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Sam Barnett, CEO, Struq.
Consumers have always wanted personalised products, but the act of personalisation has historically been both very expensive and very time consuming – just consider the process of engraving.
In the last decade however, personalised products and services have become more and more common in everyday life. When I visit Amazon, Facebook, Google, Spotify, Twitter or Pinterest I always get relevant and interesting content that has been selected especially for me.
When I want to send a birthday card I can personalise it with my own design or message, and when I want to buy paint, I can get it mixed to exactly the colour I want at the click of a button. Personalisation has become quick and cheap, and personalised services are now everywhere.
In this context, the consumer experience of “personalised” ads has been very poor in recent years. Apart from some very basic product recommendations that have typically reflected the last products a consumer looked at, in most cases, not much else has been personalised at all. Ad styles have been applied generically and there has been very little personalisation of marketing messages or calls to action based on individual customer behaviour.
Ironic as it may sound, the industry has, for a long time, effectively adopted a ‘one size fits all’ approach to ad personalisation, with all consumers seeing ads that look the same, irrespective of the differences in their online behaviour.
Things have changed dramatically in the last couple of years, however, and personalised advertising is beginning to catch up. A new generation of ads genuinely put individual customer journeys at the heart of decision making and result in truly personalised ads that offer a better experience for customers, and better results for marketers.
Today, every single element of an ad can be selected and rendered, in real time, to match a customer’s individual purchase journey and maximise clicks and post click conversions.
To bring this to life, imagine two completely different customer journeys for a fashion retail site. Beth visited the site last week and bought an expensive dress at full price. John looked at four different pairs of branded jeans, all on special offer, but didn’t buy anything. It seems obvious that these two customers should receive ads that are totally different from each other and which each recognise the precise stages they are at in their individual purchase journeys.
For Beth, we might choose to show ads that incentivise loyalty and which cross-sell complementary products for her recent dress purchase. We may also wish to offer her loyalty points, or inform her of a special sale or a new product line from her favoured brand.
For John, who we know is actively looking for jeans, we may show ads with stronger calls to action and a clear short term deal to get him back to the site quickly - within the 48 hour window in which we will know he is most likely to buy.
The reality is that all of these personalisation decisions can now be made in real time, based on data for each customer journey and an ability to accurately predict the most relevant and effective combinations for each type of journey, along with the most appropriate times (and frequencies) to display ads.
The same process also applies to selecting the layout, styling, colours, fonts, animation and the number of products featured in each ad – with every element chosen deliberately, based on real data, to make the ad as compelling and persuasive as it can possibly be for that individual consumer.
This approach is a big departure from the ‘one size fits all’ approach that has been common for so long.
High levels of competition within the space have transformed the recent pace of innovation, and I am confident that the quality and depth of personalisation options will only continue to improve as we integrate new, even richer, sources of data into our decision making (CRM, social media, multi device and third party contextual and psychographic data).