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Predictive, proactive, proximity based payments

After my discussion about the augmented economy which focused upon customer service, I thought about it from the other side: transactiosns.

Many years ago, my technology
firm made a play for banks to deploy data warehouses to perform predictive
analytics based upon consumer propensity models of their data-based behaviours.

It may sound a little complex,
but basically it was meant to use data patterns to predict what the customer would
do next and whether they might need some new financial service. 

A good example was analysis of
purchases that would show more frequent visits to a store the client had never
used – Mothercare and the Early Learning Centre – would mean promotion of baby
bonds for future education savings. 

An alternative analysis might
show behaviours that would indicate a house move, e.g. regular visits to a new
town, and therefore a home buyers and movers package would be sent out in the
post.

These predictive services were
crude and based upon delayed responses that lagged the customer’s behaviours,
but were far ahead of their time as a concept.

Now obviously, there are some
caveats to this approach, as in it needs permission to have marketing that is
so personal, but these challenges are not insurmountable and, today, are
actually imperative

Predictive marketing is the battleground
of Big Data, as it can now be proactive rather than post-event.

Good examples are shown with Google.

When Google knows my searches are
ideas, they can predict what is relevant for me.  If I searched for headache tablets side
effects, they might recommend that I switch to paracetamol, and direct me
straight away to my nearest Boots or Walgreens. 
If I happened to be pricing TVs, they might offer me a special deal as
for Best Buy or PC World to get a discount.

If you don’t think that Google
Analytics are the key to predictive, proactive marketing, just checkout the
results of research of three academics who find that Google predicts stock market
movements pretty accurately:

“Debt”
was the most reliable term for predicting market ups and downs, the researchers
found. By going long when “debt” searches dropped and shorting the market when
“debt” searches rose, the researchers were able to increase their hypothetical
portfolio by 326 percent. (In comparison, a constant buy-and-hold strategy
yielded just a 16 percent return.)

In a similar way, Google can
predict flu trends,
election results and more.

In the same way, banks can use transaction data combined
with search trends and other data to predict and then proactively offer service
in real time.

That service might be offering car loans as I drive by the
showroom of the BMW dealership I was Googling last night or mortgages as I
drive towards the real estate office fo the broker I found.

Now that’s all well and good, but
it goes further than this as the prediction marketing can now be embedded to
the internet of things.

This reminded me of the Metro
store of the future
in Germany.

A few years ago the Metro store
built a prototype of the grocery outlet of a few years ahead using NFC and RFID
technologies.   This has now been updated
with a concept video from Co-operative in 2011 that shows the latest store thinking:

The concept store included the
idea of dynamic pricing as you walk through the aisles, based upon your loyalty,
shopping habits and more.

Your smartphone would emanate
your preferences and you might want ot cut back on Baileys and ice cream but,
as you walk past these items, they change prices dynamically for you and your
phone beeps a special discount deal today.

Just
for you Chris, buy one get one free (this offer is not available to anyone else
instore).

So you get the idea, but it’s
even going one step beyond this.

As the internet of things means
that everything has intel inside and intellisense becomes the competitive battleground
using predictive, proactive marketing, you get combinations of deals coming together.

The internet service provider, mobile
carrier and bank create a partnership with BMW where they are incentivised to encourage
visits to BMW.

As a result, you keep finding
adverts, offers and deals all around you, as you are intellisensed for business
in the virtual and physical world.

You get the idea.

It almost reminds me of that
lovely vision of Tom Cruise walking into the shopping mall in Minority Report, and everything recognises him based upon iris
biometrics.

But forget the biometrics.  We have this intellisense thanks to mobile
wifi combined with RFID and NFC (technologies I recently backtracked over).

This sensing of the presence of the payer and payee through the network can also be seen in the use of mobile networks and apps, as demonstrated by the Square Wallet app where checkout is handsfree.

This is why Square Wallet wins the wallet wars against Google and PayPal today.

We are already living in a world where the internet of things intellisenses our buying habits and, if we’re
buying, we’re paying for things.  This means
the bank that ties itself into the value chain of intellisense, is the bank that
will be at the heart of the next generation of retail payments.

And that means being the bank
that mines data to provide predictive, proactive, proximity based payments.

 

About Chris M Skinner

Chris M Skinner

Chris Skinner is best known as an independent commentator on the financial markets through his blog, the Finanser.com, as author of the bestselling book Digital Bank, and Chair of the European networking forum the Financial Services Club. He has been voted one of the most influential people in banking by The Financial Brand (as well as one of the best blogs), a FinTech Titan (Next Bank), one of the Fintech Leaders you need to follow (City AM, Deluxe and Jax Finance), as well as one of the Top 40 most influential people in financial technology by the Wall Street Journal’s Financial News. To learn more click here…

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