Posts Tagged ‘business intelligence’
I have an interesting pair of careers. For the past decade or so, I’ve been working in digital marketing and analytics. Simultaneously, I earned a Bachelor’s degree in philosophy and I’m about to start work on a Master’s. Now, that may seem like a diverse resume, but these two areas aren’t so different. They’re both concerned with understanding the truth of things. They’re both governed by clear, rational and precise thought. They both require you to see the big picture when your attention is focused on the tactical and technical aspects of what you’re doing.
This series of posts is going to look at business analysis from a meta-level, analyzing the process and delivery of analysis itself. I’m going to cover the five traditional areas of philosophy, which are epistemology, metaphysics, ethics, aesthetics and logic, giving a bit of explanation of each and where our profession stands. It should be a fun and wholly geeky adventure.
The Epistemology of Business Analysis
Epistemology is the area of philosophy concerned with knowledge. Its fundamental questions are as follows: What counts as knowledge? How can we acquire knowledge? Can we trust our knowledge? Closely related to epistemology is the philosophy of science, which covers a breadth of topics related to the acquisition of scientific knowledge.
As analysts, we like to believe that what we’re doing is scientific. Rightly so, I think. We’re concerned with understanding why the data we get is the data we get, and what data we will get next based on certain actions. When we’re doing things right, we follow a scientific methodology that involves testing our hypotheses and constantly revising our theory. All of this ties in closely with questions of epistemology.
I have been stewing all week over a great blog post I read by Evan LaPointe, a digital marketer out of Atlanta. The post was entitled “I don’t want an analytics job”, and it seems to carry over the same feelings and themes of an earlier post he wrote called “Web Analytics Sucks, and it’s nobody’s fault.”
These posts both excited and annoyed me at the same time.
On one hand, it was almost liberating to read that someone is living in the same trenches that we are at Napkyn. A lot of the points of frustration that Evan talks about – like navigating both internal politics and sub-par data as well as having the role of web analyst considered a low-level technical job rather than a high level executive job – hearing someone else say this stuff will make any analyst grin and buy in. It’s like reading a good Dilbert cartoon and thinking “Hey, that is SO where I work!” – it’s cathartic, but not productive.
Hence my annoyance. Evan touches on all the challenges with being an analyst, and outlines all the skills (data analysis) and opinions (Always Be Testing) that good analysts bring to the table. But his conclusion is that good web analysts don’t actually want to be web analysts, they just represent the next generation of executives-in-waiting – web analysis is beneath them. He says that web analytics actually want to be the ‘shepherds’ of a business, who use data to help guide the organization to ongoing successes. There’s already a job title for that – it’s a CIO.
So while I totally agree with the sentiments, I thought I would share my thoughts on what the real issue is.
Being a Web Analyst is hard.
I don’t want to reopen the whole “Web Analytics is Easy/Hard” debate, but I do want to agree with and elaborate on Evan’s key points.
Most organizations aren’t ready for information based decision-making, and while many firms know that analysis brings results, they do assume that an analyst will generate a ‘magic report’ rather than help move the business forward over time. This is frustrating, and it takes a lot of patience, diligence, and small wins to earn the right to change this perception. With every client we work with, this process takes time, and it always pays off.
Very few tools play well together in the digital sandbox. In a lot of cases, it would be easier if certain kinds of technology didn’t exist – their standalong datasets add zero value unless a ton of work is thrown at them to make them align with corporate data (pay for performance vendors and dynamic CMS systems come to mind immediately here). It’s awfully hard to internally sell the value of analysis if you spend half your time talking about what you can’t see clearly because of technology/disparate data issues. Tools vendors make analysts look bad.
I don’t think that most web analytics practitioners secretly wish they were a CIO. A lot of us live for that ‘eureka’ moment that happens when you uncover amazing insight about the business, or implement a small change that immediately creates a big impact. There’s a big difference between someone who love continuous improvement and someone who wants to run the whole business.
Just because it is hard to be a web analyst right now doesn’t mean that it will be forever. As more of us start to organically change the culture of the organizations we are in, performance management and analysis will start to trump “I think, I feel, I want” and we will get better seats at the table. These information oriented organizations will refuse to accept the vendor data shenanigans and we will get better and easier visibility into the entirety of the digital data.
I for one, love having my web analytics job. It’s not always easy, but panning for gold in the digital wild west has a lot of payoffs that make the frustration worth the while.
P.S. Evan, keep up the great writing and if you ever decide to move to Ottawa I have a job for you – we can work together to come up with the right title
All too often, when it comes to online businesses, we tend to simply go with our gut feeling. Will a video on the homepage increase bounce rate? What sort of discount will result in the most sales?
Most online business owners and managers just don’t have the time or mental energy to perform the tasks required to determine these best practices. Well, a blog post by the Harvard Business Review has some harsh words for business owners who just shoot from the hip: There’s a much better way of doing business.
Andrew McAfee states that while there are some cases where human intuition has become a useful tool, in modern business, there’s no reason to ignore data and critical analysis.
Overall, we get inferior decisions and outcomes in crucial situations when we rely on human judgment and intuition instead of on hard, cold, boring data and math. This may be an uncomfortable conclusion, especially for today’s intuitive experts, but so what? I can’t think of a good reason for putting their interests over the interests of patients, customers, shareholders, and others affected by their judgments.
However, if talk of statistical analysis makes you think of punch cards and supercomputers, you’re way off track. There are a plethora of (sometimes free!) online tools that can help online business owners and managers make the best decisions based on real data, generated by your website visitors and customers.
Of course, here at Napkyn, we help business owners and managers make sense of this data using digital analysis. Quite often, we find underserved segments and opportunities for conversion that intuition and guess work would never have stumbled upon.
So you don’t have to trust your gut anymore–unless you’re thinking about lunch, of course.
We have been talking to and working with a lot of companies this year for web analytics, and an interesting trend has been emerging with the executives that we are dealing with. Most digital decision makers we talk to either want to have Napkyn deliver ‘magnifying glass’ focused consulting on a few critical business metrics every month, or they want us to pull out the microscopes and look for new revenue potential in the specifics of their data.
In understanding these two types of executives, their motivations and ultimate goals, we can quickly see what value a good web analyst can immediately bring to an organization.
Executives who are responsible for a digital channel tend to fall into one of two types:
Analytics for performance management (macro level analysis) : Macro executives view WA data as a set of health metrics that can be used to understand the digital business. Their ultimate goal is to have a small set of business critical metrics that they can monitor to assess their online success. An example of this would be Patrick Byrne at Overstock, who says that he continually monitors their net promoter score as an operational success metric.
Analytics for performance optimization (micro level analysis): Micro executives are a fast growing group (especially in digital retail), and they focus on using their website data to continuously improve the results and returns of their site. Keyword reports, landing page data, shopping cart step analysis are all areas where reams of data are modeled and tweaked.
Macros tend to be more traditional executives, often in roles where the website is only one part of their overall mandate (i.e. business to business). Micros tend to be almost exclusively digital marketers, and often have the vast majority of their marketing spend online (i.e. eCommerce).
The Napkyn Analyst program includes a performance management component. By listing the top 5 things a Macro really cares about and then reporting monthly on the health of these 5 things, we can create a really transparent ‘state of the union’ report. No decision-maker will look at their website the same once they have a strong ongoing understanding of the health of their traffic, their primary goal conversions and their marketing ROI. The problem with this being the endgame of analysis is that it is entirely too reactive. Knowing that traffic has gone up (green) and conversions have down (red) is important, especially if you can isolate root cause. There is no component of a straight performance management initiative that relates to optimization.
Napkyn’s analyst program includes an optimization top 3 report and optimization index in each monthly report we deliver to a client. The purpose is to isolate segments of under performance in the web data, make recommendations on ways the under performing segment can be optimized, and then track the results over time. This is a huge selling feature to Micros, who don’t have the time and the expertise to build a plan around this kind of continuous improvement initiative. But how valuable can optimization be if not taken into the context of the overall health of the business? Perhaps we grew the conversion rate of Australians by 300%, but hurt our overall sales by alienating North American Traffic. Context is king.
What we see happening with our Macro and Micro executives is that they start working with Napkyn to meet their specific goals “I only care about the Magnifying Glass reports” and after about a quarter of ongoing deliverables become equally as interested in the other half of the document “I’m losing that many conversions from that landing page? What should I do?”
I could carry the metaphor into how our reports are like bifocals….but I digress.
The important point is that a good analytics process allows you to see the big picture in such a way that you can understand and action on the specifics that you isolate.
What’s your process? Is it profitable?