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Blogs > MWD Advisors

How customer analytics is driving innovation in the retail and restaurant trade
Helena Schwenk By: Helena Schwenk, Principal Analyst, MWD Advisors
Published: 4th February 2014
This work is licensed under a Creative Commons License
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If you’re a industry watcher, like me, interested in customer analytics, then you’re always on the lookout for interesting stories and developments that demonstrate some of the most interesting and leading edge applications of this technology. Whether by accident or design we’ve seen a few this year already and it’s perhaps no surprise to see that Google and Amazon are at the centre. In particular both have filed patents that aim to address some of the opportunities and challenges of today’s modern consumers.

Amazon aims to predict what you want before you actually buy
First up Amazon. The internet retailer has recently filed a patent that helps predict what people will buy and uses these predictions as a basis for boxing and shipping packages—all before a customer has even purchased an item. The company is calling this anticipatory shipping as it aims to reduce the time between someone ordering a product and them actually receiving it. If it works it has huge potential for the company, helping Amazon appeal to a growing body of consumers where immediate access to purchased goods is placed in high regard (it’s also likely to engender a degree of customer loyalty too). The online retailer is already experimenting with drones as a method of delivering packages through the air so the additional of anticipatory shipping can be seen as part of a wider strategy to tackle the lead delivery times associated with internet shopping.

Amazon has long been at the leading edge of customer analytics. The company has pioneered the use of customer data to offer a one-stop-shop shopping experience underpinned by its product recommendation engine, for example, that’s effective for up-sell and cross-sell purposes. With this patent the company has the opportunity to take the use of customer data a step further. At its core is predictive analytics and algorithms that harness historical data such as previous purchases, key word searches, wish list activity, stickiness to a page, and cursor movements to help anticipate the likelihood of someone buying a product.

While predictive models aren’t particularly new in the retail business, the idea that Amazon can produce predictions at such a detailed level is really interesting. Being successful will require Amazon to accurately decipher patterns and trends in all our browsing and buying behaviours. Many of us purchase on Amazon for many different reasons: for work; for ourselves; for our children; for special occasions; on behalf of others. Marketing and selling to a segment of one is a retailer’s Holy Grail but being able to understand behaviour not only at a customer level but also in what context we are likely to make a purchase is pretty clever stuff.

Google : linking online ads to taxi rides
That said, while Amazon is hoping to encourage you to spend more of your dollars online, Google is taking a slightly different tack. According to media reports Google has also patented ad technology that links online ads to free or discounted taxi rides to an advertising restaurant, shop or entertainment venue. The idea behind it is that sophisticated algorithms will work out a customer’s location, their preferences and the best route and form of transport so advertisers can target more personalised and relevant ads to them but with the added bonus of being able to provide free or discounted travel to the advertiser’s location. It’s perhaps no coincidence that Google has already invested in autonomous vehicle technology too.

In much the same way as its keyword bidding service works (where advertisers bid for the use of certain search keywords) Google hopes advertisers will bid for the types of customers. Of course to make this service really fly advertisers really need to have access to all the relevant customer information at the right time so they determine the potential profitability of making an offer. It’s not terribly clear from what I’ve read how far this extends; it would, for example, make sense to not only have access to a customer’s preference data but also their purchase history, their lifetime value, their sphere of influence and so on. In certain respects this is what Next Best Action applications aim to achieve by weighing up both the opportunities and costs of completing an action for a customer (such as offering a discount) whilst ensuring it’s at the right cost for the business. The success of such a service will ultimately depend on its ability to demonstrate a return for both Google and its advertising customers.

In the end these stories clearly demonstrate how Google and Amazon continue to build and evolve their business models—outstripping a lot of the competition in their wake—through the effective use and exploitation of customer data. In many respects this is the core of their business (more so perhaps than search or online retailing) as it provides the springboard for future growth and innovation. With data and analytics clearly embedded in both companies’ DNA it seems only logical both companies would want to continue to protect their technology IP.


Published by: IT Analysis Communications Ltd.
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