We put marketers' questions to our community in a new series of articles aiming to provide practical advice and connect business leaders. "I am interested in how others are thinking about delivering more personalised experiences to buyers at scale. I'd love to know how they are increasing the use of information to deliver personalised experiences that will be meaningful to customers." Personalisation has been a salient term in digital marketing for many a year and as the technological shackles continue to loosen for the majority of businesses, it is no surprise that the intelligent use of data represented a common response for delivering personalisation at scale. Artificial intelligence (AI) is perhaps the best-known tech solution for optimising and personalising large datasets, and this technology too was frequently referenced alongside machine learning and automation.

Artificial intelligence, or AI for short, is playing increasingly essential roles in aspects of our daily lives, including but not necessarily limited to the online gambling industry. Both iGaming and land-based casinos have evolved, utilising cutting-edge technology to provide better experiences to engage players. And artificial intelligence's introduction to internet casinos gives users a more immersive and realistic experience that they would have only found in brick-and-mortar gaming establishments in the past. The internet gaming industry leverages AI technology to power many things, such as algorithms that guide users to games they may prefer. They collect data based on your actions to forecast exactly what you're interested in to make things easier and more convenient for you, for example.

Before the pandemic, AI in banking was primarily used to automate routine tasks. But banks now see it as a vital tool to support product innovation, develop new business models, and provide a personalised experience for every customer. A recent Economist Intelligence Unit (EIU) survey of banking executives for Temenos found that 85% have a "clear strategy" for adopting AI to develop new products and services. It revealed over a third are prioritising AI to improve customer experience through personalisation. Some are also looking to acquire or partner with fintech companies to enhance their customer experience through a personalised experience when offering investments, saving deposits, and retail lending.

Various categories of fintech firms – Buy Now, Pay Later (BNPL), digital lending, payments and collections – are increasingly leveraging predictive models built using artificial intelligence and machine learning to support core business functions such as risk decisioning. According to a report by Grand View Research, Inc., the global AI in fintech market size is expected to reach US$41.16 billion by 2030, growing at a compound annual growth rate (CAGR) of 19.7% in Asia-Pacific alone from 2022 to 2030. The success of AI in fintech, or any business for that matter, hinges on an organisation's ability to make accurate predictions based on data. While internal data (first-party data) needs to be factored into AI models, this data often fails to capture critical predictive features, causing these models to underperform. In these situations, alternative data and feature enrichment can establish a powerful advantage.

Investment in fashion-related technology increased by 66% during the pandemic, according to research by The Business of Fashion and McKinsey. The report found that the value of the top 50 investments in fashion-related technology across the past year, either by fashion retailers or businesses that sell products and services to fashion-related companies, has increased by 66% to $16.2bn since 2019, indicating an increase of capital put into technology in the fashion sector. According to The Business of Fashion and McKinsey, around 55% of these investments went towards ecommerce technology, while the rest was mostly put into payments technology, buy-now-pay-later tech and social commerce. Investment in resale technology, supply chain and logistics management, non-fungible tokens, and virtual reality companies closely followed. Imran Amed, founder and CEO of The Business of Fashion, said: "The pandemic cemented technology's critical role in the fashion industry, particularly in terms of ecommerce adoption. But now the industry must lean even further into new technologies by experimenting in the metaverse, embedding fully digitised workflows across their organisations and investing in traceability tools to help them reach sustainability targets. Those who choose to wait on the sidelines risk being left behind."

The term "machine learning" refers to a sort of Artificial Intelligence (AI) that allows computers to learn without having to be explicitly programmed. Machine learning, to put it another way, is concerned with the creation of computer programmes that can train itself to change or execute predictive models which learn from fresh and innovative data to anticipate future behaviours, events, and trends. Meanwhile, cognitive systems, a less evolved kind of AI, analyse and categorise unstructured data using predictive modelling and logical reasoning. SaaS (Software-as-a-Service) is becoming a more realistic option for businesses looking for availability, functionality, and flexibility. SaaS relies on large-scale cloud delivery, reliable connection, and enterprise-level security.

Personalisation makes your customer experience so much better. In this new age of evolved consumers who buy almost everything online, creating a great and unique customer experience has become more like "personalise or die slowly"! Some organisations do the basic -- personalise their sign-up forms or address their clients by their first name in emails. Others create personalised workout programs or, as Coca-Cola did with their "Share A Coke" campaign, print popular names on Coke bottles. Buyers prefer experiences that reflect their personalities, beliefs and aspirations.

Lately, Zomato has been taking the internet by storm with intriguing posts like the independence day'not accepting orders anymore' or super friendly notifications reminding you to order food from its platform like never before. That is just one side of the coin. On the backdrop, Zomato has been experimenting with various machine learning models to provide personalised experiences to its customers, driver-partners and restaurants. Today, many consumer-focused brands are trying to understand customer preferences in real-time and offer personalised experiences. It requires surfing through the data lake, creating useful machine learning models, and deploying them in production.

A lack of artificial intelligence and machine learning usage in digital marketing is causing a significant issue for marketers looking to deliver personalised experiences to customers, according to Gartner. In its new report, the analyst firm revealed that almost two-thirds (63%) of digital marketers struggle with this issue, from a survey of 350 marketing leaders from November 2020 through December 2020. One of the main problems is that digital marketing leaders are scaling their use of AI and ML to align with customer retention and acquisition goals rather than across the marketing function. This contrasts with another statistic: 84% of digital marketing leaders believe using AI/ML enhances the marketing function's ability to deliver real-time, personalised experiences to customers. Gartner says many digital marketers believe bringing automation, scale and efficiency to marketing activities across channels is the greatest value of AI/ML tools. "A comprehensive personalisation strategy and roadmap can be deciding factors in the results marketers achieve from their personalisation efforts, yet most marketing organisations lack an effective personalisation strategy – let alone one that is explicitly linked to desired business and customer goals," says Gartner for Marketers vice president analyst Noah Elkin.

The COVID pandemic has accelerated the technology adoption, and many businesses are riding on a digital transformation journey. AI and analytics are playing a critical role in driving these innovations leading the companies towards a new normal in the post COVID world. With the changing needs of the businesses and uncertainties that prevail around, the predictive power of AI and analytics will play a massive role in helping businesses navigate through these changes. From a change in customer preferences to logistics and more, AI has been a driving force in almost all the segments. With the increased adoption of AI, IoT, analytics to support business growth, there are a lot of trends that we expect to emerge in the space.