Artificial intelligence (AI) is powering up the ad industry’s transformation into a more algorithmically driven ad-tech-dependent environment, as our reliance on automatable tasks that require a high degree of accuracy is growing.
Surprisingly, digital marketing is one of the first areas to recognise the impact of artificial intelligence. How so? It’s a prediction model that learns and scores the campaign optimisation process, and then over iterations can predict the optimal results before actual bid values are entered. Therefore, AI’s direct impact is currently boosting campaign effectiveness, by accurate category scoring and bid factor significance, and in turn achieving media effectiveness.
According to Juniper Research, machine learning algorithms used to drive efficiency across real time bidding networks will generate $42bn, in annual spend by 2021, up $3.5bn from 2016. Eventually AI will be powering up more media than ever before, essentially making it a predictor management platform. Today, IBM Watson, Amazon Web Services, Microsoft and Google are testing their AI use cases in media or working with media companies to come up with scenarios to support the significance of testing in media.
The key use cases of AI to us in the real world of media:
1. You can begin to score your audience categories for relevancy, cost-effectiveness and performance.
2. Ability to combine user-behaviour and shopping data with AI-based templates using a variety of images, colours and calls to action to create dynamically generated personalised content to maximise performance.
3. AI, at heart, should be able to handle the volume and complexity of big data and infer appropriately.
4. Presents strong understanding of bid rules and hence budgets and performance across digital media.
5. AI can help track that single user across the digital consumer ecosystem, which is a big win in avoiding wasted eyeballs.
The AI examples that are relevant to us in media:
1. Voice recognition behind Siri and Alexa is Al based.
2. Google’s safe search, which recognises pictures and webpages that are inappropriate for children and have labelled content demarcated by AI.
3. Affectiva’s emotion recognition technology analyses facial expression and emotions, using AI to build on expressions and recognise and validate current ones, and is effective for brand responses on creatives or video themes to correlate brand value in terms of positive emotional responses.
4. Blippar’s image-recognition AI platform can understand pictures to bridge the experience between visual search and user experience. Jaguar Land Rover had an amazing execution for its Velar SUV launch, with a Blippar partnership on ads rendering up on mobile when pictures were taken of other SUVs using the app.
AI will affect our daily lives and how we interact and use certain systems, be it technology, transportation, healthcare or payments and bills, and use cases are still under way.
Examples of interesting cases that have seen the evolution of AI and are common examples as we study AI:
1. The first chess playing program, written by Christopher Strachey and Dietrich Prinz through continued learning of chess and checkers and game theory in the 1950s.
2. In the 1990s, IBM’s Deep Blue chess machine defeats world-class chess player Garry Kasparov. This example is popularised in many AI summits, and as IBM’s square focus on AI development and expansion. Most recently IBM’s Watson won against Jeopardy champions Rutter and Jennings in the US.
3. In the 2010s, Siri, Alexa and Cortana are all AI-driven technologies widely available for voice-activated searching, ecommerce and fulfilment operations at a household and business level.
4. Facebook, Twitter and Google
are continuously investing more AI into ad tech to glean better insights from big data for overall optimised targeting using the right signals, context and safe environments to communicate.
5. There is a lot of work in the financial industry that is supercharged by AI. For instance, companies such as Bank of America, Allianz and Credit Suisse use AI to identify vulnerabilities and suspicious activities to reduce overall breaches of customer and financial data. Chatbots are used as AI-powered phone assistants, reducing costs and improving efficiencies by answering commonly asked financial services questions.
6. Dubai’s own involvement on smart initiatives have been noteworthy. 25 per cent of all transportation trips in Dubai should be smart and driverless by 2030, which is part of Sheikh Mohammed’s strategy to make Dubai a smart and sustainable city.
7. A part of Dubai’s Future Accelerator programme initiative too, launched by Sheikh Hamdan bin Mohammed, is based on creating the fabric of huge growth by partnering with entrepreneurs, government and the private sector. They will drive advances in public and private sector utility around blockchain, 3D printing, autonomous transportation, AI and robotics, drones, healthcare portals and more. These will use AI, machine learning and neural network development in many areas of Dubai’s future
The AI story is vast. Almost all areas of marketing that require a degree of trained automation will benefit from it. Be it programmatic, mobile, video, search, social and a combination of those with personalisation and relevancy. This will cut precious man hours, freeing them up for other parts of the business.
Automation, hyper-personalised experiences, customer delight, shorter time cycles, significance in AI rules and efficiencies in bidding are some of AI’s results. It’s the smarter way of adapting and cutting through the noise towards working innovation.