Monthly Archives: October 2014

Together Ibiza, would this email marketing make you want to go back?

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I recently received an email from Together Ibiza trying to entice me to go back to the white isle for the summer of 2015. The way Together Ibiza tried this was by emailing me a teaser promotional video of what the trip would be like. For this email there was no personalisation, not even a hello Jordan. It was simply just an email with the video and then links to their Facebook, Twitter and Instagram pages.

 

I watched the the promotional video and indeed it did make me want to go back to Ibiza. The imagery of the video definately worked on me and all I had to do to watch it was to press play. There was no uneccessary jargon within the email that could of made it longer and possible lose my interest.

According to Ellis-Chadwick & Doherty, pictures help engage the readers and sustain attention. And interactiveness can lead to more information processing and increases user involvement. This is definately true within the Together Ibiza email, once the video is complete there are links for other Together Ibiza videos. So this gets more click throughs.

The only way this email could of been improved is if it was more personalised to the recipient. But all in all this video makes me want to go back to Together Ibiza.

Reference

Ellis-Chadwick, F., & Doherty, N. F. (2012). Web advertising: The role of e-mail marketing. Journal of Business Research, 65(6), 843-848.

Data science and it’s relationship to data driven decision making

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Hello world of blogging

I recently read an article by Foster Provost and Tom Fawcett about data science and their fundamental concepts.

Data science is a set of fundamental principles that support and guide the principled extraction of information and knowledge from data. So let me give an example to make sense of this. Walmart is currently the largest retailer in the world and as such they have extensive shopper history data. They are able to use historic trends to be able to predict outcomes following a series of events. For instance if we look at the recent earthquake in America, Walmart can use their historic data to predict what trends are likely to happen following the disaster. This is particularly useful as Walmart can stock more of what is needed in particular stores, they can analyse the demographic trends to ensure the necessary items are stocked in relevant stores. So data science allows for Walmart to take advantage even following a disaster.

If we can now look at how other businesses can take advantage of data science. If a new youtube video maker wanted to increase his fanbase, he could use data science to identify what time of the day has the most youtube hits and shares, and start to upload his videos at that time of day to take advantage of the increased popularity surge.

I hope this helps you understand data science a little more, more blogs to follow soon.

Watch this space

Hello world!

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