stop forcing outcomes… and start exploring patterns, anomalies, and little sparks that others overlook. 💡 Testing isn’t about proving what you already believe. It’s about uncovering what you didn’t even think to look for. Here's 5 ways to implement a “You haven’t exhausted all possibilities” mentality: 1. Redefine testing as exploration → Don’t run a test just to confirm what you believe. → Run it to discover what you don’t know yet. → Every “failed” test is actually data pointing you toward something you missed. 2. Shift from Either/Or to Both/And → Instead of asking “Does A work or does B?” → Ask: “What if parts of A and B combined create something new?” → The in-between often holds the breakthrough. 3. Document assumptions, then flip them → Write down your “obvious truths.” → Challenge each one: What if the opposite were true? → This forces fresh angles that rarely show up in traditional brainstorming. 4. Zoom out, then zoom in → When stuck, step back to look at the bigger system: are you solving the right problem? → Then zoom in: small tweaks (like word choice, timing, or context) often unlock big shifts. 5. Stay curious longer than comfortable → Most people give up when testing gets repetitive or results feel flat. → True innovators keep pulling the thread, asking why again and again, until something new emerges. So the real challenge is this: ➡️ Are you open-minded enough to keep testing after you think you’re done? ________ ♻️ Repost to help others + Follow Jennelle McGrath for more leadership insights

I wrote a post that I thought was brilliant. It got 6 likes (ouch). The next day, I spent 2 minutes on a throwaway idea that blew up. This happens constantly: • The carefully crafted posts I spend hours on? Often crickets. • The quick thoughts I dash off between meetings? Sometimes they resonate deeply. It's nearly impossible to predict which ideas will connect with people from inside your own head. What I've learned is that LinkedIn gives us something invaluable: the ability to take multiple shots with minimal risk. When I was writing my book on building a referral-based law practice, I'd write a chapter, then extract key principles as standalone posts. I never mentioned I was writing a book (crucial detail). When you tell people "this is for my book," they're too nice. They say "you're a genius!" which teaches you nothing. But post the same idea without that context? People will tell you exactly what they think: • "I disagree completely" • "That wouldn't work in my industry" • "You're missing something important here" That honest feedback sharpened my thinking in ways nothing else could have. Sometimes I'd write a post and halfway through think, "Do I even believe this?" The act of translating complex ideas into concise posts forces a clarity that's hard to achieve otherwise. The best part? There's no penalty for testing ideas that don't work. Delete the post. Try again tomorrow. No harm done. So if you're working on something big—a book, a business idea, a new service—consider using LinkedIn as your testing ground. Don't wait until your idea is perfect. Put it out there, see what happens, and let the feedback guide you. The market will tell you what resonates. Your job is to listen. #ContentCreation #IdeaValidation #LinkedInStrategy

I co-founded Quest Nutrition with just $10,000. Five years later it was worth $1,000,000,000. Here's the systematic testing framework that made it all possible. Most entrepreneurs waste months testing random ideas with no plan. I built a billion-dollar company by doing the exact opposite: I created a system I call the Test Stack Method. Here's why most testing fails: People test everything at once. They have no hypothesis. They don't know what success looks like. And they quit after one failure. The Test Stack Method fixes all of this. It's a logical sequence where each test builds on the last one. If Test 1 fails, you know exactly what Test 2 should be. No guessing. No chaos. Just systematic progress toward truth. Here's how it works: Step 1: Stack your tests logically. Write down 5 ways to test your idea, from cheapest to most expensive. Example stack for a meal delivery service: Test 1: Survey 100 people about their biggest meal problems Test 2: Create a fake menu and see if people try to order Test 3: Hand-deliver 10 meals to validate the full experience Test 4: Build a simple website and get 50 real orders Test 5: Launch in one neighborhood with repeat customers Step 2: Write your hypothesis for each test. Before you start, predict exactly what will happen. "If 60% of people say they'd pay $15 for this meal, then Test 2." "If less than 60%, we need to change the price or the meal." No moving goalposts. No tricks. Step 3: Set clear success criteria. Define what "pass" and "fail" look like before you start. This stops you from lying to yourself about bad results. Step 4: Run one test at a time. Only move to the next test if the current one passes. If it fails, figure out why before moving forward. At Quest, we used this method to test everything. Flavors. Packaging. Pricing. Distribution. Each test taught us something that made the next test smarter. We failed fast and cheap instead of slow and expensive. By the time we launched, we knew exactly what would work. Most entrepreneurs test once and either give up or double down blindly. Both approaches waste time and money. The Test Stack Method eliminates guesswork. Hope is not a reliable business strategy. Testing is. My free Zero to Launch tool helps you build your own Test Stack before you waste time building the wrong thing. Get it here: https://buff.ly/Non9CN3

Here’s one reason to think big and try new things: With AI, the cost of experimentation goes down. This allows business operators to think about risk adjusted returns differently. In the past, certain costs and dependencies have kept many projects from moving forward because teams couldn't get support for the ‘cost of consideration’: the capital required to formulate a compelling (and as importantly, believable) risk-return model for an initiative. Countless solid ideas have failed to graduate beyond the idea phase.  Now, there’s a huge opportunity for businesses to benefit from a new technology. We can now use AI to drive down the cost of research and, potentially, experimentation. More robust research done at a fraction of the cost will help underwrite investments that would otherwise not even receive a second look.   This means individuals, teams, and organizations are in a position to try more things at more reasonable price points. Put another way, they can place a greater number of bets with equal or higher yield. Another thing to consider is whether you have adjusted your mark for what constitutes something being researched well enough to warrant investment. Has your posture been adjusted to the AI enabled world?  What used to cost you $50,000 may only cost you $500 today.  What idea haven’t you funded in the past year because you were still applying an old model to the new world? #AI #innovation 

How do you plan when uncertainty only seems to grow? Through embracing disciplined experimentation. Here’s new writing from our Partner Charlotte Desprat on the five-step process we use to make a company great at it: 1. First, establish what you know as fact and what you don’t know – including the X-factors that could upend your plans. 2. From there, tease out the key hypotheses that you want to test. Keep in mind that some hypotheses might be more fundamental than others, and therefore might need to be tested earlier. 3. Then, consider how you might investigate each of these hypotheses using the scientific method. How can you break hypotheses into small, easily-testable components? Depending on the degree of unknowns, a rapid-fire approach might be enough to determine the key components of change. 4. Once you’ve designed your experiments, consider the time, cost, and risk associated with each. Together with the importance of each hypothesis, decide which experiments must come first vs. later. This will give you a priority list to adjust along the way. 5. Finally, set up a system by which you can quickly capture learnings and adjust. Obtain tangible measurements from these experiments. Your system should include a way to decide which experiments to follow up with, know if more are needed, and determine when you’ve learned enough from a given test. Critically, it should include a mechanism to end new ideas. Remember that about 80% of venture capital investments fail, and yet venture capitalists earn higher return on capital employed than public companies; their secret is that most of their failures come early, quickly, and cheaply. By treating experimentation as a discipline, not a one-off, you can capture the upside of uncertainty. That will be one of the most important capabilities to win in a turbulent future. Interested in our book chapter on experimentation? Click here for a direct download: https://lnkd.in/eAnUrC2t