There’s that word again: Optimization
It was mentioned at the end of your digital business review meeting last week. It floats through the air at every industry conference you attend, and was the last line item cut from every budget you oversaw in 2014. And 2013.
Like any emerging practice, Optimization may be something you are investing in but unsure if you’re doing right.
If you’re like most organizations, you first licensed software and then added seats to the table. Many fold Optimization into someone’s job description only watch as it becomes marginalized as a downstream administrative function. For years, I did similar things myself. I began with an accepted model of Design, Build, then Measure. If there was still time and budget we “Optimized.” Sound familiar?
Pivoting From Answers to Questions
Why were we testing and learning only after the “big” work was already out the door?
Most Optimization efforts I saw were post-hoc, isolated, and relatively narrow in impact because they weren’t attached to big bets made at the outset. When I accepted Optimization as a mindset, and not a stand-alone service, everything turned inside out.
I began to think of Optimization a process with no beginning or end – as the validation of all important hypotheses related to my digital business. Not as just another thing, but as the thing.
I had come to recognize Optimization could do much more than simply drive design, development, content and merchandising processes to deliver digital product ROI. Optimization as an organizational commitment was like earning compound interest.
By testing and proving the value of data-driven decision making, the impact of these collaborations inevitably led to measurable efficiencies throughout the entire organization. Opinions, debates, great ideas and impossible ideas all now had paces to be put through. We would not only know whether strategies, plans, and tactics were any good. We would know, with confidence, why or why not.
Getting Onboard With the Big O
Without question, more and more organizations are integrating user-based data into design and development improvements. Unfortunately, I’d say most are only getting fractional benefits.
Just because you are AB testing does not mean you are Optimizing. Optimization is a holistic approach to UX, Product Development, Digital Content & Promotions that contemplates the validation of all hypotheses, using a variety of tactics, including split testing, usability testing, pre-post analysis and segmentation or personalization.
Ultimately, I believe we deserve to see how data can do more than redecorate; it can deliver broad and continuous improvement. More than reporting on monthly or quarterly KPIs, data is for Optimizing outcomes. Data answers the questions we pose. It validates our hypotheses. It propels us forward. And, in 2015, with testing, personalization and analytics software more supportable and powerful than ever, we have the opportunity to Optimize quickly. And yet, most people I talk to still feel like they are falling short. And looking back.
Getting off the merry-go-round is different for every organization, each has its own inherited structure. The Clearhead experiment was born out of my own necessity, but I know we’re not alone in believing that digital organizations and processes have, generally speaking, not evolved to capture the full value of data-driven Optimization.
Every day, we test how Optimization can work as a system rather than a single service. What’s rewarding, is that we don’t prove it to be true, our clients do.
I’m guessing you probably know whether you are kind of optimizing or really Optimizing. Want to talk about it?