Personalisation, made relevant.
David Marrinan-Hayes CEO at Ve Global (“Ve”) discusses why demographic data must be complemented by contextual data to achieve personalisation at scale for an audience of one.
Imagine visiting a website for the very first time and the item you’re looking for being the sole occupant of that landing page, in terms of size, desired colour and with a price tag and preferred delivery option - all suited to your preferences.
Picture the steps leading up to that point being a journey of connected experiences, aided by intuitive messaging that reflected your current mood and motivation - consistent across device and served over the days, or even weeks it may take for you to arrive at a decision.
Now think of the impact that would have on a user; an uninterrupted brand experience that nurtured intent from discovery through to purchase. This value-add alone would be enough to counter the Amazon by-default mind set which has beset customers.
However, for ecommerce to reach this utopia marketers must look beyond demographic data and elevate in-session behavioural insights to bring context to campaigns.
Knowing your data dictionary
Before delving further, let’s clarify some terms. First there’s behavioural profile data, which refers to inferring persistent patterns of previous buying behaviour – say, buying footwear in a size nine – and using this to inform campaigns to that user.
This practice is commonplace and stands to reason as an effective way to personalise, however, the logic is far from iron-clad. Just because a shopper has previously acted with a certain set of criteria, doesn’t guarantee they will every time.
This is where in-session data comes in – analysing onsite behaviour in the moment and responding with appropriate messaging. For example, noticing the same customer is now looking for shoes in size 11, inferring that they are likely shopping for someone else.
It’s this relevance that gives the context missing from personalisation, and as is shown below, this is a blind spot amongst most marketers today.
Marketers’ love of demographic data misplaced if personalisation is the goal
In July this year, a study of 300 marketers by Lotame revealed that 90% identified audience insights as key to their activities, with demographic data seen as most valuable. However, only 10% were confident in its accuracy.
Despite these concerns, over two-thirds (76%) viewed age as most valuable, followed by geographic information. Astonishingly, less than a third believed in-session data was important.
The uncomfortable truth for these marketers is that without relevance - which contextual data brings - personalisation is a veneer, a gimmick bearing only an appearance of a bespoke customer journey online. Its job is to grab attention by imitating intimacy. And while this tactic has enjoyed success in the past, consumer expectations have evolved and calls for more meaningful personalisation are getting louder.
Relevancy gives personalisation potency
The heart of personalisation isn’t just a question of who your customer is; it’s understanding the why behind a website visit that really counts.
This is why ‘plug and play’ products reliant solely on demographic data often fail to hit the mark. Vitally, they do not factor in shoppers’ motivations, expectations, and habits to achieve modern expectations of personalisation.
Without knowing the context of each visit, personalisation tech can’t be fully optimised for relevance. It simply doesn’t know the full data story. Is the user shopping for themselves or a loved one? Have they abandoned to compare prices elsewhere or been surprised by hidden costs? Are they window shopping for bargains or researching a purchase?
To answer these key questions, marketers must complement demographic insights with real-time context that paints a holistic picture of the customer journey, from the first touch-point to last.
Gtech Case Study: Experimentation With ‘Shopping Modes’
To put our hypothesis into action, we spent the past 9-months working with Gtech – one of the UK’s fastest growing brands - on a series of experiments to deliver relevancy and personalisation at every touch point on the Gtech website.
Ve set out to validate patterns of behaviour and subsequent performance using a ‘Shopper Modes’ methodology. The results of such a campaign would be compared to a standard campaign to discover the quantitative effect of this superior level of personalisation on website sales.
To begin with, data insights gleaned from over 6,000 survey respondents allowed Ve to uncover and validate distinct Shopper Modes that visitors to the Gtech website could be categorised under: Browsers, Researchers, Bargain Hunters, One-time shoppers, and Product-Focused.
Ve found that almost half of those who abandoned were comparing product information, otherwise categorised as ‘Researchers’, and wanted more visible product reviews, more time to consider, and were using their basket as a ‘wish-list’.
Knowing this, Ve tailored its on-site Digital Assistant solution to deliver experiences relevant to the Researcher Shopper Mode. This included authoritative statements from customers who left 5-star ratings via Trustpilot and a ‘Save and send’ email remarketing option so users could email product wish lists direct to their inboxes.
Personalisation for Researchers alone drove CTRs of nearly 16%, almost 5 times higher than normal. More significantly, this approach increased average engagement rates across the Gtech site by almost 300%.
Add context for relevant personalisation
For too long, marketers in the digital marketing space have been focused on customer profiling and harvesting vast volumes of demographic data, as this definition of personalisation steadily became more commonplace in the industry.
But who cares how much data you accumulate if you can’t convert the audiences it attracts? Brands must incorporate contextual relevance into their personalisation campaigns instead of exclusively focusing on mass sweeping campaigns that zero in on the top of the marketing funnel.
The incentive to succeed is huge, with Gartner predicting that by 2020, those businesses deploying personalisation tech that recognises behavioural intent could increase profits by 15%.
The ultimate focus for brands committed to delivering personalisation must be the unification of solutions that incorporate both demographic, profile and contextual in-session insights to deploy experiences that meet both the motivations and expectations of the user at different stages of the buying journey.
This is the only way brands can successfully achieve personalisation at scale for an audience of one.
You can join the host of major brands who are using Digital Assistant to power their on-site customer engagement. Visit Ve.com for more.
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