Achieving real-time personalisation

Changes in consumer behaviour and the reality of the omnichannel customer are driving brands to gain ever-deeper market and customer understanding. With multiple and diverse data sources and innovative analytics, organisations now have an unprecedented opportunity to transform every customer interaction. However, for marketing, the new customer dynamic is creating huge pressure to deliver not only personalisation, but real-time one-to-one personalisation. According to the results of a recent research survey undertaken by Celebrus Technologies and Teradata, almost half of all respondents (44%) are already doing some degree of real-time personalisation – a figure that is set to rise to 75% in the next two years. As Katharine Hulls (pictured) explains, to realise the vision and benefits of real-time personalisation, organisations need to step out of the aggregated data comfort zone.

Understanding personalisation

Will 2014 be the year personalisation, indeed real-time personalisation, becomes a prerequisite? Over the past two years, organisations have tried to exploit traditional offline database marketing techniques, such as segmentation, to gain new insight about individual online customer behaviour. However, they have struggled, due to the lack of detailed data.

Yet, according to a recent survey carried out by MyCustomer.com on behalf of Celebrus Technologies and Teradata, more than half (51%) of respondents say personalisation is either very important or critical to their efforts today. This rises to a phenomenal 80% in two years.

In the future, not only do companies plan to embrace website and mobile personalisation but over three quarters of respondents (78%) predict that they will be making use of data in real-time in the next two years.

Aggregated data

But let’s get this clear: organisations need to take a radically different approach to data collection, storage and analysis to get anywhere near truly effective real-time one-to-one personalisation. To date, organisations have relied on aggregated data – and for good reasons. Aggregated data has provided essential insight into online behaviour that can be used to understand paths and journeys, build a better website and engage senior management with all important reporting.

However, aggregate data cannot reveal the individual customer journey or their needs and preferences. It cannot be used to understand how a specific customer arrived, browsed, searched or moved about the website. Essentially, without this level of individual customer activity information, how can a business achieve relevant, real-time one-to-one engagement?

Detailed data

Today, 25% of organisations are using individual level interaction data according to the survey results. These organisations are now able to undertake far more effective, personalised activity across multiple channels to drive better customer engagement and conversion. For example, knowing exactly which individuals browsed a specific product, such as slow-moving item, enables the creation of highly targeted multi-channel communications to help shift the excess stock.

Real-time website personalisation can also be enhanced by using basket affinity analysis. This method showcases which products are put into a basket at the same time and in what order to then present relevant offers during the online check-out process, increasing both cross-sell revenue and basket size. Alternatively, insight into which products are most frequently bought together created using product affinity analysis can be used to drive targeted content within order confirmation or shipping notification emails.

It is real-time data that is also key to creating personalised offers and engagement that reflect the many diverse ways an individual interacts with a brand. From the different devices used at a particular time of day; to an individual’s preferences for online, telephone or in store engagement dependent upon product type or weekday versus weekend; even full-price versus sale, detailed multi-channel data is becoming crucial.

Omnichannel view

So how does this work in practice? A retailer combining online data with transactional, loyalty and social graph information to attain deep customer understanding can prioritise high value or very socially influential individuals if stock is limited – thus avoiding out of stock situations for the most valuable customers which could impact not just that sale but future purchases and brand perception.

Of course, web analytics based on aggregated data clearly still has a huge role to play in providing critical insight into overall business performance and strategic direction. But it is time to extend that data: technology for online data capture, storage and analytics can now deliver that essential segment of one that will be key to meeting escalating customer expectation and fast evolving cross-channel engagement. To achieve true one-to-one real-time personalisation across all channels, organisations need to go for detail.

 Katharine Hulls is VP marketing, Celebrus Technologies.