SO-Analytics
INTRODUCTION
The fundamentals that make economies of scale work are deteriorating before our eyes. Abundant computing power, the free flow of information on the Internet, and the ability to harness data—forces breaking down conventional beliefs—make for a virtual socioeconomic tsunami that is tearing apart the way business runs and how competitive advantage is won and lost.
An ecosystem of information, communication, and methods driven by constantly evolving technology is upending 200 years of truisms. This observation implies the need for a new business model with four basic tenets:
- Network effects trump size. Third parties are building scale across multiple customers, eclipsing the traditional manufacturing and distribution infrastructure, and reducing the need for the plant, office space, warehouse, and distribution line. Instead, businesses increasingly can tag existing assets brought together by a third party that connects those in need with those that have it.
- Fixed costs and asset scale are obesity to progress. Think Amazon, Facebook, AirBnB, Uber… After just a few years they are all achieving market cap and industrial size that took decades to achieve in the 20th century. These companies are using information asset scale—the ability to leverage massive assets by connecting third parties through information channels, versus owning fixed assets. The new business model is built for constant transformation where changing parts, capabilities, and tools are the norm; the speed to adapt and innovate outmaneuvers patents and technology strangleholds.
- Technological advancement comes from the outside, not the inside. New ways of doing everything are changing so rapidly that single entities, even the best and brightest, cannot keep up. Partnering with innovators is the top priority; building fast—adapting rapidly to the best available approach—trumps scale. “100 percent tried and tested” is less important than 80 percent right and fast.
- The ability to target and market to specific people heightens the opportunity to reach a brand’s relevant audience. And the awareness, trial, and love that follow foster a more catered, lasting relationship than ever before. In this data-driven economy, any small player can find its niche of consumers and deliver higher relevance directly than any two-dimensional brand campaign of the past. The ability to speak directly to consumers is being enabled in ways previously unforeseen and will only advance as we go forward.
PEOPLE DATA: THE FUEL FOR MEDIA INVESTMENT
For marketing, people data is the clarion call to the next generation of media investment.
People data is the personal and social-media information that is being collected every day by every transaction that we as modern human beings are making in the world around us. It is the fuel for future media investment, reinforcing the need and the requirement to adopt new marketing business models.
There are three trends that I believe will make this data infinitely more concentrated and available:
- New Legislation: New European Union laws (General Data Protection Regulation [GDPR]) in December 2015 stated it would put personal data into the hands of the individual by offering “the right to receive the personal data concerning him or her… and the right to transmit those data to another controller without hindrance from the controller.” This will mean that every person will have the ability to abstract and manage permission for all use of his or her own personal data. It also will create the unprecedented opportunity for individuals to sell their data directly to those who wish to use it for insights, advertising, innovation, and many other relationship-oriented means of marketing.
Navigating the sea of legislation will require technological and organizational reconstruction on an unprecedented scale. Every existing means of storing and using personal data prior to 2010 is outdated and must be replaced with legally compliant technology and tools to make it feasible to achieve at scale with speed.
The United States lags Europe in creating formal data legislation, but the topic in early 2016 took center stage in the debate between Apple and the U.S. Federal Bureau of Investigation over access to the iPhone used by one of the suspects involved in the December 2015 shooting at a San Bernardino, CA, social services center. The company argued that it is a bystander to the phone and could not be forced to write code to unlock it, citing the First Amendment right to free speech (computer code is formally recognized as a form of speech). The issue has had broad implications for ownership of the data on the phone that is not “owned” by the company.
- Transparency and Human Anxiety: With every new hacking front-page headline, individuals’ understanding and wariness regarding their own data potentially increases. This could crescendo as legislation and companies that answer the call for solving that problem educate the masses on what data ownership can mean—both in personal financial safety and opportunity to monetize the data. Demand for control for personal data by everyone—from governments to banks, to insurance firms to the individuals themselves will be skyrocketing over the next two years, first in Europe, then in the United States as the nation attempts to find its own solutions to this universal challenge.
- Ad Blocking: The advertising industry in 2014 contributed $3.4 trillion (USD) to the U.S. gross domestic product—roughly the equivalent of the world’s fifth-largest economy—Germany. In a marketplace that becomes almost 100 percent digitalized—integrating television with mobile, online, and everyday products (the Internet of Things)—the ability to block advertising will become commonplace, and the trillions of dollars spent on traditional media will need to find completely different avenues to the individual consumer—given his or her express permission.
Everything we’ve known about advertising for 150 years is about to change, including certainty regarding which half actually works!
A “MOMENTS”-BASED APPROACH FOR THE PEOPLE-DATA ECONOMY
A new personal-data economy is emerging and with it a new generation of marketing mavericks guided by data, analysis, and speed. These players will turn the world of media investment on its head.Marketers need to act now to build new business models, taking into account that relationship building and everyday interactions with customers will convert today’s brands from one-way communicator to three-dimensional entities in the eyes of their customers. If not, other brands will take their place in these more intimate, ongoing dialogues.
The new marketing business model construct should have a two-part focus:
- Mapping consuming behavior so that you are marketing to the moment;
- Fine-tuning that moment experience.
Mapping Consumers: Marketing to the Moment
In a typical marketing company, the process for creating an advertisement or piece of creative content is long, expensive, and involves so many touchpoints that engineering process maps struggle to capture the requirements. Marketing, advertising agencies, media agencies, media function, legal, finance, and a handful of others play roles along the way. This complexity and time lag make interactions with a consumer over multiple touches almost impossible for a single dialogue.
The future brand manager will need technology and tools that give him or her control over the relationships that he or she develops with individuals at scale. These tools will facilitate
- community management,
- connection across digital platforms,
- measurement of success, and
- ongoing recycling of findings for future use.
The tools used will range from those that drive depth of engagement for large-ticket consumer goods like cars or computers, to more mass-oriented tools that pick out a thousand or million individuals all engaging with a specific brand at relevant moments where the marketing itself becomes a value to the consumer and the brand gets an attentive, interested audience in exchange for that value. This is explicitly the notion of a “value exchange.”
As a near-term solution between the fully dynamic future and today’s annual planning juggernaut, there is an opportunity to play on specific moments in a person’s life. These are the points in life where a specific emotion or change is occurring and the individual will be more open to suggestion, empathetic content, or new ways of living life. Examples of “big moments” are
- first apartment
- first car
- heading to college
- marriage
- pregnancy
- childbirth
- first house
- kids leaving home.
The marketer chooses the right “moment(s)” for his/her brand by the relevancy to the product’s use. A brand then crafts multiple pieces (dozens, hundreds) of content and messaging suitable to who/where it wants to target its communications and relationship building. The creative content, channels for communication, and scope of interaction can be predefined, similar to traditional advertising campaigns. What becomes incredibly different is the range of applications that can take place at the right time, place, and location with the right message for the targeted consumer. It requires a properly structured brand/media team with the available intelligence that addresses the following questions:
- Who is at what “moment” on any given day?
- What is the right content available for effective communication to that individual?
- What are the appropriate limits of interaction given the specific situation of the person experiencing the “moment” within the dictates of legal or the company’s policies?
To demonstrate how this might work, consider an everyday household cleaning product that traditionally spends the majority of its annual media budget on creating a television advertisement, running it on daytime television and some primetime with many GRPs actually being aired at night. In addition, consider about 10 percent to 20 percent of the budget has recently shifted to digital banners and online video targeting women ages 18 to 52 using Facebook and Google Search as flagship platforms.
Using an approach based on “moments,” the brand might focus the digital portion of the budget on individuals engaging in the rental/purchase of a new home or apartment. As a hypothetical example, consider Joan and Todd, a couple in just such a “moment.” The intelligence on identifying new homebuyers and where they are in the journey is not big data. Instead, four or five good signals—and the data to determine which people are in the market and/or have bought a new home—is rich enough to trigger some interactions:
- Joan connects with two real estate agents through LinkedIn—she receives digital advertisements inviting her to a “community” of new homebuyers discussing the pitfalls and opportunities of the home buying adventure—sponsored by our household product.
- Todd fills out a mortgage request through a website and immediately receives an e-mail offer for consultation on choosing the “right” mortgage offer from his friends at our household product via blog and “experts.”
- Both Joan and Todd are reaching out to friends about home prices on Facebook and Twitter, and both of their Facebook feeds begin seeing our household product and how it helps prep a new home for the big move-in date.
- As the lead indicator for all “moments” in the social stratosphere, we see a friend of Todd giving him the big “Congratulations!” Tweet on the new house—which triggers the launch of coupons for the household product either by mail or e-mail.
Fine-Tuning the “Moment Experience”
Using the IP address, any phone and e-mail contact information we’ve linked and their online social profiles—including historical knowledge, messaging, and content sent to Joan and Todd—can be minutely customized or selected from a range of prepared content to best fit their circumstances. This can be done with a combination of dedicated resource and machine-learning applications built for the purpose.
As Joan and Todd end this “moment,” new individuals will enter into the brand’s target area and the cycle repeats itself in similar fashion. The approach to a person entering a specific “moment” can be well structured with e-mails or digital advertisements placed at the right time on the right channel, such as “Search” or home-selling websites in the evenings or weekend hours.
Responders can be taken through a series of increasingly engaging interactions ranging from the simple offer of a coupon to personal chat on how best to prepare or clean a new home before occupation. Once the home-buying moment ends for the consumer, then the next phase of the interaction begins for maintaining a clean and happy home with the help of the brand with which the individual has become familiar. The brand now can introduce new products based on the “trust” built over the course of the previous interactions.
CASE STUDIES
Two examples executed by major brands demonstrate the possibilities from simple to complex forms of “moments” marketing, even if not using every element of the illustration above.
A “Multiflavored” Ice Cream Strategy
One of Unilever’s top global brands was researching the relevance of its brand packaging with consumers using a social-listening platform, called Brandwatch, with a natural language processing (NLP) capability added for additional understanding of sentiment in the online discussions of the brand.
As the brand investigated the social chatter, three things—completely contradictory to traditional ice cream business lore—became apparent that would forever change the way the brand used digital advertising to run its business:
- People don’t talk about its packaging; they talk about the experience of eating the ice cream—where and with whom they are doing something. Ice cream business lore classifies ice cream as a hot-weather indulgence, where sales spike when the temperature tips 70 °F (21 °C). But for this brand, people talk about rainy-day consumption almost as much as sunny-day consumption, and the flavor of the brand is as important as the brand itself.
- People talk about this brand in a rising crescendo beginning Wednesday and running through Saturday during the seven-day week. Sales happen to follow the same exact pattern, lagged by one day (i.e., Thursday through Sunday). Doesn’t everyone in the ice cream business know that the majority of ice cream sales are an impulse purchase, made in the store depending on what is on sale? The reality: Consumers of this brand plan purchases. Price does matter, and although in-store decisions are still highly important, for loyal fans and brand lovers this is an indulgence that begins in the mind on Wednesday and increases in anticipation until eaten.
- “Everybody eats ice cream” is what the business lore (and Nielsen penetration figures) would say. In the social data, however, it was clear that specific individuals eat specific flavors, almost more importantly than the brand itself. In addition, groups of individuals have different social patterns: Some conversations about ice cream are after dinner; some are daytime; some only in-home while others only discuss social opportunities.
These new insights provided Unilever significant opportunities for fine-tuning its media plan:
- First, there could be at least three different types of advertisements, particularly in the social/search space:
- one for hot weather,
- one for rainy weather, and
- one for general use.
The execution could be dependent on the weather forecast two to three days in advance.
- Second, the media laydown could mirror the relevance to the consumer each week. Different days of the week might have different quantities of media laydown. This could provide a difference in weighting and spend levels over the course of the week more aligned with when consumers are thinking of and purchasing the brand.
- Last, but more difficult to execute, targeting advertisements at the right time of week—with even more specific content (flavor) based on social history or purchase history of the individual could take the digital effectiveness of this brand to the next level.
A Deodorant Gets Creative With Online Video
In the process of using the “moments” concept, generating creative content is a challenge. A brand’s ability to identify valuable “moments” and target segments through the right data and insights is evolving every day as the data improves, and more robust datasets are continuously being put together. Buying targeted media through programmatic buying tools already exists. Creating high-quality content and messaging—and making it personal enough to leverage in a “moments” marketing approach—still stands as a significant barrier to execution.
Lynx deodorant (also known as the Axe brand) in Brazil partnered with a new movie, “Romeo Reboot,” to produce customizable video trailers to promote the film. It cut through the creative challenge by splicing movie scenes and music on preset attributes and then allowing a computer algorithm to choose which scenes/music and narrative to run based on the viewer profile.
AdAge reported on the promotional video in August, 2015:
“The campaign, launched last month (July 2015), breaks the Axe target consumer into four segments, offering 25,000 permutations to each segment, or 100,000 in all. Working with research firm Box1824, CUBOCC (an Interpublic Group agency) segmented the target clusters—based on such factors as musical tastes, brands they identified with and other consumption preferences—into Artsy, Fresh, Naturals and Roots groups.
“Of 11 scenes in the trailer, six can vary according to the viewer’s profile. The agency validated the segmentation by serving different versions of the trailer to people in the target groups as part of a test that monitored how well people completed viewing and otherwise responded. As the campaign runs in Brazilian digital media, the agency keeps optimizing the results based on how people are responding.”
On the surface, this example overcomes the creative challenge in a programmatic media execution. But the ability to truly customize those 100,000 variations to specific individuals is very limited by Internet Protocol (IP) address, a handful of known pieces of information about that IP address (i.e., age, sex, location). In the hands of Google or Facebook, a lot more specificity could be added, but then the brand would be completely dependent on Google or Facebook for getting it right, as brands are today with their media partners. This is the game changer: Specific understanding of people, provided and permissioned for use to the brand by the individuals themselves, leads to significantly higher knowledge of who/what/when to engage and whether or not the results on a person-by-person basis were successful.
Relevance and Results
Managing ROI in Real Time
The concept of targeted marketing or customized messaging seems simply intuitive, but there is an intellectual battle raging in the media world regarding whether reach-oriented communications (e.g., television or print advertisements) or targeted communications (e.g., programmatic, digital to limited audience) make the most sense. I believe the right answer in the discussion is not “either/or” but what is relevant communication, which both forms can achieve.
For a typical television advertisement, a consumer packaged goods (CPG) company might estimate that in 1,000 views of the advertisement, one consumer will act or be impacted toward purchase of a product. The message can be general and apply to almost anyone. Cost efficiency is gained in halo impact and retained awareness for the brand on the 999 views that did not result in a consumer acting.
When we examine something simple like a digital advertisement for pet food, and we apply a relevance filter to it, however, the results can be astronomically more efficient. The simple filter of only placing the 1,000 advertisements for actual pet owners drives up the response rate to four in 1,000—a fourfold improvement on the same media investment.
Even more thrilling, if the 1,000 advertisements are targeted at one more level of specificity—a dog message to dog owners and a cat message to cat owners—the response rate goes to 40 in 1,000. Not only are we vastly improving the efficiency of media spend in this example but we also know when, where, and with whom the advertisement worked to continue the relationship.
The use of analysis to identify value advertising-media spending, differentiated from waste, is the treasure at the end of the complex map that this article has described. Return on investment (ROI) in advertising will be known and managed in real time. “Gut” feel will be needed still but for much less of the decision making. Winners will be the players who do it best, biggest, fastest, leveraging an ever-changing network of suppliers, technology, and processes.
Organizing to Compete
The idea of organizing a brand team on personal data insights and then dynamic execution—which might make the longest committed window to content on a digital platform a matter of days—is extremely foreign to most large marketing organizations.
Identification of microtargets (i.e., 1,000 advertisements to 1 million people) is not viewed as relevant because the means of marketing to them effectively, continuously is nearly impossible without good people data. If we accept, however, that robust people data will be readily available over the next two to three years, and the means to interact with an individual multiple times over a period of months or a year is available, then competition for attention will increase astronomically as these capabilities will be available widely through consolidated data formats and automated tools.
New York City-based Sprinklr already provides a tool in the online space that provides the brand marketer with the ability to manage and deliver creative content on most social platforms. The marketer then can assess the responses and manage communities of individuals within the tool to continue the dialogue.
McDonald’s and Olive Garden have used Sprinklr to see what customers are saying about them on a variety of online platforms, such as YouTube, Twitter, Instagram, Facebook, and WeChat, all on a location basis. Other Sprinklr clients include Microsoft, Samsung, Nike, and Havas, and the Internet search and review service, Yelp.
To do this work at scale, an organization must have several components:
- People data management tools (e.g., data management platforms) must be implemented to simply keep track of the data in safe, reliable ways that feed other cross-brand marketing tools and make it accessible to generate insights regarding targeting, effectiveness, and brand creative content.
- Creative management must be implemented to streamline creative decision making and to generate large quantities of creative material to meet the more specific targeting needs that specific context requires.
- Brand teams and their media agencies must be allowed to operate more flexibly and make decisions in real time based on what is occurring in the world today, rather than some predestined, annual expectation.
- Tools that give the brand team the ability to use the data, access the content, execute the media, and then evaluate effectiveness need to be implemented to bring full visibility and control to brands—tool suites, such as Adobe Marketing and Salesforce, are pushing forward in this space.
These aforementioned are significant organizational requirements that break down traditional organizational structures and require decentralized, lower-level decision making across large portions of the brand marketing investment. Although some large companies are experimenting with change, the pace of change puts them at risk against the more agile companies that start with these business models as the way of doing business.
CONCLUSION
The personal-data tsunami will be transformational for making better, faster, more targeted marketing investments, and for knowing in real time whether the investments are working.
Marketing to “moments” by leveraging the growing area of people data not only will make micromarketing at scale possible but also will open the door to personalized media execution by any size player through networks of tech, creative, and media buying. Tools such as Sprinklr already exist to put this to use for interacting and buying digital media on social platforms. This increases the competition for the consumer’s attention and requires far more relevant content, delivered in the right context to achieve effectiveness. People data and the “moments” approach to marketing will make this possible in the near term as companies adjust to the full implications of this changing media investment landscape.
Annual planning in marketing, along with the annual budget process for media, will greatly evolve to make these investments more agile and work across multiple target audiences and situations. The Unilever ice cream example is basic relative to the possibilities. Even weekly variations in advertising content and locational delivery based on weather patterns, however, need to become everyday practice. If you add good demographics, context for where and on what platform the individual is receiving the advertisement, you’ve conquered two more degrees of specificity that could increase the effectiveness of the impression up to tenfold, as the pet food example demonstrated (See Managing ROI in Real Time, page 140).
The creative process and ways companies organize to execute in this new environment are critical to success. New companies won’t have this challenge. They can build brand organizations from scratch that optimize the use of people data to build strong relationships and brand equity with consumers while large companies suffer market share losses.
Ultimately, we are describing forces that will cause seismic shifts in the ways the media investment and brand marketing work. The challenge to all the existing players is how fast and how well they adapt if they want to remain competitive in such a dynamic business environment.
The Advertising Coalition (TAC) and research firm, IHS Economics and Country Risk per the report, “The Economic Impact of Advertising,” March 2015. Retrieved from http://www.ana.net/getfile/23045
The gross rating point (GRP) measures reach multiplied by frequency, a metric used within traditional platforms but also increasingly within digital platforms.
An Internet Protocol (IP) address is a numerical label that a computer, tablet, printer or other device uses to identify itself and communicate with other devices in the IP network.
Example results provided by Pixoneye in work with a large pet food manufacturer.
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