Our New eBook: How to Build a Strong Optimization Practice
 
This week we released the eBook,  How to Build a Strong Optimization Practice.
 
Before you download it, let’s see how a strong optimization practice can be built in the context of a demanding industry where users are hungry for more in-depth information than you may have anticipated. The eBook goes into greater detail on each of these topics and provides lessons, insights and examples from our experiences helping our clients optimize and test their data.
 
It all starts in-house where a strong team inside your organization determines the best approach in building an optimization practice to get the most from your data. First, your team will need to:
 

  • Define the Roles and Team Workflow

 
Who’s the decision-maker inside your company? The answer to this question is the foundation of your strategy: Should you have a centralized or decentralized team? In other words, is the decision power in the hands of a top-tier manager or is it equally spread throughout the organization? Once those questions are answered, you’ll be able to move on to the next chapter.
 

  • Choose a Suitable Platform

 
Nowadays there are plenty of platform options, but how do you choose the one that best suits your organization’s testing process? For starters, there are four main features that should be taken into consideration. In the eBook, we put you face-to-face with various questions that will validate or invalidate specific company needs you want your platform to cover. After answering them, you should be able to begin the actual ideating and testing process.
 

  • Ideate & Prioritize Testing

 
This is the part where you start getting your hands dirty. We’ll help you develop a prioritization framework that’ll ensure success with future testing. So what makes a testing idea successful or not?  We touch base on all variables that should be considered and how to gain a deeper understanding of all the information stakeholders might provide you with. This will then lead you to the experimentation part of the process.
 

  • Run Experiments on Your Data

 
Experiments are usually made of seven main elements: a problem statement, hypothesis, team involved, variations, sample size, frequency & duration, and metrics & performance measurement. In the eBook, we explain each one of them and walk you through an example to show you how these work together.
 
Change Takes Time, And We’ll Walk You Through It
 
We understand that changes take time, but you can’t change what you don’t measure. By following the steps in the eBook, How to Build a Strong Optimization Practice, your data will become accurate, easily shareable, and cause a domino effect that will help your organization better understand user behavior and generate new ideas for future iterations.
 
As a last note, there’s no one-size-fits-all approach to building an optimization practice. Personalization is key, and should be taken into consideration at every step of the process. We’ll walk you through each stage of the process so you can get the most from your data.
 
If you enjoy the content in the eBook, please share it with others who might find it useful.
 

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Cognetik

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