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Author's profile photo Luis Felipe Lanz

The #BigData après–ski, the new challenge for #Retailers

In a Digital Enterprise age, competitors are very aggressive, they are fighting in a market share that is no longer loyal to a brand, the new consumers are loyal to the company who provide innovation, make their decisions easy and thereby bring a value to the offer, if you cannot provide this, they will “google it” and find another provider in a matter of seconds.

A couple of years ago the #BigData wave hit the Retail industry, nowadays almost all the key retailers implemented successfully a BigData architecture, elastic, analytic and bring data democratisation to their organisations.

But that is the past, now the Retailers face a new challenge, how to retain customers, how to make them to come again to your store (physical or virtual) and prefer you against the competitors, this is a recurrent block of questions that any retailer has in their mind.

The solution rely in a revolutionary Personalised Marketing strategy, not the typical one, this one will be based technology, specifically in Machine Learningtogether with Predictive Algorithms, and that’s for the backend of course, once your personal offer is selected by those two elements you need to give it in a customer hands in a non-intrusive manner, that looks so natural that the consumer feels it as an obvious option, Mobility is the key here, but mobility in the wide vision that include new TV Apps (Like AppleTV, Google ChromeTV, etc), Wearables (Apple Watch, etc) and Enhancement in native mobile behaviour.

Let me explain each component with a quick example:

Machine Learning: Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence, this can be exploit in the retail industry to analyse the individual trends, what does he/she like, what not, how reacted to previous offers, what attract him/her to our store. Whit your BigData and the right infrastructure (like SAP HANA, Etc) you can get this very easy.

Predictive Algorithm: Once you have a Machine Learning processing the data and learning what are your customer’s preferences and trends, you need to apply algorithms that identify when the customer has the next buy intention and if possible which articles are in his/her Wishlist, make an offer and wait for the catch, successful retailers like Amazon, Alibaba, etc already use this with an amazing results

New TV Apps: Yes, wake up, traditional channels are obsoletes, you want to have a personalised offer, you need to be sure the customer see it and when they expect to, so you need to link your publicity to the new Television, and it is on demand, via Apps on platforms like AppleTV (tvOS) or Android.

Wearables: Smartwatches and Virtual Reality are there, people get one device each day, new retailers already have VR stores, what about you ? what about notifications in the smartwatch ?

Native Mobile Behaviours: A coupon that goes directly to their digital wallet, using Paypal, Bitcoin. Your fidelity card virtual, with some money on it, you need to re-design your mobile apps to make it more attractive and use the latest technology gadgets, use iBeacons to detect that customer when is in your store proximity and offer him/her something he or she really wants, based in your machine learning & predictive algorithm from your backend.

This is the 2017 challenge, are you working on it ?

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      Author's profile photo Henry Banks
      Henry Banks

      hi, something is amiss here with the font size and typeface - it's GIANT!!!

      it might be an idea republish it smaller, to make it more legible? thx, H

      Author's profile photo Antoine CHABERT
      Antoine CHABERT

      +1 on Henry. It would be interesting to tie the challenges that you describe to SAP BusinessObjects Predictive Analytics and to explain how the product can help tackle them. Thanks, Antoine