Disrupting Hollywood Paradigms with Analytics

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On April 4th, we had the pleasure of hosting Matt Marolda, Chief Analytics Officer with Legendary Entertainment at the monthly L.A. Marketing Analytics Group.  The event is hosted by eSage Group.

At our event, Matt presented on Disrupting Hollywood Paradigms with Analytics.  We were treated with some very interesting and thought provoking innovations that Matt and his team at Legendary Entertainment are working on to uncover powerful insights about mainstream box office audiences in the US and worldwide.  This insightful information helps inform marketing tactics and overall production investment strategies.

side bar for mayMatt and his Applied Analytics team are tasked with informing several key components of the movie making and marketing process.

The following is a list of the key discussion points and learnings from Matt’s presentation.

  • Informing Creative: Evaluate movie concepts, cast, themes and fan base long before a single dollar is spent on movie production.
  • Transforming Marketing: Use analytics to identify, understand, reach, and persuade individuals to watch a particular movie.
  • Understanding People, Content, Social and Conversation: Create a virtuous feedback loop where these four inputs are integrated into the overall marketing process to provide a continuously improving understanding of your audience over time.
  • Identify Varying Degrees of Persuadable People: Identify three clusters of persuadable personas with varying degrees of predictability with regards to convincing them to attend a particular movie.
  • Innovative Experimentation that Yields Big Wins: Movies that aren’t positively received in one part of the world may perform well in other regions. Use experimentation to test market acceptance of a particular movie in other regions before making further marketing investments.

Read on to hear more about how Matt and his team are shaking apart the old Hollywood Paradigms and creating a truly data-driven movie making environment at Legendary.


Full Article


Olegendary grey logo.pngn April 4th, at the monthly L.A. Marketing Analytics Group which is hosted by eSage Group, we had the pleasure of hosting Matt Marolda, Chief Analytics Officer at Legendary Entertainment. At the event, Matt presented on Disrupting Hollywood Paradigms with Analytics and we were treated with some very interesting and thought provoking innovations that Matt and his team are working on at Legendary to uncover insights about the mainstream box office audience in the US and worldwide.

It is known that Hollywood has many marketing paradigms that have been well entrenched for decades, some good, others beg to be disrupted. One of those stale marketing tenets that are being reevaluated and shifted to something more useful is how Hollywood has been segmenting the market using the often cited four quadrants: by male, female, over 25, and under 25; totaling 4 groups of 80 million people in the US, which is probably one of the crudest ways to look at the marketplace. Legendary is changing this old practice by looking at ways to see an audience in a much more granular way by micro segmenting this model into 80 million groups of 4, give or take – which seems daunting. But if you consider the top down leadership effort at Legendary to drive a culture of data driven marketing, it becomes more realistic. Two key efforts at Legendary that Matt and his team have been driving include Informing Creative and Transforming Marketing through applied analytics.

Informing Creative: All movie studios must decide on what creative movie concept, cast, and theme should be green-lighted, and which fan base should be targeted long before a single dollar is spent on making the movie. For much of the entertainment industry’s history scripts have been written and submitted, discussed and debated, picked up and dropped. This process includes top level executives deciding on whether the movie is going to be viable, profitable, and on brand for the studio.

Many of those decisions in the past were made by gut instinct, and then hope, prayer, chanting and the burning of incense was involved (at least in my version of this). With the advent of data collection and analytics being injected into the creative decision process, decision makers are shifting to a more data-driven approach when deciding to make a film. Present day studio brass at Legendary are now utilizing analytics (by way of Matt’s Applied Analytics Team) to evaluate movie concepts, the cast, screen fans ahead of time, test the theme, and they even look at sequel viability in order to inform the creative process and uncover the potential ROI in a very predictive way. This includes looking deeply at People, Content, Social and Conversation which I’ll talk more about in a bit. Legendary Entertainment CEO and visionary, Thomas Tull sought a better way when he launched the company in 2000.  As of 2017 Tull is no longer CEO, but his decision to hire Matt Marolda in 2013 to take Money Ball to Hollywood remains firmly intact.

Transform Marketing: Legendary shifted to an internal analytics team tasked with altering the marketing process from an older model sadly referred to as spray and pray where marketing dollars are spent in volume to reach all people with the hope that they will show up at box office. The paradigm shift is towards a more targeted approach that seeks to identify, understand, reach, and persuade individuals. Beyond that goal is the effort to reduce marketing spend by 20% through the strategic targeting of specific audience segments. That reduction in marketing spend directly affects the bottom line of movies on a global scale. Legendary is doing this is by maintaining an analytics team comprised of three groups: The Quantitative Group, The Development Group and the Delivery Group.

It’s the Quantitative team’s job to tap tons of data and apply it to the movie making and marketing processes directly using analytics. The Development team is tasked with integrating complex data feeds rapidly, turning the models of the Quant team into software, building high speed querying to allow iteration and refinement, and launching media feeds through API’s.  Finally, it is the Delivery team’s job to execute media buys on all digital platforms, where for Legendary, media agencies were unable to deliver at the speed and scale that is required to be competitive in this fast-moving effort to turn insights into marketing action that targets segments uncovered earlier in this process.

Successful marketing analytics teams everywhere strive to experiment, learn, “fail” fast, and reiterate the ongoing process in an unending feedback loop. This agile approach to data driven marketing continues to prove that trying things that might have failed in the past, or those that weren’t ever tried, can still yield big wins. This “panning for gold” approach either yields an answer confirming that one consumer messaging approach or another did not work, or in other cases it is uncovering novel and successful messaging that would not have been conceived of otherwise. Therein lies the paradigm shift from overspending and gut instinct marketing on a grand scale, to the highly targeted and strategic approach that not only saves marketing dollars, but imparts analytics that allow organizations to make their current marketing spend far more productive.

side bar for mayPeople, Content, Social & Conversation Looking at how competitive and successful movie companies like Legendary Entertainment approach data collection and the insights that are surfaced is a great example of how to stay competitive in any marketplace. This innovative approach to analytics is apparent in Matt’s Applied Analytics team who uses a virtuous cycle where four specific areas of data are integrated in unique ways. They collect and analyze information on People, Social, Content, and Conversation.

 

  • People Information: Includes 1.5 billion email addresses, 200 million households with PII (Personally Identifiable information) and hundreds of other attributes per person sourced from a multitude of available data. The Applied Analytics team at Legendary has curated this data set internally to enable them to identify, reach, understand, and persuade people.
  • Content Information: Includes box office data by individual theater for all movies from 2007, all US based advertising since 2007, meta data by second for movies from the 80’s to present day that identify actors in each scene, topic of conversation, tone & tenor of background music. These pieces of information are all crucial for comp’ing and modeling in the property evaluation process – which determines properties to buy, which movies to make, and which actors will be in them.
  • Social Media Information: Includes feeds from 500 million Twitter profiles and billions of tweets, 100 million Facebook profiles, all of Reddit, all of Wikipedia, plus thousands of News Sites and Blogs are scoured, collected and stored for insights.
  • Conversation Information: Includes social interactions by geography, plus extensive analysis on text and images using traditional and innovative techniques to help inform movie makers and marketers. This data helps Legendary understand current trends, what people are saying about particular movies along with their associated sentiment.

Using tools to analyze People, Content, Social and Conversation have helped Legendary build audience profiles and create hundreds of microsegments, identify key persuadable points and produce detailed, actionable insights. Acting on this data by matching profiles to key aspects of a movie surfaced from movie meta data informs Legendary on what movie to promote and to which persuadable audience. Changes of intent are also measured and creative actionable insights emerge at a rate of over 50 per movie, per week. This analytics ecosystem which integrates data, analytics, and campaigns, along with deep API integration allows for scale execution, sophisticated reporting and continual optimization.

Varying Degrees of Persuadable People: When Trying to identify persuadable sets of personas, Legendary looks at three clusters of people who hold varying degrees of predictability with respect to the ability to convince them to attend a particular movie.

First, there are folks that have been engaging with a property since childhood. Movies like Godzilla, King Kong and Warcraft have a historically long-standing culture of followers. Legendary seeks to turn those people into active evangelists. Marketing to them does not require a high-dollar spend because of their inherent affinity for the subject matter. Simply advertising key points like hints at trailers to be dropped and the dates of movie release are all that this group needs. The marketing effort is just to “stoke the flame” for this group.

Another cluster of people is identified as the “your mom” segment.  With this segment Legendary understands that there are just certain movies that they will not attend.  So there is no need to spend marketing dollars on this group when marketing a certain genre of movies.  Legendary will save these marketing dollars for other groups that are more apt to engage.

The third identifiable cluster is defined as the “people in the middle.” This group, when served the right creative at the right time will change their mind and their opinion of the film. In May of 2014 Legendary ran some testing on the Godzilla release. They found, unexpectedly that women ages 24 to 36 were identified as persuadable. This was a key insight. Legendary didn’t think this segment would be a viable target when they were whiteboarding their marketing effort. They then used analytics to design the movie trailer through insights uncovered about this new segment. The insights uncovered showed them that they needed to emphasize the conspiracy theory in the Godzilla plot rather than the monster destroying the city. They also knew to emphasize Bryan Cranston who was fresh off Breaking Bad. The trailer they created resonated with women and they subsequently launched an extensive marketing campaign around this knowledge, while continuing to further optimize their marketing for these segments.  Uncovering surprising and unexplainable segments like this has proven to be extremely valuable.  Establishing a culture of experimentation and building feedback loops into your strategy allows for these kinds of powerful insights.  Once a new segment is identified, predictive models are built to identify who is likely to engage with particular content.  With propensity scores, Legendary can zero in on targets as they get closer to the release, whereas other studios tend to get more panicked and market to a broader audience.  Legendary can go narrower, targeting only the specific people they think will act to a particular marketing piece.  When thinking of the world on a more CPM basis this is a better way to go.  Plus, this can all be done at scale.  This same process works for blockbuster films or much smaller projects, with both receiving lift.  With this lather, rinse and repeat methodology, these efforts all continue to inform and allow for continual optimization. Data is collected on an ongoing basis and appended back into the database, so the system continuously learns what approaches work and which don’t.  The system is continuously getting smarter and providing ever greater ROI over time.

A Third Paradigm Shift: A third and final example of how Legendary is disrupting the old Hollywood paradigms can be seen in their effort around the release of Warcraft. The movie was tested in China, with data being collected on 8 different versions of the movie with hundreds of test subjects using biometric Fitbit-like devices to track heart rate, blood pressure, oxygen levels, and more. Also, iPad-like devices were used to capture facial expressions during the viewings.  These experiments provided information on how viewers were engaged with the movie in several ways.

This data ultimately revealed that a movie that was “panned” by the critics and dubbed awful in the United States would in fact resonate well with the Chinese audience.  The movie was launched globally and was a box office success in China grossing over $220 million.  This was a record in this geo and the movie ended up with total global revenue of over $433 million.

In Closing:  The analytics concepts being harnessed by the team at Legendary are innovative and cutting edge and might just prove to Hollywood once and for all that analytics are here to stay and not just a passing fad as some have said (as they were packing up their belongings and seeking a new line of work).  Those of us who seek deeper knowledge of our customers and processes in business know that if you aren’t competing with analytics, you’re not competition.

Many of the efforts at Legendary are reminiscent of the work we do at eSage Group. For large entertainment companies and several other verticals, we too help our customers obtain deeper insights through data integration and analytics. If your marketing organization is looking to migrate from the Spray and Pray digital marketing approach to a modern and efficient Marketing BI/Analytics infrastructure, we at eSage Group can assist in that process in a myriad of ways.  We help our clients integrate data from a multitude of various sales, marketing, partner and social channels, no matter the format of the data or the system it’s sourced from.  We design and build Marketing Analytics Data Warehouses, Data Lakes, Data Marts and connect newly integrated data to all your favorite reporting and analytics tools.  We are equally comfortable with on-prem and cloud based traditional data warehouse technologies such as Microsoft SQL Server, as well as most of the modern Big Data/Hadoop based platforms.

Our goal at eSage Group is to assure that marketing teams are obtaining useful and highly actionable insights from all internal and externally collected sales and marketing data. For more information on eSage Group and how we help our clients, please visit our website or email me directly.

Variety Big Data Summit 2016 and the Ubiquity of Data in all Things

By Rob Lawrence – Southern California Business Development Manager, eSage Group

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Attending the Variety Big Data Summit for three years in a row now has always been a rewarding and insightful endeavor for me. My understanding of the data landscape in entertainment, and really business in general, has grown exponentially over the years I’ve worked in business development for a data integration and business intelligence consultancy. What I’ve come to realize over the years is that I’ve witnessed the rise of a concept that really had already existed for a very long time: Big Data. I’ve seen the widespread adoption and use of Big Data (or at least the hope to be using it someday, in some cases). Reflecting on the things I learned at this last Summit earlier this month, it occurred to me that the ubiquity of Big Data is here, finally! Or has it always been here? OK, let’s explore what I mean.

Taking a look at the topics discussed at the day-long event is reminiscent of any collegiate marketing or business major’s syllabus for a given semester: “Explore data’s growing impact on media and entertainment spanning content creation, audience measurement, monetization, marketing, asset management and more.” Subtract the overall look at entertainment specifically, and what you have here is a study in data (information) for the purpose of creating, measuring, monetizing, marketing, and managing your business. Whatever business you are in, you either do these things better than your competition, or you fail. The deeper dive panel discussions at Summit were a good reminder that data is challenging the way business has been done in the past. We looked at important topics such as Reaching a Global Audience, Engaging Relevant Audiences, People-Based Marketing, Sports & Data, Privacy & Security, The New Video Economy, Data Science, and Data & Creativity. All topics that have profound effect on the entertainment and media business, and most should be equally as important to non-entertainment verticals. Data is ubiquitous and we’ve been collecting it for years. The sense I have is that businesses are just now beginning to realize the benefits of what we’ve been talking about since the inception of the Big Data movement, and going forward this journey will never really end.

One of the panel discussions at Summit struck me as a very important commentary on the benefits of using data to drive demand, engagement, and understanding of the customer journey: The Rise of People-Based Marketing. This topic is new only in the sense that we are beginning to bring all of the pieces of the puzzle together in marketing, and some new pieces of that puzzle have emerged. I liked what Sean Moran, Head of Marketing & Partner Solutions, at Viacom had to say regarding this: “It’s cliché to say that we’re in a more evolved state in marketing than ever in our history. We’ve talked about it for a long time, but before now it was never actualized. Such rapid exchange and pace of what data can be captured during a behavior revolution. It’s all coming together. We’re connecting in a targeted way in which the ability to get targeting and predictability at scale in TV and extending it to other platforms, so you can predict the consumer’s behavior by fusing data together through viewing, geo-location as well as purchase intent. Emotional connection plays into this as well. The excellence of data can only take you so far, you have to understand the emotional connection of consumers. Some are jumping on that, others see data as a way of sourcing up the currency that’s been happening since 50 years ago.” So, in theory, the ability to collect data and the ever increasing data points that are collectible are truly giving companies the opportunity to tap into the consumers’ emotional state at the most critical points along the customer journey. We might predict what the consumer is feeling before they realize what they are feeling. However, and to counterpoint this concept, I also liked what Andrew Appel, President and CEO at IRI had to say with regard to the fragmentation of all these data points: “Yet nobody really has the capability to do that (use the data with a level of sophistication), so while the fragmentation is exploding, the ability to get all those different data sets into one place (shopper data, media data, consumer data, context data, purchase intent, television viewing habits, exposure to advertising, etc.) at an individual level to effectively score each and every consumer in real time, on what will drive their behavior change, what you should use to target them, and ultimately measure whether or not it changed their behavior, is ever more difficult.” While I agree with Andrew that it is ever more difficult, I also believe companies are getting savvier at doing these things, and thus the journey to marketing analytics nirvana continues.

It wouldn’t be right for me to finish my post without talking about Mobile. Mobile in the sense that everyone is connected, everywhere they go, regardless of the device at the crux of the matter. This represents a very intriguing opportunity for businesses, and I suspect it will only continue to grow ever more intriguing as we get better at things like attribution, segmentation and personalization, and as technologies like VR begin to take hold. On that, I agree with Eric Smith, Industry Manager, US Entertainment, at Facebook, who said: “Facebook has embraced mobile for consumers. For consumers it is known that 1 out of 5 Mobile minutes spent is either on Facebook or Instagram. Facebook has a very personal connection with people as it creates 1.8 billion personalized experiences for people every month given their active user base. Mobile is one of the key doorways to personalization. These are big numbers, but that is how you get to scale. The scale of personalization. A couple of things Facebook has worked hard at are; a strategy that they’ve built for their Partners called Test Learn and Act, where we understand who was interested in their content or the game. A great example is with Ubisoft on a game they are launching in the Tom Clancy series. We understood with them that there are three really important segments within their user base (Why people want to purchase and play their games): there’s a group that’s really interested in the technology and strategy and gadgets and gizmos, there’s a group that is really into the adrenaline and competition, and there’s a group that’s just really fascinated by the open world play where they can go and explore a universe that is unlike the one we live in in real-time. So Facebook worked with Ubisoft to understand these audiences and then to build a creative doorway; a 5-second bit of content that they laid on top of the trailer for their game that really appealed to those segments. We showed a lot of the tech, gadgets and gizmos to that audience, and so forth. We saw 63% increase in Purchase Intent, amongst those audiences by properly segmenting and then speaking to them in the right creative language – we’ve applied that to movies as well. Sony (where Eric used to work) is now a client of Facebook’s. Working together on the Sony film: Money Monster, using this same strategy, they found that men 25 to 34, an audience they hadn’t expected to be interested, but very much was. So Facebook worked with Sony again to help create some creative that spoke to that audience, targeting clusters that would reach those men, 25 to 34. As a result, they found in the exit poles there was a strong demographic of them that actually went to the film. This is the Intersection of the Content and Mobile Marketing Personalization experience.” Well said, Eric. None of which could be done without the proper collection of data, not just from mobile, but from all of the other myriad places we are able to pull from, and those are only growing exponentially with new platforms, technologies, and ways to consume content. Each new form is representative of a whole new world of available data points around the customer journey: The Ubiquity of Data in All Things!

In conclusion I’d like to say that the Variety Big Data Summit 2016 was a relevant and successful event, as it has been in past years. I’d recommend anyone working in Entertainment, or in a business that is striving to be more Data Driven to attend. I’d also say that the attendees at this event each year prove to be highly engaged, many thought leaders in their own right, and thus the networking is a blast. From a “Big Data” perspective, it is clear to me that the use of data for all things in business has a very broad surface, which has only been slightly scratched. It’s an exciting time for marketers, content creators, and businesses who have honed a skill around experimenting with, and utilizing data in new and innovative ways. Now, can we get back to referring to the practice of collecting and harnessing data as something other than “Big Data”? Perhaps we just go back to calling it, regular old, good old-fashioned, DATA.

The Future of Enterprise Analytics

Over the last couple weeks since the 2016 Hadoop Summit in San Jose, eSage Group has been discussing the future of big data and enterprise analytics.  Quick note – Data is data and data is produced by everything, thus big data is really no longer an important term.

hspeopleeSage Group is specifically focused on the tidal wave of sales and marketing data that is being collected across all channels, to name a few:

  • Websites – Cross multiple sites, Clicks, Pathing, Unstructured web logs, Blogs
  • SEO –  Search Engine, Keywords, Placement, URL Structure, Website Optimization
  • Digital Advertising – Format, Placement, Size, Network
  • Social
    • Facebook – Multiple pages, Format (Video, Picture, GIF), Likes (now with emojis), Comments, Shares, Events, Promoted, Platform (mobile, tablet, PC) and now Facebook Live
    • Instagram – Picture vs Video, Follows, Likes, Comments, Reposts (via 3rd Party apps), LiketoKnow.it, Hashtags, Platform
    • Twitter – Likes, RT, Quoted RT, Promoted, Hashtags, Platform
    • SnapChat – Follows, Unique views, Story completions, Screenshots.  SnapChat to say the least is still the wild west as to what brands can do to engage and ultimately drive behavior.

Then we have Off-Line (Print, TV, Events,  etc). Partners. 3rd Party DataDon’t get me started on International Data. 

Tired yet?

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While sales and marketing organizations see the value of analytics, they are hindered by what is accessible from the agencies they work with and by the difficulty of accessing internal siloed data stored across functions within the marketing organization – this includes central corporate marketing, divisional/product groups, field marketing, product planning, market research and operations.

Marketers are hindered by access to the data and the simple issue of not knowing what data is being collected.  Wherever the data lies, it is often controlled by a few select people that service the marketers and don’t necessary know the value of the data they have collected.  Self-service and exploration is not possible yet.

Layer on top this the fact that agile marketing campaigns require real-time data (at least close real time) and accurate attribution/predictive analytics.

So, you can see there are a lot of challenges that face a marketing team, let alone the deployment of an enterprise analytics platform that can service the whole organization.

Now that I have outlined the business challenges, let’s look at what technologies were mentioned at the 2016 Hadoop Summit that are being developed to solve some of these issues.

  • Cloud, cloud, cloud– lots of data can be sent up, then actively used or sent to cold storage on or off prem.  All the big guys have the “best” cloud platform
  • Security – divisional and function roles, organization position, workflow
  • Self-Service tools – ease of data exploration, visualization, costs
  • Machine Learning and other predictive tools
  • Spark
  • Better technical tools to work with Hadoop, other analytics tools and data stores
  • And much more!  

Next post, we will focus on the technical challenges and tools that the eSage Group team is excited about.

Cheers! Tina

 

 

 

Seeking 4 mid/senior level engineers to work on a Cloud-based Big Data project

eSage Group is always on the lookout for talented developers at all levels.  We have worked hard to create a company culture of sharp, quick learning, hardworking professionals who enjoy being part of a winning team with high expectations.   As such, we hire self-motivated people with excellent technical abilities who also exhibit keen business acumen and a drive for customer satisfaction and solving our client’s business challenges.   We have quarterly profit sharing based on companywide goals, allowing everyone on the team to participate in and enjoy the rewards of our careful but consistently strong growth. We are currently looking to fill 4 openings to complete a team that will be working together on a large-scale “big data” deployment on AWS.

  1. Cloud-operations specialist who can design a distributed platform for analyzing terabytes of data using MapReduce, Hive, and Spark.
  2. Cloud-database engineer who can construct an enterprise caliber database architecture and schema for a high-performance Cloud-based platform that stores terabytes of data from several heterogeneous data sources.
  3. Mid/senior-level software developer with extensive experience in Java, who can write and deploy a variety of data processing algorithms using Hadoop.
  4. A technical business analyst who can translate business requirements into user stories and envision them through Tableau charts/reports.

1) Cloud-operations specialist: • Bachelor’s degree in Computer Science or related field; or, 4 years of IT work experience • Familiarity with open-source programming environments and tools (e.g., ant, maven, Eclipse) • Comfortable using the Linux operating system, and familiarity with command-line tools (e.g., awk, sed, grep, scp, ssh). • Experience working with Web/Cloud-based systems (e.g., AWS, REST) • Knowledge of database concepts, specifically, SQL syntax • Data warehouse architecture, modeling, profiling and integration experience • Comfortable using the command line (e.g., Bash), experience with systems deployment and maintenance (e.g., cron job scheduling, iptables) • Practical work experience designing and deploying large-scale Cloud-based solutions on AWS using EC2, EBS, and S3 • Working knowledge of one or more scripting languages (e.g., Perl, Python) • Experience using systems management infrastructure (e.g., LDAP, Kerberos, Active Directory) and deployment software (e.g., Puppet, Chef) • Programming ability in an OOP language (e.g., Java, C#, C++) is a plus 2) Cloud-database engineer: • Bachelor’s degree in Computer Science or related field; or, 4 years of IT work experience • Familiarity with open-source programming environments and tools (e.g., ant, maven, Eclipse) • Comfortable using the Linux operating system, and familiarity with command-line tools (e.g., awk, sed, grep, scp, ssh). • Experience working with Web/Cloud-based systems (e.g., AWS, REST) • Knowledge of database concepts, specifically, SQL syntax • Firm grasp of databases and distributed systems; expert knowledge of SQL (i.e., indexes, stored procedures, views, joins, SISS) • Extensive experience envisioning, designing, and deploying large-scale database systems both in traditional computational environments and in the Cloud • Ability to design complex data ETLs and database schemas • Desire to work with many heterogeneous terabyte-scale datasets to identify and extract Business Intelligence • Experience using multiple DBMS (e.g., MySQL, PostgreSQL, Oracle, SQL Server) • Work experience using Hive and NOSQL databases is a plus 3) Mid/senior-level software developer: • Bachelor’s degree in Computer Science or related field; or, 4 years of IT work experience • Familiarity with open-source programming environments and tools (e.g., ant, maven, Eclipse) • Comfortable using the Linux operating system, and familiarity with command-line tools (e.g., awk, sed, grep, scp, ssh). • Experience working with Web/Cloud-based systems (e.g., AWS, REST) • Knowledge of database concepts, specifically, SQL syntax • Excellent Java developer with knowledge of software design practices (e.g., OOP, design patterns) who writes sustainable programs and employs coding best practices • Ability to program, build, troubleshoot, and optimize new or existing Java programs • Several years development experience using both version control (e.g., SVN, Git) and build management systems (e.g., Ant, Maven) • Able to create and debug programs both within IDE environments and also on the command line • Working knowledge of Web development frameworks and distributed systems (e.g., Spring, REST APIs) • Experience using Hadoop ecosystem (e.g., MapReduce, Hive, Pig, Shark, Spark, Tez) to program, build, and deploy distributed data processing jobs • Programming ability in Scala is a plus 4) Technical Business Analyst: • Strong background in business intelligence • Minimum of 1 year using Tableau and Tableau server. • Able to work closely with cross-functional business groups to define reporting requirements and use-cases • Extensive experience manipulating data (e.g., data cubes, pivot tables, SSIS) • Passion for creating insight out of data and data investigation • Experience using R, Mahout, or Matlab is a plus Please send resumes to tinam (at) esagegroup (dot) com

What is the Internet of Things? Why should marketers care? RSVP Now to find out!

Internet of ThingsPlease join us in this lively evening event sponsored and organized by eSage Group with co-sponsors Pointmarc and Cloudera. Hear a panel of industry experts from the areas of Wearables, Home Security/Automation, and Automotive:

Duane Bedard from eSage Group, a thought leader in the marketing analytics space, will moderate a discussion delving into the Internet of Things, where are we today, what the future holds and how marketers can best be prepared to take advantage of it to improve effectiveness of marketing campaigns and develop new revenue streams.

The Learning Lounge is presented with PSAMA and DAA.

Details:

When: May 15, 2014 Time: 6:00pm – 9:00pm
Where: Club Sur 2109 First Avenue South SODO, just south of the Starbucks Center
Cost: $25 includes beverages (alcoholic and non) and appetizers Parking is free and readily available after 6pm on First and side streets.

RSVP Now IoT

 Check out the cool digs!

SUR Montage

DONT MISS IT!

 

Just announced! eSage Group’s Internet of Things Learning Lounge – May 15th

iot3A First-Hand Conversation on the Internet of Things

The Internet of Things will profoundly re-shape marketing. As objects in all corners of our lives become connected to the web what does it mean for brands and customers? To help provide insight, and a lively discussion, eSage Group and PSAMA has arranged a premium collection of senior-level thinkers from some of the area’s strongest brands, all together on one panel.

See first-hand how Alaska Airlines is evolving air travel, how Vivint is revolutionizing digital homes and how Nike continues to be an innovator in wearables all through understanding the opportunities from the Internet of Things.

Learning Lounge: An All-New Event Format

At the Learning Lounge, Seattle Marketing Analytics Group, PSAMA members, and non-members alike are invited to join together for an evening at SUR, one of Seattle’s most talked-about venues. Enjoy food and drink (ticket prices includes cocktails and light hors d’oeuvres) while learning from some of the Northwest’s most innovative brands how the Internet of Things is starting to re-shape marketing.

Expert Panel:

Details:

Date: May 15th, 21014

Location: Club SUR, SODO, 2901 1st Avenue S

Time: 6pm

Tickets are $25 for all Seattle Marketing Analytics Group members!

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Register here!

Special Thanks to our co-sponsors!

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The Learning Lounge is replacing the normal monthly MeetUp at Fado’s for the month of May. We will return to normal in June. 

If folks like it, The Learning Lounge will hopefully become a quarterly (or so) event.

The Shish List – Big Data at MarketMix

This article was posted by Shish Shirhar, Global Director of Big Data, Retail. He was one of our Making Big Data Smart Data panelists for last week’s PSAMA MarketMix.

http://blogs.msdn.com/b/shishirs/archive/2014/03/27/bigdata-at-marketmix.aspx0312_MarketMix1_thumb_13BAE14D

Thanks to Duane Bedard & Tina Munro of eSageGroup, I participated in a panel discussion at MarketMix with the brilliant Data Scientists: Jason Gowans of Nordstrom and Jon Francis of Nike. Duane Bedard did an excellent job of moderating the conversation.  I love his skill of condensing everything we said to short soundbytes that were ready to go on twitter 🙂 , and they did with hashtag #MarketMix.

Jon Francis shared interesting insights on the work he does on the ecommerce business at Nike. Jason Gowans runs the Nordstrom Data Lab and shared his perspectives on what it takes to walk the thin line between providing great customer experience through personalization and becoming “creepy”. We discussed where Big Data has proven value and where it has disappointed; talked about how Marketers can benefit from Big Data Analytics and what kind of data is useful for enhancing insights.

I spoke with several people in the audience after the session and one of the questions that stood out was: “How can we start small, working with multiple data sources?” My recommendation is to have a look at a tool that you most likely already have: Excel. Excel 2013 has some interesting new capabilities with PowerBI. The democratization of data and the democratization of tools is empowering everyone to get started working with multiple datasets, combine them and create great visualizations to derive insights. Check out some of the examples from my previous blog posts:

  1. Analyzing Seattle 911 Data using PowerBI
  2. Using Power Map to Analyze Public Retailer Data
  3. Visualizing Wal-mart
  4. Lets visualize Beer because it’s 5 pm somewhere
  5. How To: Visualize Real Time Flight Data & Correlate with Local Airport Weather