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How to be a data hero with online customer data captureby
7th Feb 2011
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Malcolm Duckett of Speed-Trap discusses how IT is finally able to provide the answers to those critical customer questions posed by the business.
Today the online channel, including websites, mobile apps, widgets and mashups, are a key part of the way most businesses interact with customers and prospects. As a result, many business functions, from marketing to channel managers, merchandising to sales, are keen to know more about the customers’ and visitors’ behaviour, experiences, objectives and desires – and are starting to ask IT to deliver the data which answers these questions.
However, the tools the industry has provided to make this possible to date tend to fall short on a number of counts. As most companies will have discovered, the data provided by web analytics is at best unreliable, at worst, completely wrong. Furthermore, the data is often only available as a download from the service provider’s data centres (often located in off-shore facilities), and hence requires a slow, unreliable, expensive overnight FTP download processes. As a result the information is typically 24 hours out-of-date, preventing the development of real-time applications.
In addition, the tagging processes used to capture this data are costly to implement and error prone, reinforcing the problems of inaccurate and incomplete data resources. And, of course, organisations typically opt for summarized data, making it impossible to embark upon personalised or targeted marketing programmes.
Even if the business can get the data and has some trust in its quality, these tools typically organise the data around pages, hits and unique visitors; information which is completely irrelevant to the business needs of sales and marketing who want to know about customers, prospects, products and behavior. And without an integrated approach to customer identification, it is not possible to link data from the online channel to the rest of the company’s data to create the 360-degree customer view.
Online customer data capture
There is a growing awareness that web analytics is simply not good enough to meet the growing demand for business focused online data. As such organisations are turning towards online customer data capture (OCDC) systems. These light-touch, tag-free data capture mechanisms can work with a wide range of online applications, including web, AJAX, Flash, AIR, mobile and games consoles, and be deployed quickly and simply without any back-end integration.
Data is structured by visitors and includes customer ID information to allow linkage to offline datasets; while the systems compile and deliver not only real-time ‘session-state’ information but also historic ‘customer state’ data and can feed directly into data warehouses without the need for ETL or data integration processes. OCDC systems also offer real-time access to customer-structured data via SOAP/SOA/Web Service interfaces to support event-driven, real-time and cross channel applications; whilst also acting as source data for other in-house systems enabling the creation of a complete customer view.
This approach fundamentally transforms the value of online data. Using a typical web analytics view of a customer’s interaction, a company can discover that a unique visitor visits the site and hits certain pages. The company knows the visitor has looked at three products; added the first two to the basket and then abandoned the purchase. Using traditional analysis techniques, the company would ascertain it had lost the sale of the last purchase – in this case a TV stand at $69.99.
In fact, the out of stock actually cost a sale nearly 40 times this value – a fact that can be discovered using the customer-orientation, analysis and data structures provided by OCDC which allow the meaning to be extracted from this customer’s journey.
Integrating this data with back-office or customer-history data provides a very different view of this simple visit, providing far better understanding. With this depth of view, the company can see that the visitor – now identified as Simon - was interested in buying a complete package of items, totalling over $2,700. He even added two high value products to the basket but when he discovered that the final (low value) product to complete his package was not in stock, he decided to abandon (and possibly went on to purchase these items from a competitor).
Understanding the impact of the out of stock of the low value item can lead to better stocking policies of critical ‘add-on’ components, to drive improved business performance.
This ability to analyse the online channel processes at the level of each individual increases the utilisation and value of the warehouse. But actually the even bigger opportunity for the business is to take this ‘failure’ and run a re-marketing program to retrieve the lost sale and engender increased customer loyalty and sales.
In this example the business has all the information required to contact Simon directly with a relevant offer. He could be notified when the TV stand comes back into stock and offered a one-click purchase from an e-mail with the complete package he had selected - perhaps with an extended warranty too.
Or by exploiting the other data about Simon in the warehouse, the business now knows that he has spent over $5,000 in three transactions over the last 12 months; is based only three miles away from store #267 and has looked at three home cinema sound systems in the last week. Why not get the store to contact Simon with an invitation to visit the store for a planned personal demonstration of an entire Home Entertainment system at an agreed time?
In this way the online channel is providing data that drives cross-channel promotions by providing insight that is actionable, valuable and driven by the data IT are providing. This data can be exploited to use this ‘bad’ event to generate further business and increased customer loyalty by treating Simon as a valued customer. And this is proven to work, with even the most simple personalisation programs driven using OCDC data increasing turnover by 10% or 15%. In addition, companies that have used this approach to link the warehouse to a cross-channel programme have seen call centres achieve a sale for every three calls as a result of improved customer insight and relevance!
The online channel is the richest source of data available to a business. But, to date, its business value has been limited. But finally the data may be accessible for integration into the modern IT infrastructures and information architectures, and doing this in an affordable and rapidly deployable way.
Malcolm Duckett is VP marketing & operations at Speed-Trap.