qSpray and prayq tactics should be long gone for big data analytics

James is editor in chief of TechForge Media, with a passion for how technologies influence business and several Mobile World Congress events under his belt. James has interviewed a variety of leading figures in his career, from former Mafia boss Michael Franzese, to Steve Wozniak, and Jean Michel Jarre. James can be found tweeting at @James_T_Bourne.

In times when marketers have access to multiple sources to collect data and insights about their customers, it seems surprising that many business don’t know how to use these assets to better target their audience online.

Email marketing is one of the oldest tactics used by marketers. However, its evolution has been slow and many businesses continue to rely on “spray and pray” strategies that in many cases, stopped working a long time ago. Sending out thousands of emails in hopes that someone will bite is not effective and can be a gigantic waste of money.

Luckily, big data analytics effectively removes the need for any guess-work or random marketing ploys and enables companies to better focus their campaigns, re-target, improve content and increase engagement.

Data can make or break a campaign

Information gathering and sorting is easier now than it has ever been before. Companies such as Google, Amazon, and Facebook have built their businesses around personal data, and now they track everything from what we buy, to the sites we browse, to our likes and dislikes, to increase the value of their businesses.

For instance, Amazon has a gigantic database filled with their customers’ past orders, items they’ve viewed, and items they’ve expressed interest in by sharing them on social networking sites. The fact that they have this information is only part of the equation. The way Amazon uses the data is what makes their tactics so effective.

With the information they have, they are able to send highly targeted emails to each one of their customers with items that they are likely to buy. Also, when you sign into Amazon, you have likely noticed the “New for You” and “Recommended Based on Your Browsing History” sections. All of these simple but effective methods are made possible because of Amazon’s use of big data. According to Rob Salcowitz, author of Comic-Con and the Business of Pop Culture, “Amazon will keep widening its lead over everyone else by applying exactly the right pressure at exactly the right moment in the buying cycle to maximize convenience for their customers”.

Imagine if Amazon didn’t have this information. They would be forced to only send out generic emails that might or might not contain products that are relevant to each customer. There would be no personalization in their marketing efforts and as a result, they would not be nearly as effective as they are.

Break out of the small data mindset

As I mentioned above, companies like Facebook are largely successful because they realize that data is valuable. The companies who have refused to adapt and continue to strictly rely on their “gut” and intuition have either disappeared or are on a downward spiral.

Consider the issues Blockbuster has had due to the rise of Netflix, Redbox, and other services. For years, Blockbuster had an opportunity to utilize the records gathered from customers who rented movies and videogames from them. However, they were too slow to realize the transition that was taking place.

Along came Netflix, which made use of their customer database tremendously. According to GigaOm, Netflix uses Big Data to spot opportunities by looking at 30 million “plays” a day, tracking four million ratings by Netflix subscribers, three million searches and the time of day when movies or shows are watched and on what devices. This information allows them to select their programing smartly by knowing in advance which actors are the most searched or how many views a trailer gets.

But, companies that rely on big data have multiple sources to get insights from, and not just what they collect on their website. Big Data is big because it´s rich and diverse, putting together thousands of data sources that when crossed and analyzed can bring up consumption patterns impossible for a human mind to spot.

Using data analytics is easier than ever

With all of the tools and technology available today, it’s almost unacceptable for companies to use “spray and pray” tactics. Implementing a database such as MongoDB as a Data Hub allows companies to store, process, and serve data to other applications. Also, with more and more students graduating college with degrees in computer science, IT, network systems, and other related degrees, companies will have no problem finding talent that knows how to properly use big data.

Even better, most infrastructure providers can help companies get a better understanding of big data and how to implement an efficient, cost-effective database solution.

The perks of big data analytics have completely revolutionized the way that companies operate. Service has become more personal and customized to fit the individual needs of customers. The email newsletters that were once thought of as strictly spam, are now actually helpful to customers and increase the likelihood of their making a purchase as a result of big data analytics.

Author Byline

Matt Asay is Vice President of Corporate Strategy at 10gen, the company behind MongoDB NoSQL database. With more than a decade spent in open source, Matt is a recognized open source advocate and board member emeritus of the Open Source Initiative (OSI).

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