Rise of the analytical consumer
564 days ago
 

Passive no more: All hail the rise of the analytical consumer [INFOGRAPHIC]

IBM has released a report suggesting the evolution of the consumer as an informed and analytical agent rather than simply a passive entity looking to be chauffeured along the zipping highways of the interwebs.

Big Data has been a buzzword for several years now in a world dominated by endless streams of online information. “Information overload,” and strategies for managing it, have been very popular in the past few months: Fast Company, Wall Street Journal, and The Guardian have all approached the issue.

Yet the concept is nothing new – futurist Alvin Toffler first popularized this term in his 1970 book Future Shock, which looked forward to how technology would change individual lives and coping strategies. The term was actually introduced 6 years earlier by Bertram Gross in his book The Managing of Organizations, where he defines information overload thusly:

“Information overload occurs when the amount of input to a system exceeds its processing capacity. Decision makers have fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur.”

What’s especially intriguing here is that, just like computers, consumers are learning to digest, parse and analyze heaps of data into more manageable chunks of actionable information relevant to them. Devices are becoming more sophisticated as well, providing utility and UX that allow users to more quickly digest and act on the most important information at any particular moment.

In fact, IBM’s research shows that a majority – 62%, a surprisingly large figure given the prevalence of information overload content – said that the internet and social media has actually made decision making easier.

The “information overload” and “paradox of choice” that are often pointed to as major drawbacks of the Internet age, is actually a positive thing for a majority of respondents.

The research also revealed the following trends:

  • Broadcast mediums, such as television and radio, are 5x less influential on decision-making than online sources.
  • 18-24 year olds are 2x as likely to use social media for research as 35+ adults.
  • Grammar rules in user reviews: 40% of 18-24 year olds are influenced by poor spelling and grammar.
  • Ease of access still wins out over style – 58% compared with 24%.

Vivian Braun, IBM’s consumer analytics expert, believes that the oft-discussed “information overload” is actually being managed surprisingly well by digitally savvy consumers.

“This research shows that, rather than struggling to deal with information overload, modern consumers are proactively using the abundance of data sources available to them to be more savvy about the decisions they make. In particular, the upcoming generation of consumers are very comfortable with jumping between multiple sites and forums, polling opinion and cross-referencing information to research everything from their latest music download to their next job.”

The essential aspect of this jumping between information sources is that consumers are much less brand-loyal and more apt to use whatever source offers the right mix of intelligent user interface, usefulness for the task at hand and compelling content.

“If businesses want to develop personal relationships with their target audiences – and they absolutely should do – then they need to understand what’s influencing their decision-making. To do this, the use of tools such as social media analytics – which enable companies to derive real-time insights into consumer preferences and drivers of behaviour – will inevitably become more widespread. Ultimately, as consumers get more analytical, so must the companies and organisations they interact with.”

It could be that the age of the “consumer as overwhelmed individual that needs hand holding” is segueing into the much more amorphous – and challenging – concept of the “consumer as knowledgeable agent of their own destiny with less patience for clunky, time-sucking solutions.”

Consumers want fast and fun tools that get the job done efficiently and enjoyably. Could it be that this new age of the consumer is why we see many nimble customer-centric startups gaining traction on established behemoths that might not give enough credit to consumer intelligence?

 

 
 
Nick Vivion

About the Writer :: Nick Vivion

Nick Vivion is a reporter for Tnooz, based in New Orleans, USA.

His passion for travel technology led him to travel around the world shooting travel videos for Current TV and Lonely Planet TV in 2006 and 2007.

He shot on Mini-DV, edited on a white MacBook, uploaded and shared online as he traveled. His moxie for travel video has resulted in over two million views on his YouTube partner channel.

In addition to travel, Nick co-founded of one of the web’s most talked about LGBT media sites, Unicorn Booty, and has gone "blog-to-brick" with a bricks-and-mortar restaurant called Booty's Street Food in New Orleans – serving street food from around the world.

 

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  1. TO

    No link to the study? When was the study?

     
  2. bob sacco

    Good article Nick.

    You have established the bridge as to why online marketers need to employ a quantified approach to determining whom their customers are and will be in the future.

    I paraphrase your above comments , “modern consumers are proactively using the abundance of data sources available to them to be more savvy about the decisions they make…..upcoming generation of consumers are very comfortable with jumping between multiple sites and forums, polling opinion and cross-referencing information to research everything from their latest music download to their next job.”

    Nick your article makes the case for online marketers’ need to mine their own 1st party customer data using predictive analytics to even the playing field. The insurance industry has been successfully doing this for years. Insurance companies make their profits by predicting outcomes of their customers. It’s about time e-commerce online marketers do the same and become more efficient and profitable.

     
    • Nick Vivion

      Nick Vivion

      That’s a very interesting approach for online marketers to take. How do you suggest that online marketers approach mining available data to predict behavior? Insurance companies have a data set that shows outcomes from similar customers, so can put a percentage probability that a new customer with identical characteristics will experience the same. What data would help online marketers do the same?

       
      • Vivian Braun

        Hi Nick and Bob,
        Belatedly, a comment to the thread on learning from the insurance industry. That’s a good example, insurance companies are heavy duty users of advanced analytics, primarily driven by the need to understand and manage risk. Online marketers have click-streams available for analysis of browsing patterns, basket abandonment, response to prompts etc, which they can correlate with customer profiles and purchasing behaviours. Applying predictive modelling, this all provides great input for personalised offerings… even in real time, as the system detects the customer’s browsing steps and adapts the offering accordingly, based on the historic patterns.
        By the way, I recently met with a leading provider of insurance comparison services – they stored years’ worth of web click streams, but hadn’t got round to analysing this wealth of information for a better, individualised design of the web site and the services offered, so even the insurance industry may find that there’s room for improvement!

         
        • bob sacco

          Yes Vivian I concur. Though, there are major issues with companies currently offering online predictive analytics for marketers. 1) they are NOT designed by insurance actuaries whom are the most qualified and produce the most accurate outcomes. 2) They usually are NOT prescriptive. That is, they may point to a trend but do not specifically prescribe a specific action to be taken by the marketer in order to produce the desired action. This combination produces powerful results. If you are interested in learning more visit Actucast [dot] com.

           
          • Vivian Braun

            Indeed, Bob, predictive + prescriptive is a strong combination, where you combine the analytics with the defined business rules, and automate the execution.

             
  3. Liz

    “Grammar rules in user reviews: 40% of 18-24 year olds are influences by poor spelling and grammar”- LOL

     
 
 

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