Knowing what types of data and tools consumers are using should inform advertisers to reallocate marketing resources to better match new shopping behaviors.
Don't flatter yourself. Marketers aren't the only ones leveraging data to increase relevancy and efficiencies. The average consumer has gotten pretty adept at data analysis as they waltz through a dance floor filled with amorous brand and retail suitors. Today we live and shop in a world complete with real-time features, experiences, and tools that empower consumers to compare dozens of shopping sites, predict whether prices will go up or down, filter out merchants by reputation scores along multiple dimensions, and accomplish these tasks all within seconds or minutes. In this new "real-time" world, both buyers and sellers use data and analytics to further reduce the transaction costs of e-commerce. As a result, advertisers and brands have to quickly become more sophisticated real-time marketers – or they won't be able to compete for increasingly savvy shoppers armed with digital tools of their own.
Shopping search engines, online researches, rating services, and social networks are increasingly providing new data-driven tools to help consumers find and select merchants, brands, and product offers. Businesses adapting to these technologies to become more visible to consumers will likely be more successful. For example, an online tax preparation software compared my data to people in the same income group and suggested that I think about investing more in an IRA and donating to charities to lower my taxable income. Another tool I've used recently recommended better credit card and checking account offers based on the patterns of my transactions. These smart marketing features provide consumers useful information thus boosting an underlying brand loyalty.
Brands only have seconds to make their best offer to the right people at the right places. Once you miss that real-time window, chances are you've missed the consumer. Take display advertising as an example, where the utilization of ad exchange inventory and audience targeting is becoming a growing trend. As consumers use these tools to leverage real-time features, marketers will have to follow suit and focus more heavily on the right ads and messages, for the right person, at the right places.
Buying the right audience in real-time is just the first part of the equation. Getting the right message to them in the right places is just as critical. Just as good website content enhances the brand with borrowed brand equity and consumer loyalty to the site, an inappropriate website or page content could easily negate or destroy that relationship. In other words, contextual signal is another form of data. Savvy consumers expect savvy ads that are well-placed temporally and spatially. Contextual, demographic, behavioral, and social graph-based ads all infer consumer intent and optimize ad placement with more data.
Knowing what types of data and tools consumers are using should inform brands and advertisers to reallocate their marketing resources to better match new shopping behaviors. The more consumers engage with online tools, the easier a marketer can optimize, increase relevancy, and ultimately drive ROI (define). In the end, this is a win-win for both the buyers and sellers. Consumers get to choose more intelligently, while marketers reduce waste and see better performance.
If more and more advertisers lean towards buying audience rather than just content, perhaps yet another evolution on this theme will put consumers directly in the control seat of smart marketing and advertising tools. Stanford University's cryptology group is experimenting with a browser plug-in that is already moving in that direction – albeit for a different motivation. Letting consumers configure what kind of smart ads they want to see based on client-side tools that analyze their purchase transactions might be another form. If designed and built carefully, these tools can ensure a new level of consumer trust and engagement.
In a real-time world, marketers and consumers do a tango with data. Understanding the give and take of this partnership will make for more effective advertising for the marketer and more valuable experience for the consumer.
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As Chief Technology Officer at Turn, Xuhui Shao focuses on the power of optimization, machine learning, and advanced analytics solutions in driving new business models, products, and services across all industries. Xuhui is responsible for architecting the machine learning and optimization technology to deliver the most effective data-driven digital advertising in the world. He is passionate about the dynamic online advertising community and works closely with industry leaders developing data transparency and consumer privacy protection.
For the last 12 years, Xuhui has practiced research and development in machine learning, statistical theory, and computational intelligence for Fortune 100 companies in various industries from banking, finance, online retailing, healthcare, insurance, marketing, and online advertising. As the lead inventor and co-inventor of three awarded patents in the areas of advanced analytics and optimization, Xuhui is a recognized expert in harnessing data and transforming analytics into actionable insights and optimization strategies.
He earned his bachelor's and master's of science degrees from Tsinghua University, Beijing, and his Ph.D. in electrical engineering from the University of Minnesota.
Gartner Magic Quadrant for Digital Commerce
This Magic Quadrant examines leading digital commerce platforms that enable organizations to build digital commerce sites. These commerce platforms facilitate purchasing transactions over the Web, and support the creation and continuing development of an online relationship with a consumer.
Paid Search in the Mobile Era
Google reports that paid search ads are currently driving 40+ million calls per month. Cost per click is increasing, paid search budgets are growing, and mobile continues to dominate. It's time to revamp old search strategies, reimagine stale best practices, and add new layers data to your analytics.
June 10, 2015
12:00pm ET/9:00am PT