Easton Analytics

Today's data visualization tool is Raw.  An interesting choice of names for a not so raw experience designing easy to make, sophisticated-looking graphs. 4.   Raw Pitch:   Raw is an open-source visualization 'framework' designed to make visualizing complex data easy and accessible for all. Review:   Useful for smaller, complex, but definitely not big data sets as the content must all be  copied and pasted into the platform's excel-style interface.  That said, it caters to the less tech-savvy visualization geeks offering an easy drag and drop interface to produce beautiful 3D.js-based graphics.  

Charts.js is today's featured data visualization tool.  I won't lie, I am not sure how much coding is involved so I may not be to produce graphs with Charts.js, but we shall see!!  To be continued... 3.   Charts.js   Pitch :  Javascript charting for designers and developers. Review :  Charts.js is open-source charting code that provides 8 categories of charts.  While visually simply, Charts.js allows interactivity for the user to mouse over and identify and understand data points and events.   This functionality is great for in-depth exploration by the user, like you would expect in an in-depth digital magazine case study or as part of a museum kiosk feature.

Today's data visualization tool  is Data Hero. 2.   Data Hero . Pitch : The fastest, easiest way to understand your data. Review :  Data Hero is a cloud app which can connect with a variety of tools, such as Hubspot, Stripe, and Salesforce, to access and consolidate important data, providing recommended charts appropriate for each data type, and automatic updating or each report. It features a drag and drop interface to simplify user experience.  Given their ad video's techno music soundtrack I'm going to go out on a limb and say its geared towards the less tech savvy digital marketer.   Several of the features appear to overlap with Google Analytics tools including e-commerce tracking, customer engagement, and sight performance monitoring.   Data Hero is designed to support marketers, agencies, sales, but is not also being marketed t to financial services and education as well.

Tableau may be the hottest trending data visualization tool, but its certainly not the only game in town.  Over the next few days I'm going to highlight different visualizations tools on the market and will circle back in the coming day with samples produced using each tool. Today's feature is Plotly. 1. Plotly . Pitch : Plotly pitches itself as open source visualization libraries for Python, R, Javascript, Shiny, and Dash, allowing users to create stunning and informative graphics and easily sharable dashboards. Review :  They claim to be geared for data scientist primarily, although accessible for non-coders as well.  As a key point of differentiation, the tool is collaboration-focused so that disparate teams can all access the tool and data through their 100% online platform.  Plotly also uses web-native graphics, which they point out are also employed by The New York Times. The graphs are beautiful and dynamic in 3D and colorfully nuanced using D3.js (javascript) charts

I recently read The Economists's March 2017 article, " A Digital Revolution in Health Care is Speeding Up. "   Several of the developments they address have me excited about this field for the first time.   We are approaching a new frontier of better outcomes, healthier lives, and I would anticipate, greater personal responsibility.  Coincidentally, the government's actions to reduce our mandated healthcare benefits are likely to accelerate consumer use of preventative care resources in this category, simply out of necessity.  This will be a boon for the makers of Fitbit and other wearable health technology providers as well as those big data gatherers who leverage the feedback from these systems and related data sources.  Overall, the new digital tools and firms outlined in the article are intended to empower patients and payers alike, above traditional service providers, thereby giving customers a substantive, information-driven approach to supporting their individu

The above image is a list of 'a handful' of companies working in the Marketing Technology space. Only about 8% of them are very large, but as you will notice, a slew of them are in Data.  Within Data, there are always new niche players coming up with neat visualizations tools. However, I will address just a few of the large players today. TABLEAU Much has been said about the benefits of Tableau as a data visualization tool, particularly for large datasets.  It is certainly a wonderful software once you learn to use it, the drag and drop interface makes it super easy to handle.  Unlike basic Excel, Tableau can work with extremely large amounts of data, and can analyze that data very quickly into highly interactive graphs, charts, and geographic visualizations.  The availability of heat mapping and color coding to illustrate vast amounts of data across a geography is perhaps one of my favorite features. Notably, Tableau doesn't work with unstructured data well, as oth

Ultimately the end game of a marketer using data is to monetize that data.  Of course there are more or less direct methods to make a case using data; they vary in degree of complexity and investment to acquire.  They might also require teaming up with a data analyst or data scientist.  The most important point to remember is that you have to know what question you're trying to answer, you can just browse and expect to get a simple solution.  There are almost always a confluence of factors either determining or related to the problem at hand and determining causation vs. relation is an important human-level of the analysis the requires logic and experience with the subject matter. Here is a list of common ways to monetize data. 1.  Data can be used for predictive analysis to determine when customers are most likely to be shopping and on which of their devices. 2. Data can be used to segment customers by what types of products they are most likely to purchase.  Companies can d

In 1790 the Pennsylvania state constitution called for publicly funded education for poor students.  The assumption was that wealthier families would fund their own children's education, and that it would be superior to the public offering.  A decade before that Thomas Jefferson had proposed a two track education system, one that provided different tracks for the "laborers and the learned,"  which would be designed, in Jefferson's own words, to "rake a few geniuses from the rubbish."  Mind you this was in the time of slavery and indentured servitude, so the assumption that students had finite and largely low-level capabilities and that this might warrant their station in life wasn't the least bit controversial.  Coincidentally, this aligned with the prejudice that only land owners be allowed a vote in the new world.  It was only with the eventual adoption of publicly-funded education across the country and in the 1940's the introduction of compulsory

I really enjoyed reading Kaitlyn Nastro's blog post this week entitled, " Is Data that Great? " Kaitlyn challenges the authority of algorithms as they are increasingly applied in modern life, particularly to business situations.  She points out that Big Data comes down to numbers, and "sometimes numbers are wrong, sometimes numbers don't tell a story, or provide reason."  In other words, using algorithms can result in recommendations that don't jive with human judgment or that result in abject error. We cannot forget that algorithms are made by man.  Which brings up another interesting point, and my reason for blogging on this topic as well.  What happens when all of our latest technological breakthroughs are based on a methodology that is modeled after man's vision of the world, as well as, at least initially, our way of thinking?  Do we produce something that is way smarter than us but still deeply flawed, as we are? How will we know when to let

My father went into the ER a few weeks ago.  I later learned its better to go to a teaching hospital for unusual symptoms, and a local hospital for run of the mill stuff where an ER doctor might do those procedures several times a day.  But how, when Dad appears to have sudden onset dementia, or a stroke, are you supposed to know that going in the door, and why aren't hospitals referring you to ensure the best care when they come across something outside their ability to immediately diagnose and treat? After a service and diagnosis failure at the first hospital, and an inability to do further testing within 36hrs, my parents headed home.  It took nearly 24hrs for us to convince them to go to an academic hospital (and to learn that that'd be a good next step ourselves), and for the next round of testing to begin.  There was no major stroke, or dementia, but after another 24-36hrs there was a perfectly reasonable cascade effect that resulted in blood poisoning, as a result of o

There's been a lot of talk about AI recently, and I'll admit it, I'm officially caught up in it, and shamelessly so.  A few recent examples, and I will have to come back to add the third because it is suddenly slipping my mind: AI is being trained to write scripts, as it did recently based on  the Knight Rider sitcom.  The body of scripts from Knight Rider was analyzed, and a new scripted based off of that, but written by an AI, was developed.  David Hasselhoff even collaborated on the project reading the lines for his character.  To read more about that, click  here .  Its nowhere near replacing the Hollywood Writer's Guild, but its possible that using AI could help them identify more salient themes to explore in their content ideation. Smart cars. Okay, I'll admit I'm not that interested as a consumer. I like driving too much. That said, they are an ideal solution for elderly folks who are a growing portion of the population. Now, these may not seem li

Deep pockets come in handy once again. On April 28th Ikea's external innovation lab, called Space10, launched a consumer survey online and at locations in Barcelona, to discover what people are thinking about artificial intelligence.  The results are sure to guide not only Ikea's future product innovations, in-store shopping experiences, external business investments, but also perhaps 'smart furniture' advances for the industry as a whole. The survey is a rather creative, and academic approach to online consumer research.  It is introduced with a set of conceptual frameworks for AI that we are already familiar with today, but that most consumers have little personal experience with. The consumer is is asked to speculate on their own future preferences.   What would you want from AI?  Human personality, guidance on how to live or do things, robotic personality, male/female gender identification, what type of attitude,  do you want the system to grow with you, and mim

Boston-based venture capitalist, Rudina Seseri, is the founder of Glasswing Ventures, and lucky for me, a close friend from my undergrad days.  Rudina has spend her entire career working in or around the tech industry, beginning with a stint with CSFB's Tech investment banking business under Frank Quattrone, (the famous, and then infamous tech investment banker,) followed by an MBA at HBS, and an managerial role at Microsoft.  From there she entered the VC world, first working for one VC and then starting her own. Click hear to listen to an interview with Rudina at a UK tech conference this week:   ow.ly/z1mh30b19MU   Rudina and her host are discussing the future of AI and what VC firms like her own want to see.  Rudina's firm focus solely on AI and machine learning-related businesses. One of the catch phrases the tech industry types likes to use when identifying good ideas and investment opportunities is "disruption."  AI was first invented in the 1950's

For the last three weeks I have been exploring Google Cloud and the GCloud ML (Machine Learning Engine) via a video labeling competition on Kaggle.  I thought I had no expectations other than that it would require me to apply the techniques learned in our Consumer Decision-Making class in a more depth project, and given this was a video classification endeavor there'd be some significant learning.  In fact, one of my expectations, which I took for granted, was that there would be some type of graphic user interface, a la SAS Enterprise Miner.  Initially I expected it to be Google's Tensorboard software, a modeling tool, which so far as I have experienced is not manipulatable, though it appears to be marketed as such. Maybe that comes later in the game. So far I have simply completed the training, but am stuck at building a model.  So here are my learnings for marketers wishing to try this out on their own. 1. Talk about a steep learning curve.  A solid knowledge of Python is

Anyone who is paying half a mind to politics has heard how Obama leveraged social media and business analytics to win the 2008 election.  Set aside, if you will, my admiration for Barack Obama the person, and take note of this very forward-thinking endeavor.  His campaign out-posted John McCain's campaign by 3:1 on social media. By pulling in data from communications channels Obama was able to leverage a reliable method of polling while simultaneously building a database of millions of passionate followers at a relatively early stage in the digital BI game.  I have no qualms with John McCain, but Obama was able to leverage the progressive youth of this nation to win the campaign, and that was not easily or  successfully repeated at a pivotal level by Hillary Clinton, despite what would seem like her obvious political and operational advantages and four years of preparation and hind-sighting.  Does that mean that at the end of the day it has less to do with analytics and social medi

Depending on which survey you read, the skills that you need as a digital marketer are either concrete skill areas (SEO, SMO, Google Analytics, etc), behavioral, or a mix of both.  Here are a few lists I'v run across recently. STANDARD LIST OF DIGITAL MARKETING SKILL AREAS 1. SEO 2. Pay-Per-Click 3.  Mobile 4.  Email Marketing 5. Social Media 6. Content Management 7.  Analytics (*Courtesy of the American Marketing Association) I have deleted their descriptions, which were pretty straight forward, but these field specialties seem rather expected, no? Now compare those points from America's leading marketing association, to this list, summarized from a Mashable survey of experts working in the field. VALUABLE SKILLS FOR DIGITAL MARKETERS ACCORDING TO IN-THE-KNOW EXPERTS 1. Paid Social Advertising Expertise - Be able to develop campaigns and segment those campaigns with iterative customized creative, then run Facebook analytics and insights against those cam

There are a number of analytics providers who have created business intelligence (BI) and analytics platforms.  Some of the big names are IBM's  Watson, Microsoft's Power BI, Tableau, SAS, and dozens of other smaller players.  Business Intelligence tools offer interactive, visually-compelling dashboards of real time or near real-time data accessible from numerous sources and data storage environments.  The tools, which can have a desktop or cloud setting, allow for companies to be FAST and FLEXIBLE in developing and sharing business insights across all types of devices and operating systems, engaging more people than ever within the organization in gathering insights and analysis.  Some companies build one-size-fits-all tools while others have developed for niche use and focus on out-performing in a specific category of the BI market.  As with all new and high-growth markets, the competition for users is stiff and large companies are beginning to buy small businesses in areas

While preparing for this week's long blog, I downloaded a white paper Tableau published entitled, " The Top Business Intelligence Trends for 2017 ."  According to their report, LinkedIn has listed business intelligence skills as one of the hottest skills to get hired for 2016; and beginning in 2017 data analytics is predicted to be a mandatory core competency for all types of professionals.  As much as this may be true as a trending "necessity" for business success (and I acknowledge I have been out of the workforce for a while, which may color my perspective) but I think they are overly optimistic about businesses and workers adaptive capacity.  Here's why. Change is hard and busy professionals, particularly senior ones, are going to have a hard time embracing the hands-on use of this data.  These tools, whether they are Tableau, Watson, SAS,  Microsoft's Power BI, or anything else worth its salt, are a really big deal not just as a tool for how a busin

We've not yet gotten to the skills necessary for being a Digital Marketing Analyst, and I have a feeling that many of you who have spent a large portion of your marketing careers honing your talents for salesmanship and selling big idea campaigns and product concepts, are starting to hyperventilated at how quickly technology is changing your job, and how your work measured. Digital marketing tools are soooo faarrrr away from your specialization that you are wondering how you can make it from here to retirement without having to learn said skills. Or perhaps you'll accept only having to gain a vague command of what digital marketers and digital marketing tools do, so that you don't make a fool of yourself in the board room.  You might even understand enough to place requests with IT for interesting types of data that you've always wished you could know.  Maybe this sounds like you? I'm certain I've had a few bosses that were wired for this outlook.   It is pr

I'm going to be honest with you.  This is a 2-part post about what skills Data Scientists and Digital Analysts need.  Now, I've never worked as either so none of the line items here are informed by my own experience, so you be the judge.  What I can say is that from all of the people I've talked to, and articles I've read, digital analysis, or data science if you are on the more technical side, are rapidly evolving fields.  If you are the type of person who wants to cram for 2-7 years and remain thereafter an expert in your field without constant continued personal learning, swipe right, these roles aren't for you.  I, on the other hand, spent seven years dedicating far, far too much time to coming up with language and pitches that were all essentially the same, selling beauty, luxury, and a vacuous fascination with sparkly items designed to make people feel special.  I am beyond tired of the monotonous view on that treadmill.   So, bring on the learning!  And the c

My first job working in marketing was in 1999 for 3COM. I somehow landed a summer internship, one of about twelve awarded to students from my college by one of our older grads.  I don't remember her name, but she was able to swing getting several of us great paying jobs for the summer and it was an amazing experience overall.  Our 3COM office was at their Silicon Valley headquarters, and we got the full experience of living and traveling in the region, as well as getting to know the software and hardware engineers who defined the company's culture and of course built all their fun toys.  That role was like no other marketing role I've had since though.  The department I was assigned to made routers.  For the entirety of the summer I worked for a Marketing Manager who tasked me with updating the copy in a 3-5" thick brand manual, which was essentially a collection of do's and don't for marketing the product and updating the product's spec as they evolved,