This is the first blog in a multi-part series that will outline how to create a successful optimization practice within your organization
OPTIMIZATION: an act, process, or methodology of making something (as a design, system, or decision) as fully perfect, functional, or effective as possible.*
Sounds great, right? We think so, too, and we have a practice area dedicated to helping clients take real action around this topic. The exciting part is, there is no one way to approach it or one place to do it, so this leaves a lot of room for creativity. Furthermore, it means that it’s an iterative and ongoing process – really, we think about it as developing a culture. Since, it isn’t something you stop and start or finish.
Digital Optimization really begins with 3 main questions:
- What are we trying to optimize?
- Where is the greatest area of opportunity?
- How can we improve conversions?
ESTABLISHING A DATA-DRIVEN MINDSET
The first step in all optimization programs is establishing a data driven mindset in the organization. If the organization does not look to data to make key decisions, the testing output will most likely go ignored as senior management continues to make decisions on gut feelings.
The process of creating this data-driven culture is a task in and of itself, but can be boiled down to a few key steps. First, it is imperative that you “Democratize the data.” This means making the data accessible to everyone in the organization. Help stakeholder to understand what data exists today, how to access it, and how to interpret it.
Next, it is essential to invest in the right people – no matter how great your tool may be, if you don’t have the right resources in place to analyze and interpret the data to create actionable insights, the money spent is all for naught. You must have the capacity organizationally to understand the data that you have and identify data that you need.
As mentioned above, making an investment in the right tool is important. This includes thinking about tools that not only work for your current environment, but also for your future goals.
So, to bring this all together, it is important to plan for and execute on investing in the training and development for your people to use the tools effectively. Technology is constantly changing and so is the way we look at data. Making sure your team is current on best practices will go a long way in establishing credibility in your data.
Lastly, it is important to embrace change – change can be risky, but if you fully trust your data and your people, the risk can be greatly reduced, while increasing your rewards.
USING DATA TO FOCUS YOUR EFFORTS
When first starting out, most companies want to dive right into testing without doing the analytical legwork to help them focus their efforts. This often leads to tests that lack compelling results. It is important to use all available data (web analytics, voice of customer, survey, user lab testing, etc.) to help focus your efforts.
Once you identify your main areas of opportunity you can begin to develop your roadmap from those points, placing high opportunity, low effort tests at the top of the list and high effort, low opportunity tests at the bottom. This approach is not 100% foolproof, but will deliver compelling test results on a more consistent basis than gut feelings alone.
Think of it like trying to hit a target at a range. You can take the time to calculate the distance, elevation, wind speed and direction, and use that information to calibrate your scope; or you can just start shooting. Sure, you may hit the target with the latter, but if you take the time to accurately calibrate your shot, you will hit the target with greater accuracy and precision.
So, how do you get started? You’ll have to read the next blog in the series – where we will dig into how to create an Opportunity Report and what metrics to look at to identify your testing priorities.
* www.merriam-webster.com/dictionary/optimization
Further Reading
Getting a Testing Program Off The Ground: Optimization Part 2
3 Key Questions for 2015: Governance, Big Data and Customer Journeys
Advanced Analytics and Marketing Optimization – 2 Sides of the Same Coin
