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Creators and curators: Getting the most from your ecommerce data

29th Oct 2014
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It’s a widely held view in ecommerce that the key to a successful and profitable business is held in your data and your algorithms.

Many look to Amazon’s “People who bought this, also bought this”, “Top Picks for You” in Netflix and Ocado’s predictive basket as the standout examples of personalised, profitable ecommerce. Each of these often cited examples demonstrate how ecommerce can enhance the purchasing experience by helping and inspiring the customer to make more purchases, rather than simply enabling them to buy what they were going to anyway in a different channel.

In doing so, each experience generates incremental revenue, rather than simply delivering cost of sale efficiencies. This approach to managing the purchasing experience also drives customer loyalty, making a single purchase customer into a repeat spender, moving them along the cycle to become brand collaborators, customers that not only support your brand with purchases, but actively recommend you and your product or service over the competition.

The challenge with each of these examples is that the algorithms that drive them require lots of data. But many brands are simply not blessed with a deep history of multiple transactions or a rich journey of browsing behaviour and content consumption from which to build up a meaningful profile of the customer. Even those that do have statistically significant depth are still only seeing part of the picture. This may explain why in a recent survey from Econsultancy and Adobe, that despite 77% of marketers agreeing that personalisation using purchase history data delivers a high return on investment, only 21% of those companies were actually using the technique and even less were using browser behaviour as a source of personalisation.

So, for those 79% of brands that are missing out, how do you build up a complete picture of the consumer? There are two different ways to obtain more insight: curating and creating.

Curating data

Firstly curation; acting as a data curator means seeking out insights from a variety of existing data sources, direct marketers and financial services companies have been doing this for years with geo-demographic analysis and credit scoring.

Applying these data matching techniques to new digital data streams offers far richer sources of inspiration to feed a personalisation algorithm than was ever previously possible. In 2009, the Museum of Modern Art in New York was curating data about your interests from your social graph to customise an inspiring calendar of their summer events, individually tailored to you. Amazon US profiles your friends with upcoming birthdays to suggest items they will like and lets you know the right time to buy them.

Curation isn’t just limited to the Social Graph. Google Now offers a variety of insights into its user base and has already demonstrated the power of combining time sensitive data sources such as your calendar with weather or traffic feeds to create intelligent alerting services such as proactive messages to tell you to leave earlier for your meeting due to traffic or tips on what to pack ahead of a trip based on changes in the weather at your destination. Although commerce applications of these data sets are currently scarce it is possible to access browsing history for example to alert you when a product you have sought recently is in stock or on sale at a retailer you are walking past.

Not all data is readily available, accessible or affordable. It’s a changing landscape both commercially, as organisations wake up to the monetisation potential of their data, but also from a legislative perspective as privacy becomes an increasingly sensitive area for consumers. For long term sustainable success, it is important to ensure that you are creating your own data as well as curating what currently exists.

Creating data

Creating data to fuel your ecommerce efforts gives you ownership, something that curating alone cannot provide. Also, by creating data from interactions with your customers, you will be building a bank of information that is tailored to you and your brand, making it invaluable. When creating data in this way, it is important to clearly show the benefit of a customer supplying you with their valuable information. Discounts and free offers are the most common examples of this, but these offerings must provide a clear benefit to the customer to make them feel valued, rather than just another data point to be used.

Creating data doesn’t have to be complex; it can start with a simple question.

Online dating service Tinder has shown how people will happily answer questions, as long as there is a clear benefit. Ensuring it is quick and simple helps adoption and the playful left or right swipe has become the differentiating element of Tinder’s experience. Restaurant and hotel recommendation engine Nara uses the simple “thumbs up” and “thumbs down” mechanic to build up a picture of the places you like. This is then analysed and refined over time to continue to deliver you tailored recommendations.  Our own work with chocolate brand Beyond Dark used EEG headsets capturing brainwave activity enabling people to measure the pleasure they received from a variety of different chocolate products inspiring them to explore the new brand.

Each of these examples demonstrates how an engaging experience can quickly build a picture of your customers that no database would be able to provide. So, if you don’t have the data you need to deliver personalised inspiring experiences, think about curating and creating the insight you need.

Rob Urquhart is director of commerce at OgilvyOne.

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