Copy
View this email in your browser
Digital Analytics Hub
Aloha Hubbers,
 
For years organizations have been collecting customer level data. Whether through CRM programmes, store loyalty cards, credit card transactions; some of us have been injecting customer IDs into our digital analytics tags to enhance our datasets.

Tesco’s Clubcard loyalty scheme is a prime example of using customer data to optimise product offering. By mining the data of millions of UK customers' purchase behaviours Tesco was able to profile its customer base and identify significant revenue opportunities. Did you know that the Tesco Express store concept was borne out of research conducted on the Tesco Clubcard data?

Tesco identified that many of their customers made a big weekly purchase at their local megastore. However, they never supplemented essentials such as milk, eggs and bread during the week in that store. Instead they were purchasing these goods elsewhere. So there was an opportunity to provide such a service in smaller format local stores.

 The Tesco story is one of utilising data mining and predictive analytics at a large scale to great success. However, rarely do we use these techniques for digital analytics.

Is that because of digital analytics doesn’t lend itself to using such techniques or do we lack the necessary skills to apply those techniques? Perhaps it is a tool issue – how come none of the most common digital analytics tools offer these capabilities?

Dan Grainger who leads travel giant TUI UK’s analytics and optimisation efforts argues that statistical and predictive modelling features such as automated insights and cluster analytics are becoming increasingly more accessible to digital analysts. You only have to look at product roadmaps to see that more predictive and mining features are on the way.

The situation poses big questions. Do we already have a need for such analytics capabilities? Are they being adopted by analysts or simply left to gather dust? Are we able to learn these new features “on the job” or do we need to reskill? Are they potentially game changing?

At the DA Hub, Dan will invite delegates to bring forward their views and opinions in his I Predict… roundtable discussion. Together we will compile a picture of where digital analytics is moving and how we could better use emerging tools to improve business value and customer satisfaction.

Oh and you could also come talk to Tesco about how they are mining their digital analytics and applying it to their digital optimisation.

If predictive analytics and data mining are a key interest then you might also want to check out discussions such as Anna Denejnaja’s (Head of Analytics, Hermes) Applying Data Mining in Digital Analytics, Gary Angel’s (Partner, Advanced Analytics, EY) Exploring Machine Learning for Digital and Carmen Mardiros’ (Head of Digital Analytics, navabi) How to Forecast When Factors Keep Changing.
 
We predict you won’t be disappointed.
 
There are only 17 places available at each discussion and they are going quickly. Book your place today to confirm your place at the Hub and at these discussions.

Join senior leaders for Accenture, Allianz, Amazon, Argos, ASOS, Barclays Bank, BBC, Dixons Carphone, EY, FT, Hermes, Intel, LEGO, Nike, M&S, Microsoft, PwC, Sky, Tesco, TUI and William Hill. 
 
For further information about booking your place or anything associated to the conference please contact Guy Jacobs at guy.jacobs@aepconvert.com or directly on +44 (0)7870 170 885.
 
We look forward to hearing from you,
 
Matthias Bettag & Michael Feiner
Conference Premier Sponsor
Emerging Technology Showcase Partners
Snowplow Analytics
Use It Better Analytics
Piwik Pro
AUTHORITAS
Copyright © 2016 Digital Analytics Hub, All rights reserved.

Our mailing address is:
info@digitalanalyticshub.com

Want to change how you receive these emails?
You can update your preferences or unsubscribe from this list