The Next Stage of Big Data – Personalisation

Big Data remains a key buzz word for 2013. However, with so many data assets out there ecommerce sites can struggle to digest the information and work out what’s relevant and useful to help them increase conversion rates. As a result, one area of Big Data that’s growing is personalisation. This involves analysing the vast quantities of data about how individuals are engaging with your website and then tailoring the site so that it reacts to a person’s specific needs.

For example, the data might reveal that visitors who click on two different product categories and don’t put anything in their basket are more likely to convert if a popup message offering them a discount appears on their screen. This means that a website becomes almost a living element – changing and reacting the way it looks and operates depending on the type of consumer that engages with it.

However, whatever the personalisation, the key thing to remember is that it should have been implemented based on thorough insight. To achieve valuable insight, you need to work from good data that leads you to understand what needs to happen for a particular audience to improve their experience.

What is good data?

What companies sometimes fail to realise is that the majority of big data is not good data. And without good insights, developing a successful personalisation strategy is difficult. Good data consists of:

• Measuring visitor behaviour; the who, what, where, and most importantly, the ‘why’ part of the purchase cycle.
• Covering all bases to ensure a complete understanding of visitor behaviour.
• Arriving in a common currency; if you’re collecting lots of data, or big data, the task of querying becomes much more straightforward if the data sets are compatible.
• Structure; this begins with precise categorisation and ends with well-organised storage, again, all in the pursuit of simplified querying and investigation.

Why personalisation is key for ecommerce

Once you’ve gathered true insight, this information can then be analysed to help site owners optimise their online presences to maximise sales and increase consumer satisfaction. We’ve already seen from our own clients what this level of analysis can do to conversion rates.

For example, fashion retailer Stylistpick noticed that users who visited a second category page without putting a product in their basket were less likely than other groups to convert. Furthermore, the analysis revealed that Google Chrome users were the most price sensitive customer. In order to optimise their website for these different groups, Stylistpick implemented a personalised discount offering 25% off to Chrome users who arrived on a second category page without putting anything in their basket. This tactic immediately increased conversations from this segment by a third.

Childrensalon, a children’s designer fashion site, is another example of a company that’s successfully used big data personalisation. The company was trying to target customers abroad so created a personalised customer service message into a local language for those coming from the key territories they were looking to target. This tactic alone saw a 13% increase in conversions.

At Qubit, we believe that those businesses able to rapidly respond to visitor behaviours will create the best online experiences and will earn the most brand value with their customer base. Personalisation is therefore a case of the survival of the fastest in today’s new internet world.