This week, we’re sitting down with Tom Webster. And we’re talking…wait for it…NUMBERS. We all know-we are living in a data filled world. It’s everywhere, and the truth is, we can truly learn a lot from it. Tom is a professional at this precisely. He has nearly 20 years of experience researching consumer usage of technology, new media, and social networking, and is the principal author of a number of widely-cited studies, including The Social Habit, Twitter Users in America, and the co-author of The Infinite Dial, America’s longest-running research series on digital media consumption. He is also the co-author of The Mobile Commerce Revolution, and a popular keynote speaker on data and consumer insights. Take a listen below, let us know what you think!
Running time: 59:25
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What is the future of jobs that incorporate working with numbers and data? (7:09)
Increasingly, smart technologies such as AI are going to be taking these jobs. This work is rapidly becoming automated. Even the processes I work on throughout my work, I have been introduced to a ton of new technology that makes my job easier. This is great for me, because it allows more time for insights, which allows the deepest understanding of numbers.
What is the difference between aggregate data vs. individual data? Does aggregate data matter? (11:06)
Aggregate data says that there is a specific time, number of characters, etc that allow for the best success on social media.
The biggest problem is that aggregate data is not your data, but rather uses data dredging, in which you look at a big pile of data of others and what worked for them. This allows people to believe that the best time to post is at 12:00 on a Tuesday, for example.
However, the best time for YOU to post is when YOUR followers are online, which is probably not at the exact moment that other people’s followers were online when they posted a successful campaign or whatever it is.
The only way to successfully do this is to do your own research. Find out when your followers and customers are engaging with you, so that you can grow your competitive advantage.
So, what do you do for a living? (13:51)
I work with numbers. More specifically, I work with the aggregate data we talked about to see how people are behaving. We release them in surveys and graphs etc.
Ultimately, a client comes to me with a problem and I help them solve those problems using numbers.
Let’s make a scenario. How do you research the data that best helps and represents a client that you are working for? (17:20)
First, start with the question: What is the problem you are trying to solve?
There are three types of research I can do for a client:
- How am I doing? This is looking at entire landscape and seeing your success rates, as an individual company and also when compared to competitors.
- What do I do now based on that data? This comes after recognizing the problem, and planning the next steps. It is the research designed to help these problems.
- What can do next? This is solution based, often involving something that hasn’t been done before. In this question, I work to see what motivates this business, I hope to reveal their human experience working within this business to see what they truly need to solve the problem. This could mean releasing a new product, etc.
What are things to consider when performing research? (21:59)
- Are you asking the right questions?
- Are you asking the right questions to the right people?
- Are you doing the right things to ask those questions?
- Do you have the right tools for the job?
- Do you know your audience?
- Do you know how to best reach them?
How much of the data out there is accurate enough to use? (24:08)
Most data out there isn’t terrible, but rather, it is just reported wrong. People often report it in ways that look to benefit their organization. There are many problems that can arise from this.
- Not using and showing variables correctly. This is known as non-response data.
- Failure to account for those who maintain light internet use. 1/3 of people use it for less than a hour a day. This results in an under-representation in online survey.
How has the current technology landscape, in which bots are extremely prevalent, affected by this data? Can we trust the data out there in today’s world? (30:57)
I do not use social media media for anything quantitative. I may get language usage and ideas data from it, but that is all. Rather, I use sampling. When used correctly, the small pool of samples can tell you all you need to know from the huge pool of data. So, in this case, something such as bots would not have as large as an effect.
How do you get the best data? (33:50)
Being willing to take those pains of GETTING the best data depending on what the client needs. If they need deeper insight, we need to be prepared. Hold experiments, provide surveys, whatever you need to do. Whatever allows for a single source of data is extremely valuable, depending on the actual business goals you are working with. Get to the right people, and ask the right questions.
How do you compensate those who provide data through experiments and survey’s? (36:29)
The form of compensation depends on the organization itself. For example, a B2B company would need a worthy compensation to make it worth it to people. However, not every successful data will require actual monetary compensation to each person. This could be a service, a donation, whatever.
What is regression analysis? (40:20)
Regression analysis 101, here! It’s simple, really. You take a variable. Let’s say the variable is Sales. Then, you look at all the other variables that affect it. Let’s say these variables are temperature, weather, traffic, employees who work there, etc. So now you have all these samples of data. Basically, regression analysis tells you how much the variants of each of the variables contributed to the variable in which you are measuring. So clearly, it is very beneficial when studying data.
What is a pivot table? (42:54)
Any piece of data can interact with any other piece of data, which will change the insight depending on what you are comparing. A pivot table allows you to see and understand all of this overlapping data much easier. It requires a lot of trial and error within this process.
One Book Everyone Should Read (47:30)
Thinking Fast and Slow, Daniel Condiment
One Podcast Everyone Should Listen to (48:57)
One Show or Movie Everyone Should Watch (52:04)
One Lesson you Wish you Learned Earlier in your Career (53:53)
Understanding how to work within a team.
Most important skill of the future (55:05)
Knowing how to make something by hand.
One thing that everyone listening to this should go and do today? (55:40)
Say something kind to someone.
CONNECT WITH TOM
CONNECT WITH JEFF
- Email Jeff
- @JGibbard on Twitter
- Jeff on Facebook
- Jeff on Linkedin (make sure to introduce yourself)
- Jeff on Instagram
- Jeff on Snapchat
SPECIAL THANKS TO
Ray, our Audio Engineer.
Thanks for cleaning up our voices and adding all that sexy production value.
Maria, our Intern.
Thanks for providing the show notes for today’s episode.