MAD Perspectives Blog

Recognizing the Signals

Peggy Dau - Monday, June 29, 2015

A fast paced world requires the ability to recognize the signals. Like Native American smoke signals, Morse code, or even a baseball managers swiping the rim of his hat, signals guide and alert us. Various forms of technology represent today’s signals. Whether they are social media, wearables, apps or platforms designed to monitor and measure – we are seeking signals to warn us of potential failures and to identify opportunities. This is why Big Data is so omnipresent – it is perceived as one method of identifying signals.

Broadband penetration in the U.S. has grown from 20% in 2004 to 79% in 2014 (Leichtman Research Group 2014), while broadband connection speeds have increased from 56Kbps in 2003 to and average of 11.1Mbps in 2015 (Akamai State of the Internet Report, May 2015).

Many a start-up will tell you that their foundation was based on spotting a gap (aka opportunity) in the market that they knew they could fill. The ability to create a new reality is called progress. Look at the adoption of social media. The grand daddy of social media, Facebook, has 1.44B monthly active users (MAU) based on their April 2015 earnings report.  That’s larger than the population of China. 70% of that MAU is mobile. That’s a signal.

When it comes to video, the power is shifting. YouTube was and still is the king of online video. Before YouTube online video was proprietary with inconsistent performance. The broadcast and cable industry did not consider online video a challenge or an opportunity. However, YouTube changed that by providing a user-friendly ability to upload AND view user-generated content. That’s a signal.

Facebook has entered the online video segment and is challenging YouTube for the all important ad dollars. The popularity of both platforms is not in question. The challenge will be who can better optimize the video experience, for both uploads and viewing, for the mobile audience. BTW, I’m defining the mobile audience as users viewing content on a tablet or smartphone via a Wi-Fi or 4G/LTE connection. Ooyala says that mobile now accounts for 42% of all online video viewing. That’s a signal.

What’s the next step in the progress of sharing and viewing video? For sure it is mobile? But what does that look like. What signals are we seeing from device manufacturers? Are you ready to watch TV on your smart watch?

What are the signals in your industry? How will financial services capitalize on tweets? Will railroads improve safety and optimize routes using communications and Internet of Things technologies? Will your car not only tell you that you need gas, but also the location of the closes gas station?  By paying attention to the signals that are shared every day, perhaps you can identify the next big idea!

What’s your perspective?

Data is the Legendary Needle in the Media's Haystack

Peggy Dau - Monday, May 11, 2015

Obtaining volumes of data can be a double edged sword. The media industry is embracing data, particularly consumer data, as the basis for validating investments and business models. Vendors at all stages of the media workflow are collecting data and emphasizing its value to their customers. But, collecting data without an understanding of how it will be used creates new problems, the least of which is storing all that data. The bigger challenge is figuring what they really want to learn from the data and then drive real, measurable value from it.

Imagine all the devices that now provide data: set-top boxes, tablets, smartphones, network routers, servers, storage....and more. Then consider all the data that is already surrounding any piece of media: descriptive metadata, licenses, contracts, schedules, algorithms...and more. And, we haven't even brought up the related social or digital data or the insights that are important to advertisers. There is data everywhere with just as many the vendors ready to help you collect it. And, they all directly or indirectly reference the all important consumer experience.

Even focusing on the consumer alone, means aggregating, correlating, and analyzing data from a plethora of resources. It's not enough to collect data from set-top boxes that reveals when and what a subscriber consumed. It's now a priority to assess their method and frequency of engagement with and around video. Content protection vendors will provide you with data to reinforce that derived from distribution channels. Did the subscriber start watching on one device and finish watching on another devices? How did they authenticate their access to content on their device of choice? How did this impact their level of engagement? The answers to these questions influence content production, scheduling, marketing, and advertising. Oh, and did I mention monetization?

Understanding preferred methods of engagement, will drive advertising models. What works on TV, does not work on a tablet nor on a smartphone. Yet, content must be monetized. It takes more than demographics to understand how to derive revenue for programming targeting the 18-24 year old audience. How does this audience respond to ad-supported content versus subscriptions? How do they discover the video programming?  As the saying goes, "it takes a village" to capture data from a variety of sources and develop conclusions that subsequently drive future actions. It may start with demographics, but the process quickly incorporates analysis of a variety of stimuli and resulting actions. What happened that caused a viewer to engage or disengage?

Defining what is needed from the data is critical. Is it about audience engagement or customer experience? Is it about content quality? Network performance? Ad buying? The more specific the goal, the better understanding of the right vendor to provide that data; and the more effective the data collection and analysis. Making sense of data can be like looking for a needle in the haystack. Is that how you want to define your strategy? Big data has the potential to help shape the future of the media industry, let's not forget that it's about more than simple data collection.

What's your perspective?

4 Ways Data Matters for Media and Entertainment

Peggy Dau - Monday, April 13, 2015

Every industry has it's perspective on data. Yet, perhaps no industry will change as dramatically, as the media & entertainment industry, through it's use of data. This is an industry that has long been driven by it's "gut". Watch almost any Mad Men episode and see how Don Draper pulls a pitch out of nowhere to win the client. The "golden gut" has long been the driver for green-lighting projects in Hollywood (and elsewhere). However, the shift to data driven program development may be attributed to Bonnie Hammer at USA Networks. She systematically changed the way original programming was approved and pursued. However, their access to viewer data was limited - until they initiated a comprehensive multi-channel fan engagement strategy. Their adoption of second screen tactics to engage with viewers has given them keen insight into fan sentiment. 

More recently, the champion of data driven content is Netflix who have access to volumes of subscriber data that they aggregate, correlate and analyze to identify and validate project development opportunities.  But is the use of data by the media and entertainment sector limited to that data related to their audience? This may be the most talked about use of data, but there are others. Data is critically important throughout the the process of creating, managing, distributing and consuming content - especially in this age of digital workflows.  

Where is the data? It is everywhere. It is around the creative process, the business process and the actual consumption. Every aspect of data is directly or indirectly related to monetization.

1. Content Creation - This is where the "magic happens". Editorial teams collaborate to layer files, add graphics and special effects, incorporate music to create a finished product. They tag assets and create metadata to describe the asset. The metadata includes, but is not limited to, title, artist, composer, genre, encoding format, frame size, frame rate, bit rate and DRM properties. This data facilitates editing team discovery of assets to assemble new content or to repurpose existing content. Metadata stays with the asset throughout the media workflow and when it is stored or archived. Without metadata, the ability to create content and determine which content can be monetized becomes very difficult.

2. Business Management - Alongside the creative workflow, are the workflows to manage resources, scheduling, transmission, contracts, rights management and royalties. The data in these systems help to view, manage and control production costs. When content is available for distribution, platforms deliver solutions and data relevant to manage, track and monetize assets and related royalties payments, across multiple distribution channels. The complexity of the business processes, adjacent to the creative process, cannot be ignored. The data related to these processes is critical to the overall success in 

3. Distribution - The mandate to deliver content to consumers across a myriad of devices requires those service providers who own the networks to guarantee a defined level of performance. They must serve the needs of content owners as well those of their consumers. They must monitor and manage the quality of their networks. And, these measurements are data. They measure bandwidth, network performance, streaming experience, track video playback quality, audience consumption patterns and more. Data is captured, analyzed and shared with content owners.

3. Consumption -  This is the focus of the industry - creating and distributing content that will attract an audience. Whether it is a feature film or a sitcom, understanding the audience is key. They buy tickets and subscriptions. They are the potential buyers of products advertised by brands. The attention and focus on measuring audience is ever growing. Whether it is Nielsen, ComScore, Twitter, or other audience measurement solutions, the goal is to identify the volume, demographics and sentiment of a program's fans. This data ultimately drives advertising revenue which is also changing with the rise of data driven programmatic advertising. The increased adoption of OTT channels provides content owners with increasing sources of data about their consumers. OTT enables a direct relationship with consumers. Like Netflix, networks can benefit from a direct understanding of audience demographics and behaviors to understand which content, actors or genres appeal to their OTT audience. It can influence schedule, availability

Digital media has changed every aspect of the media industry and in the process increased the number of data sources. Data is persistent, voluminous and valuable at every stage of the media value chain. There are many more ways that data matters throughout the creative, business and distribution processes. Yet, this industry still relies heavily upon its gut. Perhaps this is due to the creativity that is a necessity. It will be interesting to see the balance of data and creativity. Data can validate investments. Data can reinforce strategies, but this industry more than others is dependent on creativity. Can all this data inspire creativity? 

What's your perspective?

Making Data Matter

Peggy Dau - Monday, April 06, 2015

It really is the overarching conversation across all business sectors. Data. It's always been there, but we seem to have fallen in love with data all over again. We've been using it since we were in elementary school. We've collected it at every point in our life. We absorbed data about which friend liked the same sports team or what color shirt they wore or what time they ate dinner. We align ourselves with those of similar interests and seek out those with opposing opinions, if only to debate or educate.

Completion of our education did not stop the data deluge, it only changed its form. In fact, some of use decided to become analysts or scientists that steeped themselves in using data in new and fascinating ways. We are no longer memorizing multiplication tables or historic dates, nor are we organizing arguments to support theses. Now we are absorbing data about our industry and its people, processes, products, technologies, tools and communication methods. We manage a LOT of it instinctively. However, the rise of BIG data reinforces the relevance of data and the technology industry for all sectors, whether they are financial services, healthcare, consumer products, hospitality, travel, manufacturing, environmental - ok, you get it. Big data is applicable and pertinent for all industries.

But, how do we make all that data matter? I collect data points every day as I work with clients to develop strategies and content that reflects their value to their target customers. This means understanding their customers' needs, communicating in a manner that resonates with the customer, while still reflecting the key attributes of my client's technology. It's not always easy finding and collecting the right data. All that data doesn't always makes sense. It can be confusing.

This is why we are now seeing the focus grow beyond data collection and analytics. We're going to learn a lot about predictive and prescriptive analytics in the coming months. These are the magic 8 balls of the big data industry, thus far. They are fortune telling at their current best. If we can anticipate the needs and behavior of our customers, we can improve how we address and fulfill them. We can adapt business processes, modify go-to-market models, refine marketing and ultimately, improve revenue and profit margins.

That's the holy grail - make the data matter. But it's just not that easy. I have technology clients managing data, analyzing data, manipulating data and making recommendations borne from data. In the media sector, Nielsen reports data about what we watch. Ooyala shares data about how we watch. Cisco reports about how many bits move across networks. Bay area start-up Guavas provides data on the health of those networks. These are all indicators that should be acted upon. We are all awash in data and I, for one, am eager to see how we make this data really matter for business customers and consumers.

What's your perspective?

Big Data - Is It Worth The Money?

Peggy Dau - Monday, March 30, 2015

Every organization seems to be prioritizing their need for data. Small or large businesses, finance, accounting, sales, R&D and marketing - they're all seeking data. But, are they willing to pay for it. We could argue yes when  IDC predicted Big Data would drive 16.1B in revenue for severs, storage, software and services, in 2014. But that's just the infrastructure. What about the analytics to understand the data? 

Let's consider the use of data as it relates to marketing. Of course, it could be used for R&D, manufacturing, sales and other aspects of business. However, there is an interesting shift in marketing, with CMOs increasingly investing in technology to better under understand their customers and to manage their marketing programs.

Marketing executives all prioritize their need for data analytics to drive smarter campaigns and improve personalization. Yet, when it comes to prioritizing budget, e-Marketer says analytics falls behind digital commerce and customer experience. However, according to the CMO Survey, this is about to change. While marketing analytics currently accounts for 6.4% of the overall marketing budget, this is expected to increase to 11.75 over the next three years. 

It's not unusual for the budget to lag behind the defined need. After all, why spend the money if it's not aligned with your business goals. The interesting thing is that the data analytics could drive more effective digital commerce and/or customer experience investments. The global marketing analytics market is expected to grow to $2.1B by 2019 according to marketsandmarketsThe big question is if that investment is worth it. It comes down to more than analytics, as there must be a human element that capitalizes upon the finding. But, the reason analytics is hot, is the promise that data analytics can improve marketing ROI. 

Here are just a few examples:

  •   - understanding customer use and engagement of different mediums allows marketing to optimize use of channels such as email marketing, social media, webinars
  •   - identifying customer needs allows marketer to develop relevant content at every stage of the buying cycle
  •   - uncovering audience personas and motivations allows marketers to align messaging, agenda and/or sponsorships at business conferences 
  •   - align human effort more effectively 

Marketing budgets represent approximately 10% of the overall corporate budget. Isn't it worth the investment in analytics to uncover the data that will can lead to a tangible increase in marketing ROI? 

What's your perspective?

Big Data Loves It When You Get Emotional

Peggy Dau - Tuesday, February 17, 2015

You know the saying, "it's either laugh or cry". We've all been in those situations where we choose which emotion to express. In fact, in business it's considered poor form to be too emotional. However, those emotions are at the heart of all this big data that's floating around. In the media space, where companies large and small are collecting, aggregating, analyzing data in order to pontificate about the likes and dislikes of their audience, emotions are critical. It's not enough to have 23 million viewers. It's better to understand what they enjoyed or hated. 

The media industry has always been focused on making an emotional connection with its audience. Just look at the run-up to and the aftermath of the SuperBowl. We all know this is not just a game. It is big business for advertisers. GoDaddy created an ad that generated a lot of negative feelings. Whether it was planned or not, they pulled the ad and replaced it with another ad - equally annoying in my opinion but successful in making me take note of their brand. Budweiser continues to tug on our heartstrings with their puppy + Clydesdales storyline - to further cement the position of the brand as a warm and friendly.  

The benefit of the data coming from social networks is that it reveals sentiment. Sophisticated algorithms have been developed to assess whether a statement is positive or negative. Data scientists extrapolate terminology and identify trends. While social media and online behavior provide context in data analysis, that context is more than about what might have influenced a tweet or other social update. It is about the emotion expressed in those updates. 

Live programs are evolving to incorporate audience sentiment into their conversations. Real-time decisions can be made to abandon discussions or investigate "hot" topics more deeply. Reality and scripted TV benefit from the stories portrayed on screen as audiences develop emotional connections to the characters. While data analysis allows producers to better understand audience emotions and subsequently guide their social engagement and promotion strategy. 

Face to face we can read body behavior. Online it can be difficult to detect emotion, which can lead to misunderstandings. This is one reason why the emoticon has become so popular. Aside from being a fun way to quickly express an opinion, they help others understand our moods. 

Consider the ongoing quandary at Facebook about adding a dislike button. We've all wanted a dislike button, especially when we want to reinforce a friend's negative opinion of something. The challenge is understanding the business impact of clearly expressing a dislike. 

Is there business value to being emotional? Yes, there is! So, go ahead get emotional.

What's your perspective?

And the SuperBowl Winner Is...

Peggy Dau - Tuesday, January 27, 2015

…DATA!! Ha! You thought i was going to predict the winner of the big game. Well, i don't claim to be enough of a football fan to even make an attempt at that prediction. I'll leave that to the Las Vegas bookies and the legions of fantasy football leagues. But I can predict that we will see a LOT of data as we approach the game , during the game and directly after the game.

After all, it's more than a game. We will watch the competition on the field, digest a slew of statistics, and debate the merits of ads costing $4M for 30 seconds or $8M for 60 seconds (yes, that's my obligatory pice of data and it doesn't include the cost of producing the ads). We will post social updates about various plays, but also about Katie Perry's halftime performance, our favorite snack food recipes and drinks, what we are wearing, and the weather.

We will seek, find and share videos and data points about past super bowls. In fact, the NFL is makes it with their new Game Rewind service (P.S. free trial access expires February 2, 2015). There will be #hashtags a plenty trending on Twitter - some promoted by the NFL, Patriots and Seahawks - others inspired by on screen events (football related or….not).

Oh, and yes, this is the event that still drives live TV viewing. Sure we will use second screens to enhance that TV experience (and there will be tons of data after the event to reveal what devices, platforms or apps we did actually use), but we will gather together for the original social experience, a party with friends, to enjoy the big game. We will watch the game on HD and UHD TVs. NBC will appreciate the ratings bump.

Yes, we're going to consume a LOT of data. We will debate the merits of each team, player by player, position by position, by salary, by location, by owner and head coach. And, we will create a LOT of data that will be aggregated, analyzed and spit back out to support various perspectives about the birth, death or sustainability of live TV, second screen, social media, and advertising.

Enjoy the game!

The CES Barometer

Peggy Dau - Monday, January 12, 2015

The Consumer Electronics Show is the annual event that sets the stage for the coming year's technology conversations. While the name indicates a focus on consumer electronics, there is a lot of big business mojo in play. Sure there are gadgets and "toys" for us to get excited about, but as many of the journalists attending the show this week indicated - it's just as much about the technologies that enable these gadgets.

To be hones, I've only been to CES once - about 7 years ago. It was an interesting experience for a professional who had previously attended large enterprise events in and around the high tech industry. I walked away thinking that every man i know should attend CES at least once. Now with the rise of the Internet of Things this is truer than ever. Whatever the interest - healthcare, finance, lifestyle, gaming, entertainment or sports, there is something there is always some "bright shiny toy" that will appeal.

But what about what makes all these toys work. Many of them would not be possible without advancements in wireless networks, software development, and plain old creativity and innovation. Having spent a large part of my career in the technology space, focused on telecommunications and media, I appreciate the ongoing efforts to deliver entertainment to greater numbers of devices. I remember trying to watch the World Series on a PC at the 2003 ITU Telecom World in Geneva. Video streaming over the Internet was still pretty sketchy. The connection was persistent, but the quality of the video was low with high pixelation and pauses as the stream re-buffered.

Today we take internet video streaming for granted, as evidenced by the rise of OTT consumption of TV and movie content. Announcements from HBO, CBS and ESPN reflect the shift in consumer behavior. Where TV has been considered the lean-back" experience of enjoying sports, comedy, drama or news, tablets and smartphones are actively intruding. Thanks to improved streaming, compression and network technologies, we can enjoy whatever content we want, wherever we are.

So as we read about the excitement of CES, consider the implications and continuous investments in:

  •  Wireless networks - 4G and LTE are just the latest iterations of network capacity and its ability to an increasingly wide assortment of content.
  • Video cameras capable of capturing content in 4K, 6K and 8K. What's the point of those UltraHD television sets if there is no high quality content programming.
  • Software development - Cloud computing has changed the way in which we access and design enterprise and consumer applications. The concept of apps will only evolve to something even more easily distributed and accessed. It could be virtual.
  • Batteries - All these advanced capabilities, controlled by smartphones, placing increasing demands on battery power. Solutions to "charge-on-the-go" must evolve, if only to eliminate the number of back-up devices that must be carried.
  • Data analytics - The availability and adoption of wearables creates even more data points from which consumer and enterprise can benefit. We willingly share our behavior via social networks, apps and devices. Imagine the insight gained that will enable our devices to anticipate our every need.

Sure CES is entertaining. But, it's also exciting in getting a read on the pulse of innovation and development. Sure, not everything at CES will make into the mainstream. But, it is a barometer tracking the evolution of consumer influence on technology development.

What's your perspective?

A Data Driven Christmas?

Peggy Dau - Wednesday, December 10, 2014

As we enjoy the holiday season and prepare to enjoy time with friends and family, we also struggle to find the perfect gift. We seek suggestions, rack our brains from creative ideas, and sometimes default to the ubiquitous gift card. What we are seeking is the data to support our decisions.

Whether we are shopping in-store or online, we want validation that we are selecting a gift that will please the recipient. Our intent is to create joy. However, sometimes we mis-fire and our seemingly perfect gift falls flat. Could a data driven gift selection process improve our "win ratio"?

E-commerce sites are investing in big data to improve the consumer experience, to expedite your purchase decision by providing recommendations, and to drive revenue. In-store promotion seek to attract buyers with heavy discounts, but recommendations are absent, unless shopping with a friend. Many of us seek to avoid the physical shopping experience due to lack of time or distaste for crowds. More of us are shopping online as noted by the lackluster Black Friday figures. Yet overall spending both online and in-store declined by 32% from 2013, per the National Retail Federation. There are a variety of reasons for the decline, but perhaps better marketing driven by an understanding of customer need would result in a smaller decline.

Amazon has long been noted for its recommendation engine. Not that it's perfect, but it does gather a lot of information about consumers and it has the ability to recommend products that are similar to those we have viewed, purchased or queried. But, what if we are seeking something completely different than any prior purchase? Amazon, or any other e-commerce site, would struggle to recommend an interesting item. Without incorporating data that reveals our goal, recommendations fall flat.

Big data is the combination of internal data, such as Amazon has collected in it internal databases, plus the combination of external data collected from the internet. It includes data from online searches, social networks and other publicly available sites. It is this unstructured data that does not reside in an existing database that begins to reveal the intent or motivation of the buyer. With an understanding of intent, recommendations can become more relevant and actually influence consumers to take the desired action of buying a gift.

Businesses, B2C or B2B, must define their own intention for using big data. Then, they can create the strategy to collect and analyze the right data to help them achieve their goals. Then, they can provide the context that will motive at customer to take the desired action.

Each industry's buyers and sellers have unique influences driving their behavior. Acknowledging and identifying these drives, helps big data become more relevant and allows big data to lead to measurable actions. Perhaps next year will be a data driven holiday season. For this year, the data is informative but not inspiring or influential.

Will you have a data driven Christmas ( or Hanukkah or Kwanza)? Has data streamlined your gift buying and giving?

What's your perspective?

Are We Too Dependent On Data?

Peggy Dau - Monday, December 01, 2014

I'm a fan of the rise of data analytics and am enthusiastic about it's potential to deliver greater insight that subsequently allows individuals and companies to better serve others. However, I wonder if we are becoming too dependent on that data, or perhaps on the promise of the data.

Regardless of industry, every business thrives on data - whether it is in the form of sales revenue, expenses, headcount, volume of customer service calls, mean time between equipment failures, number of Twitter followers, crop yields, or trading volumes. Publicly traded companies provide Wall Street analysts with lots of data every quarter. Said analysts then pontificate on the virtues or shortcomings resulting from the announcement.

Companies talk about making data driven decisions. Netflix has been the poster-child for this way of thinking, in the media space, as exemplified by their investment in original content creation and choices in what content is promoted subscribers. Fortune 1000 companies make decisions about new products, pricing, go-to-market strategies, customer service, supply chain, hiring, firing, and just about every element of their business, based on data. In many cases, managers and individual contributors are penalized if they do not have the right data at their fingertips.

The challenge is, that some decisions have to be made in the absence of data. The ability to make those decisions is typically born from past experience. But, what happens if a generation of workers has been wholly subjected to data-driven decision making? What if they have not been allowed the autonomy to pursue a strategy that makes practical sense, but is not 100% supported by the data? And, what if that same strategy has minimal cost impact on the organization, but could provide a significant return? Many would say, yes, pursue the strategy for a period of time but measure the results carefully. Yes, that means find the data to support the activity. Others would say, no, there is not enough data to support the limited investment. There are better ways to spend the money.

The billions of dollars being spent on big data are pointless if the data cannot be analyzed and used to support innovation. The challenge remains, how to use the data to drive some type of action. The data is useless without understanding the impetus for acquiring the data. The desire for data should acknowledge that hard earned experience, market awareness and gut instinct are part of discovering the right data and the subsequent analysis of the data. Data taken out of context can lead to misunderstanding and potentially unintentional actions.

Let's be aware of the data, but add in a healthy dose of common sense and human assessment of the data. Let's use data to test our instincts, not replace them.

What's your perspective?