Building an optimization culture is hard and it seems that it might be getting harder. My friend Avinash Kaushik, the analytics evangelist at Google, recently shared an important stat and his observation on Google+:
Only 22% of companies have a strategy that ties data collection and analysis to business objectives. Down from 25% last year. [Source: Econsultancy Online Measurement & Strategy report http://goo.gl/OGscu]
The problem is not the tool. The problem is you and me and our management.
Think of it another way: 78 percent of companies are just hoping for success by guessing how well they are at providing their customers quality experiences. While we may all be suffering from data diarrhea, making decisions based on analysis of our metrics is just unclear, and they fear failure. Some call this assumption marketing. For over a decade, I’ve called this a symptom of accidental marketing.
One key question is why did the numbers go down from 25 percent last year to 22 percent this year? My answer stems from a simple economic theory that holds true in most marketplaces. The rich get richer! It happens in finance, it happens in SEO with the Filthy Linking Rich, and it happens in data-driven cultures. Companies that have a culture of analytics and testing seem to pull in those individual talented people who show up at the odd company and get frustrated that they have no impact or value there. I have seen this countless number of times with friends in this industry. It’s frustrating, like pushing on a rope.
When leadership’s ability to focus on optimization is dysfunctional, they keep relying on the next “big idea.” They favor long CYA meetings instead of managing to the metrics that impact their business. They continue to do business largely the way they have for the last 20-plus years, even though everything around them tells them the world has changed. Meaningful change is not just releasing a cool mobile app and launching a new HTML5 website. It’s not the medium but a management and business cultural issue that needs reexamining.
As Marc Bruns commented on Avinash’s post:
The fact is becoming an optimization culture is hard. In my experience, implementations of any kind of data-driven metrics, analytics face the hurdle of an ‘irrational exuberance bubble’ when they begin … early on it seems like it will be easy to change the world, the tools seem so powerful … but then people, politics and turf battles enter the picture; [when times get the least bit tough] management tends slips [sic] into old habits, ‘the old shoe is comfortable.’
I’ve harangued many and even written before about what it takes to build an optimization into your business culture. What’s the first step?
Focus! Pick your key performance metric and get your team obsessively focused on continuously improving the marketing efforts and time spent achieving those numbers.
Web analytics industry pundits have suggested that the key to success is better investments in people and process and less on tools. That’s wonderful! Nevertheless, neither of these matter if the investment isn’t on changing culture first.
So companies bring in the tools and assign someone inexperienced to start distributing reports and they start to believe that they are data driven. Surprise! There’s no profit from having a web analytics report; you make money from making changes and experimenting based on the insights available from the data. In order to do web analytics correctly, it needs to generate a to-do list for you.
However, as Philip Walford, another commenter on Avinash’s post adds:
You’ve been scrupulously data-driven in identifying where problems and inefficiencies are located, but now you have to switch and start to hypothesise about why those problems and inefficiencies exist. Two entirely different disciplines: rare to find them in one individual, almost impossible to find them in one organisation.
It is this sluggishness of corporate metabolism to change that has allowed many in the retail industry to forfeit their sales to Amazon.com, which now dominates approximately 30 percent of all U.S. e-commerce.
Noted author Stuart Wilde says “Poverty is restriction and as such, it is the greatest injustice you can perpetrate upon yourself.” Are you condemned to be data rich but optimization poor?
I don’t think it is because companies don’t care or haven’t tried. Are the tools to blame? Partially! First and second generation tools flourished by the promises of riches to come by just tracking the data. Many invested significantly in these tools, but couldn’t find the people to support it. Now many free tools exist and more people are used to using these tools. I’ve always said get good at free and then pay. So are free tools the answer? Nope! Just because someone knows how to use the tool, doesn’t mean they can “convert” management into a data-driven culture.
It’s increasingly harder to hire truly qualified candidates; not that many exist in the first place. When my brother Jeffrey and I built our agency, we’d hire young college graduates who displayed tremendous amounts of curiosity and trained them in our processes and they were turning out insights that rivaled their high-priced MBA alternatives. Training certainly is one option, but it doesn’t work if it cannot be evangelized throughout the whole organization. It fails if all it does is make one or two optimization/analyst employees smarter, because in the long run, those employees will find work elsewhere.
Will you commit to optimization riches or will you remain poverty stricken? Isn’t it time to focus on what the numbers are already telling you?
A new starter in Team SaleCycle recently asked me the following question… “Wouldn't they just come back anyway?”
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