Wouldn’t it be great if you didn’t have to burn through thousands of dollars to see if your product or service is profitable? Even better, how cool would it be if you just put something simple together that got your idea across, then let the users do all the work for you? Well, that’s actually easy to do when you know how to track and digest customer behavior, then turn that into smart, iterative solutions.

Create, Collect, Change—Iterating Smart Solutions

Okay, maybe it’s a little more work on your end than that, but not by much. First, you develop and release a Minimally Viable Product (MVP)—that is, creating a first version of your product containing the least amount of features possible while still satisfying the intention of your product. Simplicity and speed is the goal here.

Next, you track how your users interact with the product. What’s the user’s experience (UX)? From heat-mapping to click-tracking, every move a user makes while interacting with your product can be tracked in order to facilitate product optimization. It’s all about data collection, interpretation and actualization (more on this in a bit).

Finally, use this data learning to iterate solutions. In short, take what the users told you with their actions and then give them what they want in the next version. Why risk building what you think consumers want when they’re literally telling you what they want with their interactions—it’s about user needs, not your own. So, you simply change your product to get in harmony with the market.

Is This a Better Approach than UX Research?

“Well, why am I spending all of this money on UX research?” you’re probably asking. Good question. UX research does play an important role in product development, but it can only take you so far. That’s because speculative research can’t guarantee success—instead, it more or less tries to help you predict and manage your expectations of failure or success (if we’re going to get real about it).

Time and time again we’ve seen entrepreneurs that want to rely too heavily on what the predictive data says and not what the actual user data says. Some startups wait too long to implement iterative solutions, and wind up missing the window of cost-effectiveness (generally speaking, the sooner you start iterating toward user data, the more money you save) while simultaneously losing early adopters.

How to Improve Your Conversions Using Iterative Solutions

For starters, we help our partners track every single interaction that their user is making. Every.Single.One. Where they click/tap/swipe or scroll, how long they mouse over a certain section, what they had for breakfast…okay, maybe not that last one. But everything else!

At Litebox we use smart, simple, and efficient methods to keep our startups from wasting time and money.

Once we have all this data, it’s important to be able to separate vanity metrics (things that might look good on paper, but mean nothing) from the data that matters. This is accomplished by setting up conversion funnels that track a user’s journey while they march toward the goal: Conversion. As they reach checkpoints throughout the funnel, they move further down the funnel toward the goal—if we aren’t seeing those checkpoints hit, we need to go back and either make changes to the product or the funnel, e.g., smart iteration.

Another way our startups quickly attain their best results is through our completely customized dashboards. Elegant dashboards help our entrepreneurs make the best decisions based on input from some of the most cutting edge tech out there—not to mention our teams’ extensive battery of professional experience.

Remove the Guesswork and Make Your Guests Work

Simply put, smart iteration is the best way we can help our entrepreneurs learn from mistakes that would otherwise prove fatal to misguided entrepreneurs. By doing this, startups are able to minimize their risk of failure before leaning full tilt into a product and potentially blowing through all of their capital. We save companies time and money while maximizing their success, all by taking the guesswork out of the equation and giving the users what they actually want—and all we have to do is listen.

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