Career Opportunities And Perceived Value

Tell me the last time you observed these titles at a business-to-consumer organization (non-vendors):

• Vice President of E-Mail Marketing.
• Sr. Director of Web Analytics.
• General Manager of Business Intelligence.
• SVP of Catalog Circulation.
  

It's interesting that many businesses have an executive in charge of information or technology (CIO or CTO). Many businesses also have pay scales that are very favorable to information technology employees. In other words, an e-mail manager might earn a base salary of $75,000 per year, while a comparably skilled information technology individual might earn $90,000 per year. The information technology individual might have a limited career path, but at least she gets compensated for the unique skill set she offers to her company.

Which brings us to the typical e-mail, catalog circulation, web analytics, SAS/SPSS programmer, data miner, or business intelligence individual.

What is the career path for the web analytics individual using software that doesn't even capture 100% of online sales?

What is the career path for an e-mail manager that is given no budget, but is criticized for generating only $0.09 per e-mail delivered?

What is the career path for the SAS programmer who provides the intelligence that an information technology individual cannot provide, yet is considered a "computer geek" by Sr. Management?

What is the career path for a catalog circulation manager that is criticized by eco-friendly organizations for cramming unsolicited junk mail down the throats of helpless consumers?

In my opinion, there is one common theme across each of the four jobs I described ... perceived value.

The e-mail marketer is a spammer. The web analytics individual measures only one channel, and cannot frequently tie out net sales to finance-based reality. The SAS programmer is a computer geek. The catalog manager is always wrong, why would you mail a catalog that 98% of the people hate, can't you only mail the catalog to customers who will purchase?

Remove the information technology expert from your business, and your order entry system might stop taking orders. That's what "perceived value" is all about.

Stop sending e-mail campaigns, stop sending junk mail, stop creating a report that requires a complex merge of e-mail address and multiple mailing addresses, stop showing that conversion rates are flat, and who cares?

Career opportunities are often based on the perceived value of the individual. I know this is true, I've experienced it. I've been told by leadership that I'm not qualified to do any other job than an analytics-based job.

Conversely, merchants, those who choose product, are perceived to have high value, perceived to be able to lead finance individuals or marketers or information technology experts or call center leadership.

So many of my loyal subscribers are e-mail marketers, catalog circulation experts, web analytics professionals, or business intelligence / data mining wizards. Collectively, we have two problems.

• We have low perceived value.
• We do a terrible job of marketing our skills.

Not surprisingly, these two issues are interrelated.

There are three types of employees in the multichannel world.

• Employees with scarce skills, like the folks in information technology.
• Employees with leadership potential or those with the ability to "move the needle" on sales. Think CMOs and merchandising executives, as examples ... especially CMOs, folks who either drive a big increase in sales, or are kicked-out within two years.
  
• The rest of us.

In order to reap the benefits of career opportunities, "the rest of us" must market ourselves as indispensable individuals. Either we cannot be easily replaced, or we provide such significant value (sales, profit, leadership, consumer insights) to the business that we cannot be ignored, or we must market our value to the rest of the organization to increase our perceived value. Otherwise, we must be at peace with our lot in life.

At this point in time, few promotional opportunities exist within multichannel brands for my readers, causing my readers to switch jobs across brands, or to venture to the vendor side of the equation to find opportunities. It might be time for us to start marketing our abilities, to begin increasing our perceived value, or to actually prove that we are highly valuable.

Data Mining vs. Mining Data In Multichannel Retailing

If there's one thing I've learned during my first four months as a small business owner, it is that multichannel retail executives are hesitant about "data mining", but are very enthusiastic about "mining data".

Assume you have a catalog/online CEO who wants to understand how website customers behave between a first visit and a twentieth visit.

A statistician might provide a series of reports and analyses that thoroughly explains the process from soup to nuts, publishing exciting findings along with complex statistical information to support his findings.

The multichannel CEO nods politely, even offers verbal kudos, then leaves the room feeling like she still doesn't understand how her customers behave.

The person who "mines data" identifies the handful of key findings that every CEO must know, then puts the findings into a context, a "story", that the CEO can use to create actionable strategies that drive sales and profit. There is something that the CEO can "do" with the findings, and it is easy for the CEO to "know" what the next steps are.

Mathematically, this type of work is much less satisfying. Professionally, this kind of work can be more gratifying.

Data mining software and data mining experts are generally plentiful and affordable in multichannel retailing.

Folks who "mine data" are generally in short supply, and are desperately needed by multichannel executives.

Fresh Data And Storytelling

Back in 1990, you'd feed a 5.25 inch floppy disk into your IBM-AT desktop computer. You'd fire up SPSS. At the bottom of the screen ticked the number of records that were being processed .... 20 records ... 40 records ... 60 records ... 80 records.

Today, I loaded a large dataset, wrote six hundred lines of code, and began processing the information. At the bottom of the screen, I could visualize the records as they were being processed ... 200,000 records ... 400,000 records ... 600,000 records ... 800,000 records. Thank you, Acer, AMD and SPSS for providing a fun computing environment.

It's a blast to see new data, information you haven't been exposed to before. The data at Nordstrom seldom changed during my six years there. Sure, occasionally the annual retention rate would vary (maybe 67.2% one year, then 69.3% the next year --- if you are at Macy's or Neiman Marcus or Saks, sorry, those aren't the actual numbers). New customers might vary by fifty thousand verses forecast. There were seldom huge surprises. Such is the case when a business consistently meets or exceeds expectations.

When you get to see new data from a new company, there is a sense of exhilaration. It is like opening up a box of puzzle pieces. You find the corners and the border pieces first. Each piece fits into another piece. Eventually, the pieces provide a path for you to get to the end of the assembly process.

Each line of code produces reporting --- the reporting tells a story. Existing customers are retained, lapsed customers repurchase, new customers feed the future growth of a business. Within minutes, the lifeblood of a company is evident on your computer monitor.

Looking across years, you can visualize the decisions that executives made, decisions that caused increases or decreases in customer counts. These increases or decreases drove subsequent decisions, which drove increases or decreases in customer counts. Within an hour, Multichannel Forensics illustrated what happened, and forecast what is likely to happen in the future. Suddenly, there is a story to tell.

There is a huge difference between Data Mining and Storytelling. Data Mining seeks to explain the data. Storytelling is an art form that translates information in a way Executives can digest, understand, and act upon.

Data Mining has a place without Storytelling. Data Mining coupled with Storytelling yields potential. Data Mining and Storytelling that speaks directly to a current, future or perceived Executive need (as defined by the Executive) causes change.

Measuring Advertising Effectiveness, Early Feedback

Lots of good feedback so far on the exercise to find a way to measure advertising effectiveness, and on the dataset of ten thousand simulated customers. Several vendors have volunteered to attempt to find a solution, and I received feedback from several data mining experts that they want to take a crack at the exercise.

If you know of good analytical folks, or you work with good vendors willing to try to solve something for the good of the catalog/online industry, send them this link. Entries need to be submitted by January 31, 2007.