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Opinion: How to monetise your eCommerce data

During tough times brands tend to redirect above-the-line marketing spend to below-the-line opportunities and the unprecedented economic circumstances facing us today mean a sharp decline in marketing spend across the board -- with only investment in digital rising.

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During tough times brands tend to redirect above-the-line marketing spend to below-the-line opportunities.

The unprecedented economic circumstances facing us today mean a sharp decline in marketing spend across the board -- with only investment in digital rising.

It's therefore no surprise that retailers are looking to digital techniques to manage customer interactions and to optimise marketing activity and every pound of marketing spend.

This doesn't mean mass marketing through digital channels -- retailers have an opportunity to differentiate themselves by implementing tactical yet highly targeted digital campaigns.

Unlike many other brands marketing online, retailers are blessed with sophisticated and flexible ecommerce platforms that handle valuable data relating to consumers and transactions.

They have the opportunity to produce the type of personal cross-channel communications to which most brands merely aspire.

Today's online retailers also face a significant challenge, in servicing a market that increasingly seeks out information from social networks, forums and comparison sites -- as well as direct from retailers themselves.

This has led to retailers creating Web 2.0 features such as customer review and rating, engaging media rich content, collaborative filtering navigation and search techniques.

Beyond this, making brands' communications personal and impactful -- by cutting through the noise -- has become a major priority, and it's this angle that has driven the development of a technique known as "synaptic marketing".

So called because of its likeness to a "digital brain" in accessing and analysing multiple inputs instantly, synaptic marketing involves combining data from online (e.g. browsing and purchase history) and offline (e.g. purchase and customer service interactions).

The result is a comprehensive and real-time view of the customer that drives complex and dynamic decisions on which messages are shown to which customers, and when.

These messages are then delivered to the customer through whichever channel they choose to use, or is identified as most pertinent to the interaction in question.

Based on proven direct marketing principles, the challenge behind this technique has been to create an environment in which data can be held, analysed and acted upon without interruption -- either to the business or the site/communications channel.

At the heart of this is the combination of technology and analytical expertise --the "gold dust" of skilled people with a commercial and statistical focus.

Furthermore, data is held and managed using a "data light" principle, based on identifying key data items and drawing on them only when needed.

As well as seeing the benefits of this truly bespoke communication right now, smart retail marketers will be looking ahead to identify and implement leading edge technology as a prelude to future advances in this concept.

For example, "Web 3.0" -- defined as a collection of small, customisable applications using data "in the cloud" and running fast on any device -- has extraordinary potential.

The principle is that processes will have more built-in intelligence -- thereby reducing the amount of input and context needed from the user.

The key within an e-retailing landscape could be to aggregate large groups of data held within user logins, friend lists, messaging systems and feeds for relevant targeting and viral distribution, while integrating with payment systems and online wallets in order to close the loop for ecommerce transactions.

To begin the technical journey towards this, mature e-retailers need to focus on how best to eliminate data silos between applications and data objects in applications, thereby enabling the deduction of meaningful relationships between users and behavioural data.

It's important to note that these types of approaches are based on the understanding that either the consumer's permission to use their data has been sought, or that the activity is based on non Personally Identifiable Information (PII).

Adhering to the principles of permission and privacy are a vital prerequisite to any marketing activity, and even more pertinent when we reach this level of data-driven decision making.

Web 3.0 at present is more akin to science fiction -- tellingly I don't believe that we yet have access to the kind of artificial decision engine needed to make this level of intelligent connection between data.

Generating insight to direct relevant and meaningful interactions with customers is already happening, in the discussed synaptic marketing technique.

The only difference here is the necessary (human) analytical element, which ensures that the scope of possible outcomes is comprehensive enough to meet the level of data input being made.

If Web 2.0 was concerned with making the web a compelling application interface platform, then the next stage of evolution would be leveraging this interface platform with open data interfaces and combined services, to create a more dynamic value chain, and to initiate multi-business solutions that help customers live more productive and profitable professional and personal lives.

While there aren't yet computers that can approach the remarkable feats the human mind can perform -- necessary to drive Web 3.0's ultimate potential -- the benefits of this kind of joined up thinking are already becoming accessible.

Ben Langdon, chief executive, Digital Marketing Group

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