Data Analytics

Prescriptive Marketing Analytics: Strategy into Action

06/04/2016 By debkr

A quick refresher on the three kinds of analytics:
1. Descriptive: collects data which describes customers’ past actions and behaviours, and analyses it to try to find patterns which explain that behaviour;

2. Predictive: takes the historical descriptive data and patterns contained within it and uses that to try to predict what those customer might do in the future;

3. Prescriptive: takes a more strategic approach and uses data, trends and predictions about customer behaviours to help inform recommendations on actions (such as process changes, changes in marketing tactics) which might help change the customers’ behaviours and move the company closer to achieving it’s business goals. [Read more…] about Prescriptive Marketing Analytics: Strategy into Action

Predictive Marketing Analytics: Insights and Inferences

02/04/2016 By debkr

In an earlier post we took a look at how we can measure and track customer behaviour with the descriptive branch of customer analytics. Now let’s turn our attention to predictive analytics, where we use that data to generate insights and infer possible future outcomes, e.g. what ways are customers likely to have behave in future, based on what they did in the past.

Source data:
The wide array of data which could possibly be collected from a consumer includes a whole variety of different things. Firstly, the ads or other marketing/promotional pieces they viewed (including where and when). Second, the promotional offers and other communications they received (including the media by which that communication was made e.g. online, by email, by mail). Third, any actions the customer took – including the [Read more…] about Predictive Marketing Analytics: Insights and Inferences

Data Visualisation: Network Graphs (work in progress)

20/03/2016 By debkr

The following is inspired by (and based loosely on) a tutorial by data journalist Clara Guibourg: Network analysis of a Twitter hashtag using Gephi and NodeXL (hat-tip @KirkDBorne), worked up in a ‘Heath Robinson’ fashion since I don’t currently have Java or MS Excel installed on this laptop. (Java v.7+ is required to run Gephi, “the leading visualization and exploration software for all kinds of graphs and networks”; and, without Excel, not much use in trying to run the NodeXL Excel 2007+ template “that makes it easy to explore network graphs”.)

Graphs don’t just come in curves:
A standard Cartesian graph consists of a set of (x,y) co-ordinates (the points or vertices on the graph) and the relationship (the edges, arcs or lines) between them. The result is the graphed line, which may be also expressed as some algebraic function specifying the relationship (for example, in its simplest form: y = x). [Read more…] about Data Visualisation: Network Graphs (work in progress)

Most Influential Data Scientists (Two Lists)

20/03/2016 By debkr

While I was busy playing around with how to do a data visualisation on Twitter’s most influential data scientists, @kdnuggets went and posted this blog post about the exact same subject (dated 2012). But that’s cool, cos it saved me a bit of a job… (although I still need to do the learning exercise anyway, and update it to the list of influencers today, so that project’s still a work in progress).

The Twitter list (2012):
But in the meantime, here’s the list as produced by Gilad Lotan (@gilgul) based on Twitter bios containing relevant keywords (original post here) – the bios shown are taken from current Twitter bios: [Read more…] about Most Influential Data Scientists (Two Lists)

Digital Marketing (Web) Metrics

19/03/2016 By debkr

Let’s take a first look at the branch of Marketing Analytics known as Digital Marketing Metrics (or Web Metrics), which sit within the category of Sales Metrics (see earlier posts here and here). That is, they relate specifically to sales, and their measurement and improvement leads to increased sales revenue for the business. They are also a kind of Dynamic Metric: one which is likely to change significantly in a short timeframe (within one month or less), and one which can be significantly impacted in the short term by actions the company can take now. For example, making small tweaks to the customer journey through the website may increase additional purchases, or shortening the number of steps, and hence time to checkout reducing cart abandonments, and so on. [Read more…]

How Data Becomes Knowledge

18/03/2016 By debkr

Data questions and data analysis:
The journey from raw data to actionable knowledge takes us through various stages, each with a different kind of question we can ask of and analysis we can perform on that data, ranging from the simplest through to the very complex. But it will always begin with the question.

Descriptive analysis
This is the simplest kind of analysis, which describes some event or data set in order to get a better understanding of what has happened (descriptive step) and why it happened (interpretive step). This kind of analysis won’t be used to generate decisions as its difficult to generalise from the descriptive data, but is used instead to support understanding. [Read more…] about How Data Becomes Knowledge

Finding My Ideal Job

16/03/2016 By debkr

Growth Analyst
TransferWise
London

Job description
TransferWise is the clever new way to move money between countries. Co-founded by Skype’s first employee and backed by some of planet’s most experienced innovators, including Sir Richard Branson and PayPal founder Peter Thiel, we’re disrupting the world of international money transfer. That means flipping a gazillion dollar industry on its head and taking power away from banks and the establishment. [Read more…] about Finding My Ideal Job

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