The prospect of a personalised experience is one that many automotive customers would welcome –arriving to the website of a brand you’re considering purchasing from to be met with rich information and imagery about the model and products that you’re most interested in, represented with people just like you, living the life you’re beginning to picture yourself in.
Taking insight from the retail world, research shows that 53% of those engaging online would be willing to share more data with brands in exchange for personalised experiences.
With vendor offerings increasing every year, there’s no shortage of reward or technology partners to attract enterprise brands to the space.
Yet these types of experiences remain the exception instead of the standard many believed we would be experiencing by now.
At times it feels like personalisation is slowly being relegated to the marketing buzzword graveyard, resting peacefully beside omni channel marketing. As a reminder, that was the promise that walking into a retail environment would soon mean being greeted by someone holding your favourite drink while smoothly uttering the second half of that sentence you stopped reading on their website just before you left home.
The prospect is getting closer, but much of the excitement around omni channel has been a premature expectation for brands to run before they can walk.
Personalisation is very much an essential step on that journey, but a misunderstanding of its enablers is arguably one of the core reasons we’re not seeing more of it. Those enablers being not just technology, but assets and time.
How it should work
To illustrate the above, let’s take a quick look at the steps needed to deliver a basic personalised experience.
1. Website gets tagged with one of the various personalisation systems available today.
2. Customer comes to the site, gravitates towards the car model they’re interested in and ideally at some point also fills out a form (brochure, newsletter signup etc) – all captured by the personalisation system.
3. Based on the customer’s website behaviour over time, the brand makes some assumptions about what they’re interested in and assigns the customer to a profile.
Layer in the data captured via that form fill, like age and gender, and a basic profile would look something like the below,
If that customer has shown some more telling behaviours, like customising the seat trim on a car configurator, the brand could reasonably assume he’s also in the late consideration stage of his purchase journey.
So the brand has all of this indicative data, and a system ready to deliver an experience tailored to that customer.
Practice would dictate that core site elements like homepage imagery should update to show a young male enjoying a real life experience with his new BMW 4 Series. Ideally the accompanying information and call to action would be personalised to inspire a tactical next step for the customer – like a link to his finance options.
But this is where the problem starts. In our basic example there are four profile variables used in showing a personalised image but a customer could be any combination of the below.
That means that, to show a targeted, personalised image on just one section of the homepage, the brand needs 180 different image variants (3x4x3x5). Any customer with a variation in just one of the above profile elements would call for a different image to be shown.
Keep in mind this doesn’t take into account all additional factors that require different imagery, e.g. other website sections and pages, new model launches, seasonal factors etc… Include those, and the assets required by a global automotive brand can comfortably reach into the thousands.
And here we face the reality. Delivering a personalised experience is equal part technology and equal part content, with the latter issue perhaps too often assumed to be one that will solve itself once a suitable delivery system is identified.
In the future, AI image creation (known as GAN) may provide a solution to generating high volumes of well segmented assets, but we’re quite a distance away from that tech sitting in the hands of even the largest enterprise marketing departments.
Even if GAN does become the norm, early examples have aimed to highlight the host of social considerations to overcome before this becomes a feasible alternative to real, authentic content.
How close are we?
The fact is that after digging through centralised asset storage systems, searching for freshly approved brand imagery from headquarters, automotive marketing teams are often left with very few tactical options despite their best efforts.
The strategy and rationale used when updating website imagery is one understandably closer to ‘let’s use image A on the model page, so that we still have image B to use on the homepage’. Requiring a rationing of assets across channels with no choice but to have one aggregate audience in mind.
Next comes a tussle with a delicate and complex central CMS before quickly moving onto the mounting list of to-dos that make up the automotive marketer’s day.
In terms of numbers, our own previous customer research found brands to have as little as two hours per week across relevant teams to dedicate to curating targeted content, clearly nowhere near enough to deliver hundreds (or thousands) of targeted assets on demand.
Adobe’s recent State of Creative and Marketing Collaboration Survey estimates the average time taken to bring a piece of personalised content to market to be twelve days, with content creation time very much being the greatest barrier to delivering personalised experiences.
What can be done
brands are faced with a reality of personalisation technologies advancing rapidly while their own marketing resources remain relatively unchanged, leading to an ever widening gap between potential customer experiences and those being delivered.
An issue further complicated by the majority of marketers naturally reporting an unwillingness to press ahead with personalisation at the expense of content quality.
Senior automotive stakeholders should be considering the pursuit of personalisation as one that requires both scaled processes and a strategic technology stack to work alongside their core legacy systems. Not just an essential blend of old and new infrastructure, but a fresh outlook on the limits of their human resources too.
That means understanding that the wide remit of today’s marketing departments makes manual asset sourcing an unrealistic approach to enabling personalisation, and that a layer of content automation combining brand and third party assets such as user generated content is the only feasible strategy.
Such automation allows brands to build and maintain a deep reservoir of content without marketing teams loosing focus on foundational tasks, offering the brand the tangible advantage of being able to deploy highly targeted campaigns at a pace dictated by their software capabilities instead of asset restrictions.
Those enterprise brands without this critical layer cannot realistically expect their hopes of delivering a personalised experience to become much more than hope in the long run.
For brands that have yet to take the leap into personalisation, the widening gap between potential customer experience and current offerings means an increasing prospect of competitors pulling ahead once they’ve found the right combination of integrations and resource alignment. Along with a very real increase in the costs and effort needed to catch up in the future.