Digital Root

Agile Is Dead

Agile methods for planning - from software to market research - have evolved to a buzz/hype laden, heavy, and bureaucratic burden. At least in many shops that have too many people bearing spreadsheets and too few creating unit tests.

In practice I've restricted Agile/RUP/XP/etc to the minimum applicable elements necessary to get the job done consistently and humanely. Typically this means a basic sizing/risk estimate for discrete stories (oops my 1990's XP training is showing), pushing the high risk elements into early prototyping, burn/build tracking and iterative assignments. 

Generally it gives our teams what they need - projects that have the features and functions it needs, clear visibility, ability to change scope and assurance of date/budget delivery.

Applied to planning (advertising / product or research) a recent book eschews the mythos and hype around agile and boils it down to simplified experimentation. I read a good review that simplified it even further:

It's about doing the minimum amount of work needed to get to, or inspire, an idea.  It's about cutting down the waste - things like deliberating adjective soup and brand vegetables for 3 months.

It's about generating hypotheses that can be tested, not sitting in an ivory tower with a damp towel on your head waiting for the answer to appear like divine inspiration.

It's about making stuff that can be tested in the real world, not running weeks of focus groups to hear people talk about how they think they think or might behave.

It's about making as few charts as possible to explain a strategy or idea - get to the work

It's about understanding that strategy has to evolve and morph over time (whilst being aware there's a danger that this could become an excuse for superficiality).

It's a bias to doing over thinking.  

It's about doing stuff to learn stuff.

It's more like experimentation than planning as we know it.

 

 

Gaming YouTube

Youtube is reported to be the second largest search engine in existence, placing well above Yahoo! and Bing in terms of traffic. However, unlike Google, Yahoo! or Bing, there's little you can do to drive your videos to the top placement; short of being wildly popular.  And if that's the case, you're probably not reading this blog post.  YouTube while having the second largest search volume, they have less than .1% of web pages indexed by Google, providing a dramatically less competitive environment to get placed.

Based upon various online discussions, I concluded that searches within YouTube were subject to unintended but effective optimization techniques - just like normal search engines. To prove this, I setup a test with a well known brand (name withheld) that had less than 50 videos and less than 1500 lifetime views.

Cleaning up their tags, links and descriptive text was the first step, to make sure they were consistent, but the break-through was enabling Closed Captioning (as in for the deaf closed captioning) for every one of their videos. Essentially, we created our own closed caption script and uploaded the videos with them vs. using YouTube's automatic option.

The results were impressive – a 508% sustained improvement search results.

It appears that Youtube/Google uses the text from the closed-caption to index your video. When a user searches for a topic the words placed in your closed captioning text will be matched and placed higher in the search results.  In cases where your keywords are clouded by unrelated videos and hash tags, closed captioning may enable you to consistently place above other videos.

Optimizing search for images, videos and other rich content is untapped territory with a big payoff for relatively little effort. The simple technique of adding closed caption text to every video out performed paid sponsorships, link building and generating content.

When Good Design Happens To Bad Data

This infographic has been getting all kinds of love on Mashable. While it was created by a professionals I know and respect, it frosts me when wishes are presented as fact.

A portion of the underlying data originated from the ecumenical Addthis  of Clearspring Ad-network fame, but the comparative set is fit into models that are dubious at best.  Taking unlike metrics (e.g., Facebook's Monthly Active User, vs number of Gmail accounts) and using them for corollary or comparative models is risky if not deceptive form.

In the case of this infographic, the objective is to transfer the merits of well-known data (addthis tracking data) to unknown (pretty much everything else) and obscure the equivocation with slick design. 

It's doing exactly what most people expect advertising to do; Lie.

Mary Meeker is a Copy Cat

A week after I wrote about Mobile web trends pointing to a new form of data consumption,  Mary Meeker publishes a report supporting the same theory. 

Except she included a bunch of research baggage and such.

Internet Trends 2010 by Morgan Stanley Research

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Using Search To Predict Hits

There are over 100MM internet searches performed daily. Keywords, phrases and numbers are collected and stored within the major search providers vast databases.

What if that search data could be used to predict trends before they happen?

In 2008 and 2009 Google researchers showed some success in trending flu cases using search data alone. However,  most studies since have been inconclusive, or statistically irrelevant.

A few researchers working with Yahoo! recently leapfrogged prior studies by formulating a set of statistical models that were comparable to baseline models.  The intent was to see if by just using search data, could they get close to well-informed models.  The first step was to observe the impact of time on the models. In the case of Movies, Games and Music, build up towards release showed significant traffic spikes, signaling consumer intent (or interest).

The conclusion of the studies showed that search data alone - automatically generated models predicted revenue/success for  Games, Music, and Movie releases with an overall range of 74%-93% accuracy. 

The regression (log) scatterplot below depicts the model visually. The dots represent predictive values, the line actual baseline. The closer the dots are to the line, the more predictive the regression is said to be. In this case, with Theatrical releases, the model had a near 80% accuracy for success based solely on search volume data.

 

The same models can't be used universally for all topics, products or brands. And these models may be improved upon by adding more variables, or using traditional methods of measurement.

The big deal here is that using something as simple as query data - future outcomes are meaningfully predictable. The reduction in cost and time in rendering the models is staggering.

In addition to search, mining unstructured internet data, social media and sentiment often reveals trends that weren't visible through traditional studies. When combined with Direct-Survey & Consumer Insight analysis, the planning capacity grows dramatically and informs marketers in a whole new, and often surprising way.

2010: The Year Your Mom Changed The Face Of Gaming

Projected to earn over $1B in revenues in 2010, social gaming is taking the market by storm.  By 2011, projected sales generated from these games will be on-par with all software sales for Nintendo's Wii.

In a recent report from social game maker Pop Cap, the most surprising revelation is that the growth isn't coming from PC or console gamers; Its coming from middle aged women.

In the report, nearly 80% of players are between 40 and 70 years old (!!) and approx 60% are women.  Single, married, kids and no-kids all play social games like Farmville and Mafia wars regularly.

Amongst other findings, Pop Cap's survey revealed:

• Facebook is far and away the most popular destination for social gamers; 83% of social gamers cite Facebook as a place where they play social games, compared to 24% who play on MySpace, 7% on Bebo and 5% who play on Friendster.
• Social gamers spend 39% of all their time on social networking sites/services playing games. The second and third most popular social networking activities among social gamers are chatting with/messaging friends (17%) and playing non-social (solo) games (15%).
• When asked to choose as many reasons as they wanted for playing social games from a lengthy list, social gamers cited "fun and excitement" as the most popular motivation (53%). Stress relief (45%) and "competitive spirit" (43%) were next most popular respectively, followed by "mental workout" (32%) and "connect with others" (24%).
• Nearly half (49%) of the times when they log into social networks, social gamers do so specifically to play social games.

The implications are staggering for social media networks and interactive markers alike.   A recent innovative campaign launched by Ignited and Appsavvy, integrated Universal Pictures' Public Enemies content into Mafia wars. The results we're staggering considering the cost and complexity of generating equivalent impressions& engagement stats using more traditional digital tactics.

Over the next 18-24 months social gaming will become a mechanism to reach audiences in richer, more engaging ways - and likely more cost effectively than banner ads.

Does Targeted Advertising Erode Profits?

Taken at face value the report from MIT Sloan Assistant Professor Alessandro Bonatti contradicts what every computational advertising network has been saying for years.

"...as technology keeps improving, more and more web sites can sell very narrow products to very specialized audiences... with lots of people targeting the same audience the profits to be made through specialized advertising become more and more spread out... instead of competing for one large pool... you will have price war in each targeted segment as the slice gets more and more narrow."  Bonatti concludes that, "... the better the technology, the lower the profits for advertisers... "

There's more to this story than a clumsy application of the economic theory of crowding out.

A key flaw in the report is that CPM is used as the benchmark for profitability. While CPM was the preeminent metric in the days before digital, where there was little or no ability to measure beyond the impression. Not to mention the inherent elasticity of CPM as a representation of cost and reach.

Digital advertising and marketing has enabled the use of Cost-Per-Action (CPA) and full life-cycle tracking of events from consumer impression through to conversion and re-engagement.

A second point is the focus on long-tail consumables. When applying the notion of crowding and diminishing value (or utility) it's important to qualify the volume and ratio of units considered.

In the long tail, low volume goods become marketable due to targeting. Without targeting, the cost and overhead associated with selling the items is unsustainable and generally removed from consumer choice.

In the digital world, the leveraging mass scale markets and digital targeting pairs highly distributed consumers and sparsely available goods together in a cost effective manner. Essentially bridging the production gap of industrialization expressed by economists for the last two centuries.

The observation of impressions and clicks representing a fraction of outcome behaviors is also worth noting.  More sophisticated research has revealed that impressions have a profound effect on sales, awareness and consideration - even if they don't result in a click.

While the report has merit for what it measures - CPM in a long tail environment, it is missing the point of its own supposition; Targeted Advertising reflects the changing of what measures matter and creation of a new class of utility.

Why the Army has more fans than CBS

According to an upcoming report by Sysomos, the top 96th percentile (or top 4%) of fan pages have 10 thousand or more fans.

Sometime in late November 2009, the Army Experience Center's Facebook fan page celebrated its 10-thousandth fan. It's continued to add 200 to 300 more per week since then.

 Considering the vast amount of brands and products with fan pages on Facebook, what put the Army ahead of a network like CBS with its well known Survivor and CSI franchise?  This isn't about CBS whatsoever - that was just a randomly selected comparison - the Army AEC's fan page has approached social media on its terms, and is the better for it.

• Community.  The AEC didn't dictate their community in advance and structure content solely for them. Instead, it listened to the community and found several under-served segments that needed a voice.  Content was and continues to be shaped by the needs of the overall community and not simply what branding planners crafted.
• Relevant.  The Army community is active - one post generates an average of 45 responses or shares. The topics are current and in interest to the online community.  More importantly, because the community helps define the content, it self-regulates polarizing fans intent on disruption. Topics are relevant to the communities interest, not something that would normally come out of PR or planning.
• Local.  The AEC itself is a physical location set in Philadelphia that draws thousands of visitors every month. But it's still a single location that serves a 10-12 mile radius.  The content and community on the fanpage expands throughout the country (and world) by providing local content (events, pictures, personal experiences) without excluding fans that are there in spirit.
• Authentic. What makes the AEC fan page interesting is that actual soldiers are part of the community. When questions are asked about Army life, enrollment or benefits - they're met with real answers, not directed to a website or FAQ. 
• Engaging. Polls and crowd-informed decisions are common on the AEC fan page. They allow the community to shape and mold topics and discussions - instead of giving them a one-way communication.

While many fan pages have polls and pictures, they often don't attract active fans without give-aways or promotions. Why?  Because they've missed the message that social media is about the community, not the brand.  The brand may participate - and may be embraced - but if it's heavy handed, bullying, or a one-way speaker it'll be dismissed as just another commercial.

Measuring Past The Click

Key Insights:

• Digital Advertising will continue to grow while traditional media spend shrinks, eventually overtaking traditional
• Clicks are a poor proxy for measuring digital
• Digital impressions have a profound offline and online impact on intent, sales and dollar value
• Quality of impression, with emphasis on time (reach & frequency) is a superior measurement over clicks

In September, UK Digital Ad spending overtook TV for the first time representing approx $2.8B  of spend in the first half of 2009.   By comparison, the US market spent $10.9B but its share accounted for less than 20% of traditional media spend overall.

Proportion aside, growth forecasts predict Digital spend in the US will represent over 31% of overall advertising spend within 3 years, whereas traditional will shrink 15%.

Who's clicking?

With digital media taking a significant, if not lead role in advertising, how does the prevalent "click" measurement hold up?  Not terribly well.

From June 2007 to August 2009,  the volume of people who click shrank from 32% to 16% - and is expected to continue its deterioration.  More importantly, those that do  click, are comprised of no-to-low income people under 24, hardly the audience most brands are seeking.

The Impression Effect

Clicks clearly aren't the answer as it represents a small portion of the audience, and typically one that doesn't convert into sales.

A recent study found an interesting answer to the question. Where clicks failed to register as a proxy for sales, post-impression behavior indicated a profound impact upon sales, both online and offline.

The presence of ad's in the form of display and search combined lifted sales an average +27%, and lifted traffic at least +46% over a four week period.

 

   

When search and display ad's were coordinated, offline sales lifted up to 52% with a staggering 119% increase in dollar value.   Online numbers were even better;  173% increase in sales lifted 124% in dollar value.

When you consider the data, measuring clicks is like trying to tell if a shirt fits by counting the number of buttons on it.  

What To Measure

So, what is the answer? Most research suggests that the longer a person is exposed to an ad, the more effective it will be— until the point of diminishing returns. The future of digital measures has more to do with depth of impression (time, reach, frequency) than clicks or views alone.

Rather than simply counting the number of impressions served, the appropriate measure becomes quality (reach, time, frequency) of an impression. Using this method, you can even reduce placement by focusing on impressions that offer a quality level that may be counted as true impressions over focusing on total volume.  Utilizing real-time segmentation and coordinated digital planning, campaigns can deliver far reaching, impactful impressions to the right audience.

In light of the rapidly changing advertising landscape, it's imperative to understand the full impact of impressions, and shape your campaigns to drive your end-goals, not just rack up clicks and impressions.

Data: Anonymous or Useful; Never Both

Anyone who works with consumer data understands that when sharing or using private data, individual identifiers must be "anonymized" for privacy concerns.

In the US this is typically accomplished by removing the Social Security number, name, address and account identifier.  Data elements such as ZIP code, birth date and gender are considered legally acceptable for sharing or publishing.

However, a growing body of research is proving that even generic identifiers present a serious risk.  For instance:

• In 2008, two UT researched reverse engineered Netflix's public data  using only a name and three movie ratings to identify every movie that individual rented.
• In 2006 AOL released search data for 650,000 users, but only after removing user names, IP addresses and anything considered identifying.  Within days, an individual was identified by nothing more than a generic users ID and search content such as “‘landscapers in Lilburn, GA,’.  The seemingly anonymous data was tracked down to Thelma Arnold, a 62-year-old widow from Lilburn, Georgia who  confirmed that searches such as “numb fingers”, “60 single men”, and “dog that urinates on everything." belonged to her.

With the growing body of publicly available data sets from sources such as the US Government  (here, here and here),  Amazon, or dataset sites, the risk of identification through cross reference increases dramatically.

True, the techniques used today to identity individuals is somewhat brute-force and manualized, the growing body of cross-referencing data will lower the bar over the next few years. And remember, the internet never forgets.

For those responsible for data sharing here's a few points of advice beyond standard anonymization techniques:

• Group age by ranges instead of providing DOB. E.g., 18-24 or even reported age.
• Instead of providing ZIP codes, use US Census FIPS codes to identify broader geographic areas.
• Avoid including gender where possible.

For consumers, be selective of where you record your information online. Its not possible today to exist online without providing at least some of the data, but for elective services such as facebook or youtube, approximate your DOB or Zip lest the organization share it down the line.