Organisations have understood the value of personalisation for some time, with many companies adopting simple concepts, such as targeting specific website promotions or email content towards pre-defined customer segments.
In the new mobile world, personalisation is not a feature but a customer expectation, and this expectation extends to being treated as a “me”, and not a “we”.
“I am not a typical 35+ male, from London, who has opened a promotional email in the last week and purchase shoes in the last year; I am me, and I spend my money with the company who appreciates that.”
Many experts regard this expectation as hyper-personalisation and believe it must be the basis of any interaction between brands and their consumers. While many people believe that the juxtaposition of this hyper-personalised experience and the inevitable customer expectations, and regulatory evolution of privacy and anonymity, present a challenge.
A select few marketers see this differently. Privacy is not an obstacle or barrier to personalisation: privacy and anonymity must be seen as the guiding principles of personalisation.
In the new digital world of mobile consumers, personal information is a commodity, sometimes available and sometimes not. While personal data may be unavailable, there is a vast amount of data that can be used as the basis of a personalised experience for example:
What form has the interaction taken - such as the device type, whether this interaction is instigated from a “pull activity,” such as the consumer browsing the webpage or mobile application, or a “push activity,” such as the consumer’s being pushed a message as they browse your aisles.
Anonymous behavioural information – such as which products I have browsed, and how long I have been browsing. Have I, the customer, navigated directly to a product or product category, moving systematically between areas, or do I appear to be meandering? This applies to both online and offline interactions.
Environmental Information – regardless of whether this is a brick-and-mortar store, an email on the user’s smartphone, or a website browse from their home machine; environmental information can be gathered and used, such as the city I’m currently in, local weather, recent local or global news, upcoming events, pop-culture trends, etc.
Some, or all, of this data can be used to provide a valuable and truly personalised experience, as well as anonymous. This is intelligent contextualisation.
Contextualisation does not simply mean a gimmick, such as showing the local weather in the corner of a message or a list of local news stories you may be interested in. Instead this means using this array of data, intelligently, and guided by the marketer’s hand, to improve the consumer experience and achieve the marketer’s objective. Whether that is providing the right offer at the right time in the right place, or refining content and presentation for the specific consumer. Even choosing whether this is the right time to attempt to reach out to the customer at all is an in-time contextual decision.
Amongst our clients, we have a number of examples of providing true value using anonymous contextualisation, a few simple examples including;
A large wine retailer, with stores throughout the UK intended to provide intelligent wine recommendations to its customers when they browsed its website. By using the products they had looked at so far, their search terms, and critically what was currently available in their local store, the recommendations were personalised and valuable. The latest cloud based technology helped ensure that the offers were not only relevant to the consumer from a preference perspective, but also relevant to their personal locations
A major content provider wants to continue providing content that is contextual and personalised to every consumer. While personal preferences are occasionally available, most consumers choose either not to identify themselves or not to divulge personal preferences on topics of interest. Using the latest cloud based technology, the content provider is able to combine powerful signals to maximise the interaction-value of every consumer into a hyper-personalised experience, including:
- Using the broad topics and subject matter the customer has already browsed in their anonymous activity
- Constantly evaluating what the customer was viewing, and for how long, as well as unique evaluated attributes of the consumption, including the readability of the content, writing style, sentiment, tone, etc
- monitoring trending topics of interest on social media in real-time
This data was combined together, providing a wealth of data that could be processed in less than second to provide a personalised presentation of content for each consumer. From the first interaction, using the consumers location, current social trending topics, current content consumption statistics, and time-of-day to predict the ideal content for this experience.
From the consumer’s reaction, what they chose to drill-down on and how long they chose to dwell, the system began to model a persona for this anonymous user. Using cohort analysis as well behavioural analytics, the interaction was continually optimised to that user’s expressed preference. This user’s preference also helped shape and refine the next user and the next.
Content served to the right person at the right time
Using content analysis and advanced (natural language processing), new content could be served to the right person at the right time as soon as it was made available, and using social trend analysis mapped to the content and subject matter of every piece of content, the system ensured that all content served was relevant and contextual to that time and place.
Ultimately, consumers will decide if and when they want to provide more personal data or identifying signals to retailers, and it is likely that this decision will be based increasingly on the value they perceive and receive from this exchange of data-for-service. Once an individual is identified, all prior contextualisation approaches are just as valuable, but inferences can then be confirmed, distinct physical and virtual brand interactions across many devices linked together into a single consumer behaviour, and critical personal information can all then be used as a force-multiplier in the contextualisation and personalisation of the experience.
Instead of generic social recommendation, I see advice from my own friends; when I enter my favourite store, the sales assistant recognises me personally and offers to show me the product I left in my virtual cart; as I pass by the shoe department, my phone reminds me of my friend’s upcoming birthday and her frequent social media comments about those new pumps. I believe this is the retail experience of the future. Privacy is not the enemy of personalisation, but the basis to its true adoption.
About the author
Jonathan Taylor, is Chief Technology Officer at SmartFocus, where he builds intelligent solutions for some of the world’s largest brands - including Nestle, Mercedes and House of Fraser - that take the guesswork out of marketing and help organisations, ranging from governmental agencies to financial services, to uncover new opportunities within their data. Prior to joining the team at SmartFocus, Jonathan held leadership positions at organisations such as AGT International and IntraLinks.