The intersection of vast data and artificial intelligence (AI) is paving the way for transformative shifts in how brands connect with their audiences. Conventional marketing strategies are finding it difficult to match the elevated demands of contemporary consumers and the swift pace of technological innovation.

Print, TV, direct advertising, and telemarketing are still relevant in brand promotion, yet consumers across all demographics have become predominantly digital beings. The importance of these traditional channels is diminishing in light of the remarkable advancements and benefits that AI is introducing to the online environment. So far, the marketing technology sector has primarily concentrated on developing tools that enable marketing teams to implement campaigns.

This industry has been fixated on filling positions rather than achieving results. However, AI has permanently altered this dynamic. It’s no longer about instruments for humans to operate, but rather systems that independently utilize data to produce outcomes. The straightforward “customer journeys,” primarily crafted by marketers, are destined to fade swiftly. It’s not simply about guiding consumers along a route with the option to pivot as they please.

While that seemed like a significant advancement in marketing just a few years ago, it was not aligned with what consumers desired or required. It’s about tracking consumers wherever they venture and offering value at critical moments. Technology has finally enabled it to achieve this, and machines can execute it more effectively than any individual. This article explores the necessity for self-sufficient marketing platforms, leveraging extensive proprietary data, AI, the decline of cookies, and the challenges created by increasing advertising expenses, alongside the growing consumer demand for tailored experiences.

Big Data and AI in Modern Marketing

The marketing industry has undergone a significant change in the last ten years, fueled by a surge in big data. This data holds the potential for an unprecedented understanding of consumer habits and preferences; however, the sheer volume has often overwhelmed conventional marketing systems. What value does Big Data hold if it cannot be utilized, particularly in real time?

The adoption of AI technologies over the past year and a half signifies a crucial turning point, offering the long-desired tools that can effectively convert this data into actionable insights and ultimately profit. Companies such as SwiftERM are at the forefront of this evolution by integrating AI with exclusive consumer data to enhance their autonomous marketing platform. The new technology delivers unprecedented results beyond comparison, which lacks appreciation by those coming to it with traditional mindsets.

The potential of this platform extends beyond merely storing data; it functions as an intelligent system that can analyze consumer data trends, forecast customer actions, and automate decision-making to implement highly tailored and timely marketing strategies. With AI embedded at its foundation, SwiftERM’s platform allows for data analysis and application at a scale and speed that human abilities cannot match.

This encompasses monitoring billions of consumer devices and tracking trillions of digital interactions each year, creating a solid framework for listening to, analyzing, and responding to consumer signals in ways that would have seemed inconceivable just a few years ago. The outcome is a completely new marketing approach—one that not only fulfils but also anticipates consumer requirements, boosting the effectiveness of each campaign through profound consumer insights and predictive analytics.

Post-cookie Era offers Advanced Identity Solutions

As third-party cookies are being phased out, digital marketers encounter a significant hurdle: how to monitor and reach consumers without these conventional tools. SwiftERM addresses this challenge through its sophisticated identity resolution features, which are essential in a world without cookies.

This technology allows for the identification and tracking of consumers across various devices and platforms, avoiding the dependency on third-party cookies, thereby guaranteeing that tailored marketing experiences remain seamless.

By leveraging first-party data and a unique identity network, SwiftERM equips marketers with the means to effectively engage consumers, ensuring that marketing approaches are not only in line with new privacy regulations but also highly targeted and hyper-personalised. This capability is particularly important as marketers strive to sustain relevance and effectiveness in their campaigns in light of the decline of third-party cookies.

Tackling rising costs and declining engagement in traditional advertising

Traditional advertising is losing its effectiveness, as costs escalate and consumer engagement declines. Messaging platforms are incredibly cost-effective, allow for exceptional personalisation, and are viewed as more intimate by consumers. Studies consistently show that consumers prefer to receive content and offers from brands via email, a trend that continues to grow. This should prompt marketers to reconsider their remarketing strategies and invest more in owned channels.

SwiftERM’s platform leverages AI to trigger the optimal offer through owned channels, reducing marketing costs while boosting the effectiveness of these efforts. Automated marketing communications create tailored messages that resonate deeply with consumers, leading to higher conversion rates and a stronger return on investment. This strategic use of technology optimises marketing spend, ensuring that every pound is used more effectively to engage consumers.

Hyper-personalisation in consumer engagement

First let’s define exactly what hyper-personalisation, often called individualisation, is. A customer-centric term, meaning “to be unique and absolute to the individual consumer“.  Ron Shevlin at Forbes, proposes “It is a series of interactions that strengthens a customer’s emotional connection to a product or company,” in his recent article. Emphasis is on “a” customer, (an integer of one) not a segment – a section of people on a database, to which “a” customer belongs. i.e. All people who bought red wine in the last 30 days. If you read anywhere else it is something else, that someone is trying to gaslight you.

There is zero collusion of either the data or how it is used, to bias or sway application of it between individuals, despite some providers suggesting the edges can be a little bit more fuzzy, to bend the definition to suit their purposes. One example is Amazon’s “remarketing” software first launched back in 2012, which isn’t personalisation. It is what everyone else who bought that product also liked. Not a ringing endorsement of the uniqueness of the individual to whom it is addressed, unless you enjoy Lemming culture.

The absolute opposite, and perhaps the nemesis of hyper-personalisation software is “segmentation”, the definition of which is division into separate parts or sections. That stalwart of email marketing for the last 20 years still has a place in certain echelons of FMCG marketing, because it offers the opportunity to group what are hopefully a cross-sections of a database that have similar interests.

All the necessary intense deep learning analysis is only possible with AI. It enables you to obliterate the potential involvement of human beings merely on cost alone before you involve errors and omissions etc (as detailed above).

Further, AI machine learning isn’t restricted to who bought what and when but also includes the subtleties of each shopper’s unique idiosyncratic behaviour. How long that individual looks at an item, how often they come back to look at it. The correlation between the habits for this purchase against those made for previous purchases etc, is what poker players know as a “tell”. Then the less obvious, the navigation patterns around your site that identify.

Finally, we must stress the distinction between hyper-personalised web content and hyper-personalised email marketing. The distinction between the two is illustrated most simply by considering how long people are online daily, compared to how long they aren’t. The ratio is enormously in favour of them having a life, and the same applies to everyone else. i.e. You can’t sell them anything if they’re on someone else’s site, or an alternate site has usurped your best efforts to visit.

However, there is rarely a moment when people aren’t far from access to any communication you send them. We all carry our mobile phones everywhere these days 24/7. Indeed 87% of all adults now have a smartphone and 97% of 16-24 year olds. This means that as email popularity continues to rise, meaning that troglodyte naysayers still living in the dark ages, bemoaning mass bombardment of 1990’s mass emails to their inbox, can be ignored.

With the advent of GDPR (EU), the Data Protection Act (UK) and CCPA, CPRA, and CDPA (US) only those who want to hear from their chosen, preferred brands, get the privilege of emailing them. Remember consumers choose to “opt-in”. So you have a situation where your customers want to hear from you. But they demand relevancy, and therefore you must ensure they receive the right products at the right time. This can only be achieved via email marketing with hyper-personalisation software functionality.

It is important to emphasise the absence of standard email software providers in this article. Many purport to offer “personalisation”, and prefer to avoid the distinction that AI technology hyper-personalisation software provides. Theirs is stolid, tried and tested software, for the purpose it was designed for, all be it that it avoids dwelling on the distinction in ROI, that the new kids on the block provide.