Direct, one-to-one, individual, personalised… Whatever you call it, it’s a marketing strategy that’s undergoing significant disruption. Advancements in data collection methods, analytics, digital electronics and digital economics are providing marketers increasingly effective real-time and prolonged customer-personalisation tactics, making the targeting of customers at a personal level that much more achievable and valuable. But just as marketers are becoming more tech-savvy, customers are becoming increasingly conscious of mass advertising, at a time when privacy and individuality is front of mind when choosing which brands to support.
We unpack how marketers are best using behavioural science, sophisticated data sets and tailored content strategies to effectively personalise and individualise their marketing at all touchpoints along the customer journey.
Customer expectations have reached an all-time high. In today’s on-demand, always-on culture, consumers expect to be understood completely, served intuitively based on their current contexts, and satisfied immediately with exactly what they want.
Imagine that your shoe-loving friend’s birthday’s coming up and you’re going shopping to find them the perfect pair of kicks. Being in lockdown, visiting stores in person is out of the question, so you sit down at your computer, open your web browser and head straight to a website instead.
While browsing for your friend’s present, you’re treated to a few recommendations and eye-catching advertisements. ‘That’s odd,’ you think, as you glance at their suggestions – usually they do a much better job suggesting things you like. Then you notice that your significant other is still signed into their account, so that account is active. With a quick logout and re-login, you sign into your account – and see new recommendations that are far more to your taste (although this probably isn’t going to help with ideas for your friend!).
Knowing what your audience wants is marketing 101. And given the level at which marketers have the ability to access personal information about their customers, customers are becoming more used to getting exactly what they want. Or are they?
According to Segment study the ‘2017 State of Personalization Report’, 44 percent of consumers studied said they will likely become repeat buyers after a personalised shopping experience with a particular company, and 49 percent said they’ve purchased a product that they didn’t initially intend to buy after receiving a personalised recommendation from a brand. Fast forward to 2021, and research by NZ Marketing and Toluna finds that 22 percent of respondents say they’re somewhat willing to receive targeted advertising based on their interests and browsing history. Of these respondents, 72 percent want to receive targeting messages only if they’re relevant to them and 43 percent because they’re looking to receive a unique or personalised experience.
Director of Business Development for Australia and New Zealand at Toluna Stephen Walker says that the main barriers to personalisation are when a company is seen not to be open about what data they collect and how they use it, or doesn’t share their approach to protecting peoples’ data. “People are most willing to share their data for the development of relevant new products and services – 58 percent moderately to completely likely,” he adds. See page 25 for more on this study.
So on top of knowing what your customers want and the level of personalisation needed to give it to them, marketers also need to make them feel secure and the process effortless. Not asking too much, then.
How many brands are doing this well? Not many, if you consider a recent Adobe maturity model that assesses business capabilities needed to enable personalisation at scale within the retail landscape. “Our study found that no retailer is currently deploying advanced or cutting-edge personalisation tactics across the entire omnichannel customer journey,” says the report. “It’s no wonder customers aren’t satisfied with the level of personalisation they’re experiencing.”
However, according to Adobe in its ‘Achieving Omnichannel Personalization at Scale’ report, many companies have at least some personalisation on their digital properties, usually basic tactics such as product recommendations on a site’s checkout page to encourage last-minute cart additions, or email or display promotions sent for items customers have recently browsed but not purchased.
Smart strategies
Personalisation extends beyond the realm of retail, and the Adobe report offers some insight into best practices that can be applied to marketing strategies. These include:
Strategy #1: Start with Customer Experience
Personalise every step of the customer journey with cutting-edge tactics such as tailored dynamic promotions, prioritised content sequence and placements, and real-time behaviour-triggered messages across channels. There’s an ever-increasing range of tools and vendors supplying analytic and automation tools to help you do so, but Head of Insight & Analytics at Track Aotearoa Matt Jarman has noticed a core trend for marketers is often to start with a ‘tool-first’ approach.
“Although there is an obvious temptation to implement new martech or solutions with the promise of greater understanding or personalisation, in our experience this approach rarely delivers the perceived benefits. We advocate an approach that starts with the customer – identifying the experiences that you’re trying to deliver; understanding the data, analytic and martech requirements needed to deliver the requisite customer experiences; quantifying the gaps from a current capability perspective, as well as the likely business and customer uplift; and then identifying the technology or tools required.”
Strategy #2: Data & analytics
Personalisation is only as effective as the underlying data driving it. Robust personalisation requires companies to deeply understand their customers, and having accessible and relatable data is one of the best ways to do so. But it comes with a catch.
“It’s also worth noting that marketers have had a huge amount of trackable data for a long time, enabling us to track everything all the time, but we must acknowledge that the privacy landscape has shifted,” cautions Head of Data & Tech at FCB New Zealand Qassem Naim. “Although this might make it trickier in the short-term to execute our marketing activity, for many customers, it’s a welcome change.”
Strategy #3: Creative & content management
These days, getting your ad in front of the reader is the easy part – we have a host of sophisticated tools to help us find the right customer at the right time. But it’s creating something that’s going to cut through the noise and lead them to click through that’s where the real art starts.
One of the biggest hurdles to achieving personalisation at scale is producing the vast amount of content needed to deliver personalised experiences. This strategy requires marketers to dynamically assemble, automate and scale content needed for personalisation with machine-learning technology.
“In this landscape, readers are also more likely to engage with content that they can relate to and see themselves within in some way, so using clear images that represent your target audience within your creative is an important step,” says New Zealand Country Manager at Outbrain Andy Hammond. “Think about this from your own perspective. If you’re 35 and looking to buy your first home, it’s unlikely you’re going to engage with ads that predominantly show older families or seniors.”
Strategy #4: Optimisation & decisioning
Maximise sales with a centralised decisioning engine that arbitrates which messages and offers should be sent to which customers, through which channels, at what frequency. Marketers must evolve from managing siloed, channel-specific communications to orchestrating omnichannel campaigns across all traditional and new media. Managing Partner at Together Rufus Chuter says that if marketers get this right, they should expect to see an effective media strategy work coherently within a wider brand and communication strategy, as well as creative platform or idea that delivers on personalisation.
Strategy #5: Organisation & operating model
The Adobe report says that achieving personalisation at scale takes more than new technologies. “It requires transformation. First, the organisation and operating model should be structured in support of seamless personalised experience across channels. And that requires moving beyond a traditional organisational structure, with its separate online and offline teams operating under separate profits and losses.”
This is possibly one of the more challenging strategies to implement, but it essentially comes down to buy-in at all levels of business and commitment to a particular strategy. This is something that was discussed at length in the June/July 2021 issue of NZ Marketing, and again picked up by ANZ’s Matthew Pickering on page 30.
On the following pages, our experts critically and practically engage with a number of these personalisation strategies in the context of great privacy concerns, with the aim of providing marketers with greater insight into delivering branding and messaging that’s well targeted and engaging at an individual level.
The line between the ‘real’ world and the digital one is growing ever fuzzier. Smart phones, smart wallets, smart homes, smart cars and highly connected public spaces are changing the way marketers reach audiences.
We’re seeing big shifts in technology that will help marketers reach their audiences more effectively in the coming years. Sensor technology – and the Internet of Things in general – connects users’ devices to the world, whether at home, out and about, or in store, creating highly targeted customer experiences, and opportunity for digitally savvy marketers. Geo-fencing – real-time location-based marketing using geolocation data to target users in a certain area – lets marketers send push notifications when customers are near stores, and offer them deals as they walk in the door.
Artificial Intelligence (AI) will help manage these customer journeys, offering highly specific product recommendations to customers and predicting their needs ahead of time. For marketers, AI technologies support sophisticated predictive analytics and help improve the ad-buying process through detailed conversion and acquisition data analytics.
Such technologies will also provide the natural language processing for chatbots, and help organise information such as a customers’ purchase history, recommending new products and even creating personalised sales content for would-be customers. This might be a discussion for next issue…
