“Big data” has become a catchall term for the vast amount of information generated by our digital lifestyles, and the analytics techniques for dealing with it all to improve marketing, products, and business intelligence. It’s become very fashionable to decry the value of “big data” for marketing, with many pundits and consultants calling it “no big deal.”
I believe in “big data” just like I believe in the power of all data to transform our lives. Just look at the powerful applications already emerging in healthcare, world hunger, global economics, and even for those for whom hockey is more important than life itself, sport competiveness.
The opportunity in marketing and business intelligence is just as strong. Our digital lifestyles generate a tremendous amount of personal and behavioral data – in fact, IDC estimates that by 2020, the number of commercial transactions on the Internet (both B2B and B2C) will reach 450 billion per day. McKinsey forecasts that demand for “big data” in the U.S. will create up to 190,000 high-paying jobs requiring deep analytical skills by 2018.
Used responsibly, all that data has a very meaningful impact on our lives and the economy. It’s time to clear up some of the myths surrounding big data and what it can do for marketers.
No. 1 Myth: “Big Data” Has a Universally Accepted, Clear Definition
Truth: Not so! Lots of people have trouble with what criteria to use in defining “big data.” That makes it easy to use in all kinds of contexts – including contexts where another term might be more appropriate. Size alone is not big data, but also scope and how it’s processed. Akamai analyzes more than 75 million events per day to better target advertisements.
To help you form your own internal definition, “big data” is usually thought of in these terms:
- The dramatic increase in the quantity of data available to be stored and analyzed in today’s economy.
- The inclusion of “unstructured” data (meaning it is non-numeric, “free-form,” qualitative data such as text, video, social content, and click-stream patterns), which requires sophisticated new data extraction and analytic techniques in order to be usable for business purposes.
- The growing role of automation in the use of data, e.g., creating and delivering marketing messages in real time.
No. 2 Myth: Big Data Is New
Truth: While the sheer volume of data available in this day and age, and our ability to process it at a high level are certainly new, the concept of correlating and analyzing vast volumes of information is certainly not. For example, huge cross-references of every single word used in the Bible, called “concordances,” were in use by scholar monks for centuries well before the first databases.
No. 3 Myth: “Big Data” Means “Big Marketing”
Truth: Often the most effective uses of big data are not bigger marketing, but leaner, more efficient marketing. The biggest challenge now is to wrestle big data down into actionable insights. Understanding the full experience means managing data from many sources, in many formats (like transactions, social sentiment, online behavior), and often in real time. A hotel company wants to both improve the spend during each visit, and increase the number of visits per year. Competing offers must be corralled and messaged in the right context. You can’t do that at any kind of scale without effective marketing analytics.
While the use of data in marketing is universal, spending on “big data” is not yet pervasive. An estimated $11.4 billion was spent on big data investments in 2012. Of this, over $3 billion was spent by Google, and over $1 billion was spent by Facebook.
No. 4 Myth: Bigger Data Is Better
Truth: As with many things in life, bigger doesn’t necessarily mean better. Data on its own can’t tell us anything. The key is in having smart people who know your business and objectives to interpret it. Most marketers have to make trade-offs between promotions and budgets all the time. A financial services company with 50 to 60 products to sell uses marketing analytics (sometimes even “big data”) to decide which offer to present in which channel. A publisher will use the same approach to speak with each individual subscriber in a personal manner – with content, advertising, and placements that make sense for each.
No matter the industry or market share, marketers everywhere are stewards of consumer data. It is our actions and abilities (and care and attention) that enable brands to responsibly use all the data we have (big and otherwise) to delight customers, and engage them with our brands.
No. 5 Myth: “Big Data” Will Dictate Your Marketing Approach
Truth: Data – any and all of it – will only inform, not drive your marketing strategy. The “net best offer” trigger is one of the most powerful in email marketing. Automation makes these timely and actionable. However, the whole data-driven approach falls apart if there is no human element – the selection of the offer has to make sense, be respectful, and march in tune with the brand symphony.
There is magic in the connection between consumers and brands, and data enables and speeds those connections but does not define them. Consumers regularly connect with each other over brands, so marketing analysts and strategists seek to understand the role of the brand in those interactions. Similarly, a fashion brand will use the data to come up to the moment of truth with a customer – but it’s the creative, content, and context that creates a “wow” experience that closes the sale and builds loyalty.
At the end of the day, big data is meaningless – as is small data or any other form – if it doesn’t help us create more meaningful and relevant customer experiences. Our data-driven lifestyle is so ingrained today, that we hardly notice what marketers make happen – like recognizing me when I check into a hotel or airport, or sending me offers for things I regularly purchase (or might like to try), or helping me connect with friends over a common interest. The responsible use of data in any organization is about making those connections between consumer-brand and consumer-consumer.
What are your “big data” truths? Please share in the comments section below.
Image on home page via Shutterstock.
Editor’s Note: As 2013 comes to a close, we’re pleased to share our top marketing automation columns of the year. This article was originally published September 16, 2013.
The advertising industry, like many other industries, is abuzz about “AI” and “machine learning”. This post covers some of the most promising aspects of the technology, some things to watch for, and finally what that means for your media plans.
Recently, I visited my alma mater, University of Florida in Gainesville, FL, to speak with advertising students about digital marketing, analytics and how to start a career in our field.
Sandy Rubinstein is the CEO of the independently female minority-owned marketing and advertising firm DXagency. ClickZ caught up with her to find out about her role as CEO, and what advice she would give to women who want to work in the digital industry.
Effective app marketing is not about generating app page traffic, but rather about ensuring your app is discovered by targeted and relevant users who will install your app and use it regularly.