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Alexis Hall

Big Data: What Marketers Need to Know – #SESSF Bryan Eisenberg

By Alexis Hall     Online Marketing, Search Engine Strategies

Big data is definitely a buzz word within the industry right now, but as I headed to Bryan Eisenberg’s (@thegrok) session at SES San Francisco, I wondered how the average company would be able to leverage the complexity of big data in a way that is meaningful and profitable.

Target made headlines last year when it inadvertently announced to the father of a teenager that his daughter was pregnant, by sending her coupons targeted to her pregnancy. Target knew that this young woman was pregnant before her father did, through the collection and analysis of data related to her past purchases. Although Target would later refine their coupon targeting strategy, this is a powerful example of a company using data in order to speak to the needs of their consumer.

We are all aware that the Internet has facilitated an explosion of data. We are creating and consuming more data now than we ever have in the past. So what exactly do we mean by big data? In order to be considered big data, it must meet three criteria:

  1. Volume
  2. Variety
  3. Velocity

The classic example of a company which has used big data well is Amazon. In the very early phases Amazon used big data, sometimes badly, for personalization recommendations. Now their big data model is quite sophisticated. They still leverage data for personalization and recommendations, but also for coupon offers, warehousing, and shipping decisions. One of the main advantages Amazon has over other companies is their agility. On the day Michael Jackson passed away, they reconfigured their whole MP3 store within 2 hours. Think of how much revenue they were able to capture in those first hours, while other companies were still figuring out how to react.

Big Data Challenges

Companies are concerned about the data explosion. As CMOs try to figure out how to deal with all the data at their fingertips, there are three big challenges they are facing:

  1. People
  2. Process
  3. Tools

Since there are already many great tools out there which will help companies leverage big data, Bryan suggests that finding the right people and processes in order to use big data will be the biggest challenges for companies moving forward.

According to Bryan the four main types of big data marketing tools include:

  1. Analytics tools
  2. Predictive analytics tools
  3. Data driven automation tools
  4. Adaptive learning and automation tools

Four Tools to Leverage Data More Effectively

1. OneSpot

50% of people who are online are looking for more content. OneSpot targets these users by offering targeted content banner ads based on user data.  This tool offers sites the opportunity to use third party content in order to engage audiences and drive traffic to their site.

 2. DataPop

There are 50,000 ways to advertise your inventory. DataPop aggregates all this information in order to create relevant ads, which according to their site, people love to click on. The foundation of success for these ads is that the data links customer intent to content, in order to ensure users land on the right content.

3. BloomReach

BloomReach is a marketing tool which uses big data in order to dynamically route and optimize landing pages in order to target what the user is looking for. For example, a user submits the query pink lace dress and a category page is dynamically created titled ‘pink lace dress’ ensuring the user finds exactly what they are looking for.

4. Runa

Looking at over 90 variables, like mouse clicks, time spent on site, buying history etc., Runa determines which special offer will create maximum benefit for a company’s profit margin.  Tests show site-wide offers, lost 10% + in margins to achieve 8% increase in sales, whereas Runa’s personalized offers gave up ~3% in martins to achieve ~19% increase in sales.

With the tools available today, any company, both large and small, can begin to use big data the way that Amazon does, in order to deliver extremely targeted, contextual results to consumers.

7 Steps for Big Data Success

Before you get started leveraging big data, let me leave you with 7 tips for big data success from Bryan Eisenberg.

  1. Don’t get caught up with the hype and jargon
  2. Identify the questions and problems you need to solve
  3. Map valuable data inside & outside your organization
  4. Prepare your organization to see the new landscape
  5. Share case studies of other successful uses of big data
  6. Looks for updates around automation and “Black Box” technology
  7. Always remain open to experimentation

The old marketer’s motto was: “The Money is in the List!” This motto becomes less relevant today as it becomes less realistic for companies to keep track of all their customers and prospects the way they once did. Instead the marketer’s motto is evolving to be “The Money is in the Data.”

How is your company leveraging big data now? And how can it use it more effectively in order to generate revenue?

 


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