How to Combat Confirmation Bias

As analytical professionals, we are people people. We do our work because we care about people. We want to help them make the best decisions they can.

To help people, we need to understand people. And people have cognitive biases.

In a series of posts, we will explore these biases and how to overcome them.

First up – confirmation bias.

People see what they want to, usually. They tend to accept evidence that supports what they already think is true, and reject evidence that goes against it.

As analysts, we are after the truth. So, we fight confirmation bias.

But not head on. Because we will likely lose.

Let’s take an example.

You just worked hard to get some numbers that unfortunately tell you that the marketing department is doing a perfectly wretched job. No positive growth. Negative ROI. Terrible lead quality. They need to know! So you go to the marketing director and you say “if you keep doing what you are doing, you are going to burn down this entire company and sink the ship to the bottom of the Marianas trench.”

They will fight you and tell you your data is wrong and your analysis is wrong and you will lose the war and then the company will burn down.

A better option: Get some confirmation bias on your side before you try to fly in the face of everything the marketing director holds dear. “Hello marketing director, I was looking at some numbers on one of our campaigns and I’d like to go over it with you.”

Marketing Director has less confirmation bias about how well a single campaign did than he or she does about how the entire department is doing. If you carefully show them the analysis, they just might believe you. And now you’ve planted a new, smaller bias in their minds – a bias that tells them, subtly, if one campaign didn’t do so well, maybe marketing isn’t as incredible as we thought.

Take as many small steps as you need. Rally some bias to you side (which if you did your work right, is the true side). And when they have enough bias in favor of the truth, lay it all on the table.

Doesn’t work every time. But it works much better than kicking in the door.

Find Companies Using Visual Analytics Software

Visual analytics is a large and growing industry. If you are a consulting firm, you may very well have a branch of the company that helps people understand how to use visual analytics tools, like Tableau or Spotfire. You may even offer specific training for these tools.

If so, companies that use this kind of software are your ideal target prospects. Using our new technology, we found that we are able to identify them with data found only on the web.

We ran the algorithm to find companies using Tableau, Qlikview, Spotfire, and Microstrategy. At a first pass, 170 companies showed up from New York alone.

If you offer consulting services to companies that use this kind of software, these are definitely leads you’ll want to have a look at. If not, your competition definitely will.

If you would like to learn more about these companies, fill out the form or contact us directly.

Get a List of Companies Using Your Competitor’s Software

Knowing who is using your competitor’s software is extremely valuable. It gives you an idea of how strong of a foothold they have on the market. It gives you a list of specific companies that need your services. It tells you the talking points you need to win out over the competition.

On a high level, it gives you better strategic insight. On a tactical level, it gives your sales and marketing teams specific prospects to go after.

With the amount of data that is freely available online, it is now possible to be able to identify many of these companies. The only difficulty is knowing where to look, and then having an automated process that can extract, crunch, and understand that information to pull out specific company names and the software they use.

Vault Analytics has recently developed technology that can perform this function, quickly and easily. Just provide the names of the competitor software in your industry, and our technology will scan for companies that are using it and produce a list of prospects for you.

Give it a try today for free. Let us know what you think.

A Word on LinkedIn for Your Marketing Analytics Job Hunt (Post 6)

LinkedIn is your de facto online resume. But it doesn’t replace your real resume. Rather, it is the faithful sidekick.
And as the sidekick, all of the same rules apply. Write a good resume, and LinkedIn is easy.  

It becomes little more than a cut and paste exercise into the appropriate boxes.

Here is why it’s important – It’s guaranteed that your hiring manager will look you up on LinkedIn before you come in for the interview. This is your chance to greet them, show them you are a pleasure to work with, and that you can solve their problems.
So greet them with a nice, professional, smiling graphic of yourself. Wow them with the resume statements you copied and pasted (changing a few things here and there, just for fun).
As an aside, you should probably have a decent number of connections (anything over 70ish is fine) and at least a few of those silly endorsements at the bottom. Nothing big to worry about, but the absence of either of these may cause a little bit of pause for the hiring manager.

Next post we’ll look at how to use your blog to effectively get hired. Or feel free to get all of the information today in the ebook.

The Importance of Your Resume in Getting Hired in Analytics (part 5)

Analytics Resume
Without a resume (or rather, without a good one), you don’t even get into the door. You don’t get to talk to anyone and tell them all about your experience and skills. They will never meet you or know you exist.
The self-proclaimed social web experts will contest this point. They’ll say you can do it all with Twitter. Or LinkedIn. Or online talking videos of yourself. And these may work sometimes, and they may even be useful. But they are not fundamental.
And despite what people will tell you, the resume is still fundamental.
So, how do you write one that will make the recruiters call you and your future employer eager to talk to you? The answer is very simple, but please give it a moment of thought and let it sink in.
Looking at your resume, they need to feel like you are someone that can solve their problems.
Let’s talk about a hiring managers problems. He or she is under the gun to produce results for the company. They need to be able to show that they are adding revenue, reducing costs, and optimizing processes. They need to show that they are taking the company somewhere it’s never been before, and that that place is the promised land.

Does your resume reflect that you are the one that your hiring manager has been hoping for and dreaming about? If it has the following elements, then you bet it will.


Element #1: Results

What has been the result of all the effort you’ve put into your professional life? What good has come of it? When hiring managers see that you are someone that can actually produce real world results, and not just do hard-sounding things, they will swoon. Let’s have a look at two examples of statements you might find on a resume.

Not so good:
Implemented and optimized technologies such as Tableau, Eloqua, Google Universal Analytics, SQL Server, and Python to enhance the company’s analytical capabilities.

Saved the company an estimated $200,000 to date by creating strategic dashboards in Tableau and training the campaign managers how to use them.

Which of these two individuals are you more persuaded to hire? The first statement sure sounds fancy. There are a lot of interesting technologies mentioned and big words like ‘implemented’ and ‘optimized’ and ‘analytical capabilities.’ But for a hiring manager, this one falls flat. Can you see why? It’s because it doesn’t pass the litmus test of our one, all-important, all-guiding rule – it doesn’t tell (directly) how you solve the hiring managers problems.
And we must be direct in these matters.
On to the second statement. To a hiring manager, this one shines. It’s brilliant. Why? Because they can directly see what problem you solved. You saved the company $200,000 dollars. Hero! That’s the kind of person I want to hire.
But you didn’t stop there. Oh no. Lest the hiring manager doubt your statement, you then proceeding to tell them how you did it. You said, “This is the problem I solved, and this is how I did it. And I’ll do the same thing for you.”
Bingo. You’re in.

Element #2: Skill Words

This one is for the recruiters. Put skill words in your resume, load it up to a few job sites like Monster and Career Builder, and sit back and wait for the phone to start ringing. In the field of analytics, I guarantee it will.
Recruiters everywhere are trying to find people that fit into the hard-to-fill analytics positions their clients are asking them for. They are searching desperately for anyone that can do ‘web analytics’ or ‘predictive modeling’ or ‘data visualization.’
Another level down, they are looking for people who have skills with specific (and very important) tools that are widely recognized in the industry. Here are a few of them:
– Tableau (data visualization)
– Omniture, of Adobe, SiteCatalyst (Web Analytics)
– Google Analytics (Web Analytics)
– SAS and SPSS (Statistics and modeling software)
– R (Open source Statistical language)
– Python (Open source programming language good for data handling and predictive modeling)
– SQL (Programming language used to communicate with databases)
– Eloqua (Email marketing system)
– Salesforce (Widely used CRM)
The more of these you can put on your resume, the more likely a recruiter is to find you. If you have them all, get ready for the phone to ring off the hook.

Element #3: Professional Authority

People need to know they can trust you. That you’re not pulling a fast one on them. In a word, you need some street cred.
This one is basic, but important. Education, certifications, honors. Put them on the resume. Got your degree in something other than analytics? Get a certification, take a class, or join an association that deals with analytics. This shows you are interested in and involved in the space. (In fact, this is a really good idea even if you have a degree in a related field.

Learn the other elements of getting hired in analytics today.

Get a Job in Marketing Analytics (Post 4): Clear Communication

Alright, you’re doing well. You understand the business questions and have the technical skills to figure out the answers. Now comes the part most analytical professionals (unfortunately) trip over.
The work is not done until it has been successfully communicated to the people in the organization who need to understand it. Please note the deliberate use of the term “successfully”. Just because someone throws up a few hundred flashy charts and data tables doesn’t mean anything useful was communicated. In fact, it probably means that nothing useful was communicated.
Good communication is tricky, especially in an analytics context. But it is so, so, so, so, so, so, SO, SO, SO very critically important. Please don’t underestimate how important this one is. It’s the difference between a brilliant, fulfilling, exiting career and an unsuccessful, marginal, and discouraging existence.

Comic Source:

Comic Source:

While there is a lot that can be said about good communication in analytics, here is the one rule that will get you closest to communicating brilliantly.
Communication Rule #1: Show your analysis to someone who cares. Listen to their feedback, humbly. Change your presentation so it makes sense to them.
Do this one thing, and you will become an awesome communicator of analytical insights. Nothing is sacred in your presentation. If it doesn’t make sense or add to the point, change it. Or better yet, take it out all together. No one cares how much work it took you or how clever your analysis was. Just tell them what they need to know. Only keep the parts they get excited about.

Next time we’ll discuss the first of the five important channels – Your Resume. Or you can get the whole story by downloading the ebook here.

Getting a Career in Analytics (Post 3): Business Vision

Some people call it business acumen. Some people call it seeing the big picture. Some people call it focusing on the bottom line.
Semantics aside, what it means is this – you understand and can solve business problems.
Here are some good ones. Why is revenue down? Why are people unsubscribing from our newsletter? How do we persuade more customers that our products are the best thing that will ever happen to them?
These are questions business people ask. And these are questions business people need answers to. Everything you do from a technical standpoint is going to be within the context of a business question or business problem. That’s where you are going to live.

Pro Tip #1: Search for case studies in the industry you are most interested in. They will detail the business need, the solution, and how they arrived at the solution. Read up on several of these to get a feel for the industry. Focus on case studies dealing with analytics.

Pro Tip #2: Research a real company online in the industry you are interested in. Think up questions and concerns they may have and how to answer them. Contact any friends, friends of friends, friends of neighbors, or friends you meet at the dog park while walking your husky that work in the industry and ask them what kinds of issues they face. If you listen sincerely, they will talk.

Read more in the free ebook.

Artist Quote

Starting a Career in Analytcs (Post 2): Technical Skill

This is the gritty, mechanical side of the job. It’s where you get your hands dirty. It’s where you get things done that other people ascribe to magic.
And the best part about it is that most (if not all) of this can be learned for free. You don’t have to get a degree in analytics (although we’re not downplaying how awesome that is) to have the skills. You just have to know where to look.
Below is a short list of skills you need to know. They take some time and effort, but they are all attainable and can be learned a la your convenience. There are many, many online resources.
Mix and match these according to your specific interests, but as a whole you should be able to:
– Write SQL code
– Create predictive models (Python, R, and SAS are big names here)
– Work with Google Analytics
– Do Data Visualization (Tableau is hands down the best in the field)
– Work Excel like a boss
There are of course other skills you can pursue that will elevate your technical prowess to an even higher level. But these five are the basics. And if you can do them, you’re already fixing to be a top tier analytics professional.

We’ll go over business vision in our next post. Or, download the entire ebook now for free!

Why a Career in Marketing Analytics is Remarkable and How to Get There (Post 1)

If you are reading this, you probably already know why the field of analytics is so great. But let’s take a quick moment to dwell on why this career choice may just be the peak of the mountain. Here are a few of my reasons:
You get to help people in ways no one else can help them
You are vital to the success of whatever organization you work for
You get to answer very interesting questions, often in clever ways
You get to learn about everything
You will never be without love, respect, or a good job (Unless you’re a jerk. So don’t be)

If you don’t believe me, have a look at this data from Forbes. Writing in 2013, they saw a jump in marketing analytics hires of 67%. And it’s just going to keep going up.

Sound awesome? It is.
This is the first in a series of brief posts that will give you a framework to start your career in analytics. Let’s get to it.

The Five Channels

You can get into the field of analytics. Anyone can. It takes time and effort, of course. A position in a field this awesome doesn’t just fall from the sky into your backyard.
But if you’re ready to put in the work, let’s go over some guideposts to help you get there as quickly and successfully as possible. We call them the Five Channels, because, well, there are five of them. And they’re important. We’ll discuss each of these in depth later. They are:
Your Resume
Your LinkedIn Profile
Your Blog (Yes, you need one of these. But don’t be afraid, it’s not that hard.)
The Interview
The Little Something Extra

The Three Skills

Before we jump into the details of the Five Channels, it’s important to also mention the Three Skills.
These are the core. The center. The essence of an analytical professional’s being.
They are what makes you brilliant at what you do.
They are the following:
Technical Skill
Business Vision
Vibrant, Emotional, and Confident Communication
We’ll begin a discussion of them in tomorrow’s post.

Learn the Technical Side of Analytics from these Free Resources

Technical skills in analytics are the magic behind the curtain. They are what produces the results. Even if you are mediocre at most of them, you’re better off than most marketers.

In order of importance, here are the skills you need to learn and the best (free) resources I have found to teach them to you. I’ve listed them in order of importance.


It shouldn’t be the main tool in your arsenal, but it’s still foundational. For some basic things Excel is still the best. Easy Excel has a pretty good data analysis tutorial.


The w3schools’s tutorial is excellent. Basic and to the point.

Google Analytics

Google does a brilliant job here with tutorials. Start out with their digital analytics courses, and then on to the Google Analytics Platform Fundamentals.

Data Visualization

Tableau is hands down the easiest way to get visual insights from data. Learn it. They have free tutorials and a free product.

Predictive Analytics

I recommend Python (Download the Anaconda version). It’s free, there is a large user base, and it can pretty much do anything the big names like SAS and SPSS can do. Plus, some of the best data scientists in the world use Python for their algorithms, and they publish their code that you can look at and learn from on Kaggle.

If you don’t know Python, I recommend this free tutorial site.

If you already know Python, Sci-Kit Learn (with a tutorial) is the de facto place for predictive modeling. You’ll also probably want to get acquainted with Pandas to help you easily manipulate data.