“Personalised marketing and advertising is not about sales. It’s about building a relationship with the customer.” – Julian Hillebrand, author and emerging technology expert
In a hyper-connected digital age, consumers crave more than a plastic sales slogan and a static banner ad to offer their attention, loyalty, trust, investment and custom to a brand.
Regardless of your industry or sector, to win on today’s commercial battlefield, showcasing your value and reaching out to your prospects on a personal level is the key to success.
Personalisation, by its very nature, offers a means of connecting with your target audience on a deeper level, delivering content and messaging tailored to the needs and desires of the individual, rather than relying on generalised marketing efforts to generate business and boost brand awareness.
A recent study suggests that 79% of consumers say they will only engage with an offer if it’s been personalised to reflect their previous brand interactions. Moreover, around 88% of marketers based in the US alone have reported seeing measurable improvements as a direct result of personalisation.
Yet, despite the proof, many organisations, from budding startups to established corporations, see implementing personalisation in a smart and scalable way as a colossal challenge.
The term personalisation is broad and means different things to different people. By understanding the primary types of personalisation, as well as their value, and gaining an insight into emerging trends, you’ll be able to benefit from this cutting-edge branch of marketing, enjoying a sustainable level of success, growth and evolution as a result.
That said, let’s explore.
Optimisation, customisation and personalisation: the key differences
To get under the skin of personalisation and what it truly means in a contemporary context, it’s important to distinguish between optimisation, customisation and personalisation. While there are crossovers, there are notable differences that you should be aware of – here are clear-cut definitions for your reference:
Optimisation, also referred to as A/B or multivariate testing, helps to determine the best possible presentation of an asset to a wide user or consumer base.
Typically, optimisation involves presenting a series of variations to an audience over a set time frame until a preferred version is statistically determined. For instance, testing two versions of an ‘add to cart’ button on a website’s product page to see which design prompts more click-throughs or conversions.
Customisation is different to personalisation as the control is in the hands of the user, not the brand. An app, platform or subscription service, for instance, may enable users to customise or edit the experience to meet their specific needs by configuring the layout, content, or functionality.
By offering consumers the option to customise their experience, you’re essentially allowing them to self-optimise, something that serves to enhance the customer experience (CX) based on the declared preferences of the user.
Through various approaches, methodologies and data sources, personalisation builds a comprehensive profile of individual users.
The wealth of historic, real-time and predictive insights delivered by personalisation serves as a detailed baseline for marketers, empowering them to develop a personal experience for individual consumers, encouraging engagement, interaction and brand loyalty in the process.
Essentially, while personalisation, optimisation and customisation all aim to enhance CX and user experience (UX), optimisation focuses on the wider target audience whereas personalisation and customisation drills down deep into the user on an individual level. However, unlike customisation, personalisation is system led, which means it requires no effort from users and offers far more scope to enhance the overall consumer journey.
Primary personalisation types
Personalisation is a powerful force, offering today’s brands and business, like yours, the potential to reach out and connect with your prospects in a way that will forge lifelong consumer bonds, offering maximum long-term value.
Here we look at four of today’s primary personalisation types and their key features in an ever-evolving digital landscape.
One of the most widely used forms of personalisation is based on demographic information including a consumer’s age, sex, occupation, and salary.
By identifying your business’s target audience and analysing the demographic data of your consumers, it’s possible to deliver content, advertising, and social media messaging that resonates with your prospects at the times of day that they’re likely to be most responsive.
To utilise the power of this personalisation type, businesses from a broad range of industries use Smart Tokens to deliver tailored email content to consumers segmented by demographic information and leverage smart (or dynamic) content that adapts based on a user’s preferences, interests, age or location.
Both of these approaches allow modern brands to provide existing or prospective customers with a level of personal value that is automatic, adaptable and scalable, often resulting in an excellent return on investment (ROI).
Another effective approach to demographic personalisation is personalised video content – and although this can yield exceptional levels of engagement, it’s time-consuming nature means it’s not an approach that can scale with growth or demand.
Behavioural personalisation hones in on what a customer does, rather than who they are. It is a sustainable form of personalisation that remains relevant at all times, offering marketers a greater chance of delivering content, brand messaging and offers that will strike a real chord with prospects.
Here are some common approaches:
- Recommendations based on past activity: Leveraged by breakthrough video streaming giants like Amazon Prime and Netflix, product recommendations are delivered to a consumer based on their previous actions and engagements. But these actions don’t even have to be performed on the website offering the recommendations; providers such as Bazaarvoice allow organisations to offer recommendations based on a user’s activity on other websites within their network. The images used to promote these product recommendations can also be personalised according to a user’s past activity.
- Recommendations based on similar consumers: Utilised by the likes of Amazon, this approach to personalisation helps businesses to serve up behavioural recommendations based on what consumers with similar preferences or browsing patterns have purchased.
- Content based on customer journey: Akin to providing content based on past activity, this savvy personalisation technique delivers tailored content to a user based on where they are in the sales funnel. For example, a running shoe shopper in the awareness stage of the funnel might receive a relevant product comparison guide based on their preferences and past activity.
A dynamic style of personalisation, this approach is based on delivering suggestions, recommendations and content that morphs or evolves depending on factors including the weather, the time or a user’s physical location.
Today’s consumers respond to transparency, convenience and relevance and delivering content based on a user’s existing location, for instance, is a powerful way of driving engagement and cementing customer loyalty. 88% of consumers that make local searches from a mobile device take some form of action (calling a business, making a purchase, or physically visiting a store) within 24 hours.
In addition to location-based environmental personalisation, brands and businesses can leverage weather conditions or patterns in their daily routine. For instance, if a person suddenly finds themselves in a hot climate, they might receive recommendations on the best fans available in their locale. Or, if someone’s about to endure a long, traffic-ridden commute home from work, services like Spotify might recommend a drive-time playlist tailored to their preferences.
Personalised emails earn a 6.2% higher open rate than those that aren’t – and by tapping into this notion, the supermarket was able to deliver preferential content that resonated with a highly-engaged target audience.
A cutting-edge branch of personalisation, personality marketing reaches far beyond metrics and consumer data. It involves uses machine learning (ML) and psychology to develop, curate and deliver content in a way that is tailored to the personality of the customer, significantly improving customer experience.
By bringing in insights from the world of psychology, personality marketing delves deeper than demographic data or browsing behaviours alone, giving brands insights into causation as opposed to just correlation. Known information, such as how customers have engaged with emails, is used to infer previously unknown information – i.e. a customer’s personality according to the Big Five model. Having this information means we can understand why customers behaved in a certain way and also predict how they will respond to content in the future, potentially making it one of the most powerful tools a modern business could have as part of their marketing strategy.
While still in its infancy, it’s clear that personality-based personalisation is effective. In fact, to date, we at DataSine have delivered an 80% increase in customer engagement for Hello bank! Belgium; a 71% rise in sales for a leading French bank, and a earned 59% increase in conversion rates for a notable Russian bank. And that’s just the tip of the iceberg.
Personality-based marketing is where data, technology, psychology, and meaningful human interactions meet and as the digital world evolves, this powerful branch of personalisation will continue to thrive.
For more insights into the world of personalisation, explore our A-Z guide to launching a successful personality-based marketing campaign.