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October 22 2013

Actions predict louder than words

Data isn’t just bigger these days; it is also fundamentally different than it was 10 years ago. The nature of this change is driving several innovations in the way marketing is done, particularly around targeting and measurement.

From a predictive targeting standpoint, ad tech firms are realizing that knowing a user regularly visits an investing blog and regularly searches for stock tickers is more valuable than knowing the age, gender and income of that user when targeting for a financial services brand. Traditionally, demographic and lifestyle data has served as a proxy for a good audience. With modern server logs holding behavioral data that tracks every last click, marketing firms can do away with the proxies and build audience segments with a high likelihood to take some sort of specific action — like converting. Ad tech startups such as Dstillery (full disclosure: the author works for Dstillery) and Rocket Fuel have based their respective approaches around this concept. Big data technology coupled with machine learning best practices has enabled the use of event-stream behavioral data to accelerate in the last five years. The market is starting to notice the value this approach is bringing, with Rocket Fuel being a recent IPO success story.

Better user-level targeting isn’t the only innovation brought by log file data. The digital promise of having better insight is slowly being realized by firms offering third-party ad effectiveness measurement. Companies such as Adometry and Visual IQ are pioneering the use of machine learning to model the causal effectiveness of ad exposures on user conversions. Using these models, brands can better evaluate which digital strategies are the most effective at driving up their ROIs.

Although the innovations discussed above have been developed mostly around web usage, the ideas can be directly applied to other digital channels, such as mobile and TV. In mobile, the fine-grained behavioral data is being measured as app usage and the geographic movements of the user. Companies like Flurry, Foursquare and the aforementioned Dstillery are making use of this type of data. TV advertising is probably the most embedded in traditional advertising practices, but even it is poised for disruption as household-level TV viewing logs become available. DirecTV, which controls access to both the content delivery and the data, is starting to target commercials to the household level based on its content viewing profile.

While these innovations are driving better targeting efficacy and more accurate measurement, they don’t come for free; the bigger challenges in particular are social in nature. Tracking user behavior at the event or click level requires a constant focus on protecting consumer privacy. Firms with access to this data need to bake privacy into their data storage and usage policies, and start adopting machine learning methods that are privacy preserving by design. Additionally, communication is often a constraint for firms innovating the use of data in marketing. The ultimate decision makers in marketing are business people, who, while smart and creative, are not often trained in the state of the art in big data technology and machine learning. The “Black Box” nature of the new suite of advertising technology creates an impediment for adoption. To increase the rate of adoption, ad tech firms need to adopt more transparency and be able to present their technology at an intuitive and approachable level. Demographics are easy for a marketer to understand and digest — logistic regression on sparse, hashed features is not. When this gap is bridged, we should expect data-driven marketing to evolve at an even faster rate.

September 03 2013

Demographics are dead: the new, technical face of marketing

Over the past five years, marketing has transformed from a primarily creative process into an increasingly data-driven discipline with strong technological underpinnings.

The central purpose of marketing hasn’t changed: brands still aim to tell a story, to emotionally connect with a prospective customer, with the goal of selling a product or service. But while the need to tell an interesting, authentic story has remained constant, customers and channels have fundamentally changed. Old Marketing took a spray-and-pray approach aimed at a broad, passive audience: agencies created demographic or psychographic profiles for theoretical consumers and broadcast ads on mass-consumption channels, such as television, print, and radio. “Targeting” was primarily about identifying high concentrations of a given consumer type in a geographic area.

The era of demographics is over. Advances in data mining have enabled marketers to develop highly specific profiles of customers at the individual level, using data drawn from actual personal behavior and consumption patterns. Now when a brand tells a story, it has the ability to tailor the narrative in such a way that each potential customer finds it relevant, personally. Users have become accustomed to this kind of sophisticated targeting; broad-spectrum advertising on the Internet is now essentially spam. At the same time, there is still a fine line between “well-targeted” and “creepy.”

As data availability has improved the quality of potential opportunities, perpetual connectivity has increased the quantity. The proliferation of mobile devices, decreasing cost of data access, and popularity of social platforms have increased the number of avenues that brands have at their disposal. However, these factors have also made it harder for them to actually connect; today’s audience has an ever-shorter attention span, as focus is split across an increasing number of channels. Consumers are better informed than ever before; a price- or fact-check is simply a Google search away, whether users are in front of their TV screens or walking around stores.

This changing ecosystem has already resulted in a shift from transaction-oriented “product-centric marketing” to a relationship-focused “human-centric” approach. Consumer loyalty to brands is a thing of the past; brands now demonstrate loyalty to their customers. Marketing campaigns must be time-, place-, and context-aware. It’s also important to be technologically on point: cross-device, multi-channel, constantly measuring results and refining campaigns. Today’s technology has largely mitigated the Wanamaker problem, but a Goldilocks problem remains: consumers don’t want to be inundated with marketing that is too obnoxiously broad or too creepily specific. Consumers want relevance.

The Radar team is interested in the progression of “reaching” passive audiences to “engaging” active ones, and in the technology that enables brands to break through the noise and find the people who are most likely to love them. In upcoming months, we’ll be investigating the continuing evolution of marketing, with a focus on fusing the art of storytelling with the promise of data and the objectivity of analytics. If you’re excited about this field, or know of someone doing interesting work in the area, let us know — drop a note in the comments section, or ping me via email or Twitter.

August 17 2012

Four short links: 17 August 2012

  1. What Twitter’s API Anouncement Could Have Said (Anil Dash) — read this and learn. Anil shows how powerful it is to communicate from the perspective of the reader. People don’t care about your business model or platform changes except as it applies to them. Focus on what you’re doing for the user, because that’s why you make every change–right? Your average “we’ve changed things” message focuses on the platform not the user: “*we* changed things for *our* reasons” and the implicit message is because *we* have all the power”. Anil’s is “you just got this Christmas present, because we are always striving to make things better for you!”. If it’s deceitful bullshit smeared over an offensive money grab, the reader will smell it. But if you’re living life right, you’re telling the truth. And they can smell that, too.
  2. Goodbye, Everyblock — Adrian Holovaty is moving on and ready, once more, to make something awesome.
  3. Turkopticon — transparency about crappy microemployers for people who work on Mechanical Turk. (via Beta Knowledge)
  4. Digital Natives, 10 Years After (PDF) — we need to move away from this fetish of insisting in naming this generation the Digital/Net/Google Generation because those terms don’t describe them, and have the potential of keeping this group of students from realizing personal growth by assuming that they’ve already grown in areas that they so clearly have not.

June 08 2011

May 16 2011

The future of technology and its impact on work

Here's a 40-minute presentation and interview I gave at the Center for Technology, Entertainment, and Media (CTEM) at the Fuqua School of Business at Duke University. The video covers a range of subjects including demographics and technology trends that will emerge over the next 5-10 years and what will be required to succeed in the workplace of the future.

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