Since implementation, KLM has seen significant uplift in conversion through email retargeting. Within the first few weeks, testing of emails sent in local languages showed that KLM saw conversion rates quadruple – and this success has been maintained. Of the emails sent using Streams intelligence, KLM has seen a 34 per cent higher open rate and a 94 per cent higher click through rate from these targeted messages.
Additionally, this real-time data has allowed KLM to identify where it may 'lose' customers in the sales journey, and enabled it to optimise the user experience, encouraging the customer to complete their purchase during their visit to the site.
Using data for contextual personalisation
The ability to analyse data in real-time also gives businesses – especially retailers – an unprecedented opportunity to extend their customised experiences to customers in both the online and offline ("real life") worlds.
Personalised marketing has previously involved combining what we know about a user's profile e.g. their age, gender and nationality, with what they have previously engaged with online, to understand their typical behaviour and what they may be receptive to.
What's been missing, though, is the ability to analyse this data and combine it with real-time information to get a full picture of that user at that very moment in time. This 'in-the-moment' browsing data could include the device a customer is using, their specific location and their stage in the purchase cycle.
Combining known user information with the environment in which they are engaging with a brand to offer a real-time, relevant and engaging experience is known as contextual personalisation. Contextual personalisation maximises the potential of your data, allowing brands to meet a user's specific needs at that exact moment in time – giving the customer what they want, when they want it and where they want it.
Marketers can also marry the online world with the 'real' offline world through contextual personalisation. Imagine if you knew what your customers wanted before they even entered your store – everything from their shopping habits, likes, dislikes and previous purchases.
Understanding customers more deeply then ever
This information is powerful and can be used to provide a highly personalised, user-centric in-store experience, encouraging positive brand perception and ultimately driving sales. Combine this with new technologies such as Apple's iBeacon and you can use what you know about a consumers' online behaviour to market to them in-store and encourage offline sales.
Let's have a look at how this could work with a customer example. Jen is a fashion fan and enjoys shopping for clothes, both online and in-store. When she is on her favourite designer's website she is looking for inspiration for her wardrobe and may even be ready to purchase if she likes what she sees, or gets an offer she can't refuse.
Modern technology allows you to understand what she has looked at previously and align it with her current online behaviour and external data such as geo-location and weather to provide a personal and relevant experience.
For example, you could show pages that reflect the great weather she's enjoying that day in Devon by recommending a collection of summer dresses. Likewise if she is visiting Edinburgh, where it's raining, you could highlight the latest range of colourful macs. Even if she does not put anything in her basket at that time, you can use the historical and real-time data you've collated to send her a retargeting email within minutes to offer a deal based on the products she has looked at, perhaps including a time-sensitive incentive to purchase.
Combining this with broadcast technologies like iBeacon, an 'offer' could be triggered when Jen is in the proximity of her selected retail store. This could be designed in such a way as to entice Jen to visit the store because the products in her recent browsing history are in stock.
