MUMBAI: From self-driving cars to voice assistants Siri and Alexa, artificial intelligence (AI) is expeditiously becoming popular. While one may think of AI only as intelligent robots or technology, it encompasses everything from Google’s search algorithm to e-commerce to geo-target and understanding consumer behaviour.
AI has taken a hold of the advertising and marketing industry too along with big data, analytics, machine learning (ML), and chatbots. Not one advertising or marketing conference goes by without one or more sessions on the subject.
It was in 2017 that marketers realised the leverage AI and ML provided. But the reality is far from the hype as marketers in India and around the world are still unacquainted with the technology and the benefit it can add to business.
Today, companies are gathering thousands of records from each consumer touch point. They have the entire database of what their consumer is searching for, from which device and how long before they actually purchase it. Companies can also trace the consumer’s likes and dislikes by scrutinising their customer profile. This large set of data about consumer behaviour, which is also known as big data, provides definite information to brands that can help their business. This is where AI comes into the picture.
AI in marketing terms consists of machine learning, deep learning and natural language processing applications. But the hard reality is that many of the tools that are being marketed as AI are still in their primitive form and there is a long way before companies can actually begin to use AI to yield better results. Currently, a lot of brands feel the urgency to adopt the modern and new technologies to keep up with the changing marketing dynamics, but AI, just like any other technical tool, is not a magic solution and requires time, resources and money.
Though the name sounds fancy, it may not be essential for every brand to jump on the bandwagon. Agencies, being industry experts, first need to familiarise themselves with how best to use AI for their client before even discussing client readiness of AI in marketing strategy. Setting the record straight, The Glitch managing partner and business head Kabir Kochhar says that the first step to getting clients interested in using these tools by showing them the money. “Showing improved return on investment will get clients to take notice and giving them deeper insights into their customers will allow and inform them on their future product roadmaps,” he says.
For instance, predictive analytics allows online players like Amazon, Netflix, Hotstar, Myntra, Flipkart and YouTube among others to surface and finesse recommendations. Putting together information from diverse datasets is a common use of AI. Even the most advanced tech firms in Silicon Valley are just beginning to unearth its possibilities. Dentsu Aegis Network chief data officer Gautam Mehra suggests that if media companies do not catch up, it’s definitely going to affect them as we do see the local OTT players and even telecoms such as Jio building significant data practices.
In spite of all the automation and move to programmatic, there are large parts of media planning and strategy that are still being done laboriously by human intervention. While stating that currently only some really sharp media planners will come up with half a dozen hypotheses and run tests that either prove or disprove the same, Indigo Consulting national head of strategy Devang Raiyani believes that going forward, a few startups will lead this and big media players will wait till some of them acquire critical mass and acquire them.
The revolution of AI in marketing has been propelled by the advent of affordable and advanced data analytics tools, extensive datasets and a growing acceptance of the data-driven approach to marketing decision making by marketers. With the advent of cloud computing, it’s very easy to scale without having to make large upfront investments. Most of the cost to use an AI system is rarely the system itself, but in ensuring you have the right data in the right format prepared for the AI engine. While stating that certain AI systems require some level of initial investment in technology, Mehra points out that these, however, sustain themselves within a year and hence it’s not really a CapEx investment in that sense. And then there are AI systems that are absolutely turn-key and pay-per-use.
It is a herculean task for agencies to convince clients unaware of AI to use the technology. In such cases, Raiyani opines that the best way is to prove the use-cases at the fringes, create a few proof of concepts before betting big as the challenge with most Indian companies is that data available is not very clean and highly fragmented across touch-points. He believes that it will be the GAFAs (Google - Apple - Facebook - Amazon) of the world who will lead this change.
Kochhar thinks that the grasp of terms such as AI and big data are theoretical and in practice, we're just scratching the surface on how AI can transform industries. “For now, agencies need to think of it as a tool of inspiration for the copywriter as it will essentially eliminate a bunch of A/B testing we currently do to see the effectiveness of communication,” he says.
AI in creative advertising has been touted as a replacement to human copy although there’s still a long way to go for that since, in advertising, context is everything and the nuances of language still need to be mastered. AI will help throw up more insights based on user interaction with ads and act as a guide showcasing the types of communication routes that can have a higher impact on the end user.