Big data – What every marketer needs to know

Here is a first for me: while I do share my presentations here on the blog, I usually upload the slide set after the events, only.


This time, though, I am doing it the other way around. Below is the slide set for a presentation that I am doing at the Oxford Brookes University Business School as part of the ‘Contemporary Issues in Marketing‘ series. It is a 45 minutes talk, pitched at an introductory level.

I would be delighted to hear your thoughts. What other aspects must I cover?

Do you have a personal anecdote that you would like to share with the audience?

6 thoughts on “Big data – What every marketer needs to know

  1. Hi Ana

    A good source of anecdotes is from Rick Smolen

    ie Marissa Mayer to Rick Smolan: “Through #bigdata the world is developing a nervous system.Can analyze, visualize, respond in #realtime”

    “Data will grow because no one throws anything away… Ever!”

    The experts at SVCO talked about the picture being built up of measurement points.

    In practice Big Data is built of three components:

    Sensors Infrastructure -Clouds Storage.

    The phone will be the biggest access/connection point for sensors.

    The companies that are very good at Big Data are Google, Apple, Amazon and Facebook – but they are using it for their own internal use.

    The big opportunity is in mining unstructured Data – there is a distinction between behind the Firewall (structured) and outside of the firewall (unstructured).

    People who are good at this are Splunk and Meltwater. See NEST Labs for home automation – t Apache Foundation also making an impact via Hadoop – but its only a start…

    There is an authoritative report produced by McKinsey – you will find it here:

    Warnings from the experts at SVCO:

    “The smoke is still coming out of the starter-pistol barrel and we have barely taken the first step” Beware of experts – its all emergent.

    “Sentiment Analysis is the “leg-warmer” of big data – its just a fad – overrated”

    “The technology that raises the privacy concerns will also develop the ability to mitigate those concerns”

    Watch out for

    Hopefully some of this is helpful 🙂



  2. Hi Ana,

    This whole Big Data debate seems to be focussed right now on handling the data: how to capture it, how to store it, how to treat it. I’m hearing very little about how to get insights out of it; apart from getting a sentiment out of a social media stream.

    Almost all technology looks towards parallel processing as a solution. Quite often statistical analysis is used as a means to create insights. The parallel processing may work perfectly to operate a statistical model, but I’m not sure that parallel processing is ideal for creating a model. Does that mean we’ll be working on samples? How do we sample? I don’t see a lot of discussion on the analysis aspect.

    I’m very curious to see if people will remember the data warehouse hype of the 90’s and look at creating insights and applying those. In the end, value is only created at contact with a (paying) customer.

    Any thoughts on this?




    1. Thank you, Steven. Yes, valid points too. I have already included something about the representativeness of this data, but now I added something specifically about sampling issues. Thank you.

      And made a mental note about the hype surrounding sentiment analysis (your reply, and James’s).

      Thanks, again, Steven. Really great help.


  3. Cloud computing makes the whole technical challenge of big data more accessible and affordable. Some systems enable to automatic collection and correlation of unstructured data (social) with transactional and market segmentation data.

    Therefore, the concept of ‘Big Data’ is now a practical reality in part and the value it delivers is nopw working in areas such as customer service and online influencer and community marketing.

    Perhaps you would like to be a guest speaker at a webinar and or seminar on the topic?


    1. Hi Paul – sorry for the delay: your comment went to the ‘spam box’!

      I do have some reservations regarding the automated analysis of data, though.

      PS – happy to talk about the webinar / seminar.


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