Artificial Intelligence (AI) is transforming the face of businesses across the world. Right from banking, to medical, automobile, and communications. You name it and AI is already transforming the sector. I am sure you must be familiar with the long process of scrutinising loan applications. When loan applications are submitted, they must be reviewed meticulously. With the volume of applications being too high, how do you think the financial institutions manage to evaluate each application and reach a decision on granting or rejecting the loan? The answer lies with Artificial Intelligence and Machine Learning (AI & ML).
Many banking and personal finance institutions use the AI and ML driven algorithms to gauge the possibility of the loan being paid back, based on the credit scores and other parameters like the financial history, location, source of income, educational credentials of the applicants. Neural networks are used to predict fraudulent transactions and risky applicants. Based on this the credit decision is made. Apart from this AI & ML have heavy applications even in everyday financial transactions like asset management, risk assessment, portfolio management, and so on.
Artificial Intelligence is the science of infusing human-like intelligence into the machines and making them smart so that they can take their own wise decisions. Machine Learning is the ability of these programs to learn from the past data so that they can handle similar or more complex situations in the future. Just like the BFSI sector, other sectors have been finding applications of AI and ML. It can be used in industries like medicine, for diagnostics and treatment of cancer, manufacturing drugs and so on. Further, in industries like gaming, automobile, music, marketing, aviation, and the list goes on.
Union of Programmatic Advertising and Artificial Intelligence:
Another addition to this list is the digital advertising industry, and especially the programmatic advertising industry. The programmatic advertising industry is experiencing a metamorphosis, ever since it has found applications of AI & ML. The terms Artificial Intelligence & Machine Learning (AI & ML) have been frequently doing the rounds within the programmatic advertising circles. With the profound implications it has for the industry, it does not come as a surprise.
Traditionally, campaigns are managed by campaign managers, who would select the right platform for communicating with the target audience. They would use their deep understanding of their target customers and select the appropriate targeting mediums for communicating the product information with them in a relevant manner. However, today, the scenario has transformed. We now require data scientists to manage and leverage the huge volumes of data that are available for advertisers. The need to rope in data scientists is the data explosion of the digital era, which has played quite a pivotal role in revolutionizing the advertising industry. Another reason is that consumers are omnipresent, leaving behind a large digital footprint that is a precious asset for advertisers. They are all over the web and are consuming the online content in multiple formats. They have an online presence on numerous platforms and different behaviours on different platforms. This data can be analysed for gaining a better understanding about the likes, dislikes, and preferences of the potential consumers. With the help of this data, the daunting task of targeting and reaching out to the right consumers can be handled in a much better way as compared to the traditional methods.
The question here is – How? The mere idea of managing such gigantic volumes of the data can be intimidating, to say the least. However, with the advent of technologies like AI & ML, the picture has turned. The power of AI lies in its ability to mine through tons of data and understand the underlying data patterns to uncover links in the users’ behaviour patterns, which would have been impossible for the human mind. It can be used to harness the power of data readily available today. Also, in the deluge of customers and products, matching the right profile to the right product is no cake walk. Technologies like programmatic advertising help to bridge this gap between brands and their TGs. A programmatic platform backed by cutting-edge technologies like Artificial Intelligence can provide better targeting capabilities, more efficiency and help advertisers in increasing the ROI multifold. Owing to these applications, AI & ML are becoming an integral part of the programmatic ecosystem, deeply entrenched within it. As programmatic advertising automates the entire media buying process, infusing it with AI & ML seems like the most logical way to optimize it further. The AI & ML technology is empowered to take its own decision on pressing questions like which consumers are more likely to convert and which platforms have a high possibility of increasing the conversion rates and so on.
Data enables marketers to provide a more personalised experience to their consumers, which helps them better to achieve their marketing KPIs like brand awareness, brand recall, CTR% and the conversion rates. Experience-based Data Management Platforms (eDMPs) are the tools that enable brands to achieve this goal. They are even more valuable as they bring together a rich collection of customer data drawn from multiple data points. This helps advertisers to ensure that every customer interaction is indeed personal. Technologies like big data are also taking the centre stage in the marketers’ bid to win the consumers’ attention. Research by Forrester indicates that customers having a high-quality experience with a brand are 3.6x more likely to make additional purchases and are 2.7x more likely to be retained by that brand. Thus, understanding the potential consumers to serve such personalised communication assumes supreme importance.
The power of AI & ML holds quite a promising future for the programmatic advertising industry. Advertisers may soon wake up to the day when they only have to provide inputs on parameters like the campaign budget, the product information, and set their KPIs, while AI & ML will efficiently manage the core aspects of the campaign to deliver the best results. This would involve optimising parameters like, which audiences are driving the most revenue, at what time during the day is the campaign driving most results, which ads are driving the best responses, and how to best optimise the campaigns based on the real-time responses.
