Siri and Cortana have applied for your role: The rise of AI in Marketing
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Jonathan Seal, Strategy Director at Mando presents the key headlines from Mando's recent whitepaper, compiling findings from senior marketers from British and global brands.
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Siri and Cortana have applied for your role: The rise of AI in Marketing
- 1. The rise of AI in Marketing Siri and Cortan a have applied for your job
- 3. “Every aspect of learning or other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it” Mission statement of the Dartmouth Conference, 1956, where the term ‘AI’ was coined
- 4. 1. Understanding the big trends 2. Hyper-personalisation 3. Automation anxiety 4. The tech transition 5. The need for speed 6. Rise of the machines
- 12. Hang on… Sorry, there’s a lot going on here. Could you start over from the beginning. Who are you again?
- 13. 4. The tech transition
- 15. 5. The need for speed
- 16. 6. Rise of the machines
- 18. THE RISE OF AI IN MARKETING Siri and Cortan a have applied for your job
Editor's Notes
- [Good morning]. Thanks for coming. We now it’s never easy to take time out of your day. You’re all busy and important people. But just how important, and will that remain the case?
- That’s the question that was inspired by a BBC report about some research (Oxford university and Deloittes) on job automation over the next 20 years. Market researcher 94.2% risk, Junior marketers = 33% risk Now at Mando we love to Provoke, and so we laid down that gauntlet in a couple of round table dinner events. We brought together marketing and digital professionals for leading brands in a couple of round table dinner events, to get their perspective on the impact of machine learning and artificial intelligence on marketing.
- We know that there is huge potential for AI to transform our lives, and to transform the relationship between businesses and consumers. As you can imagine with participants covering retail, service providers, transport, academic institutions, technologists and charities, the conversations were incredibly wide-ranging, and with very diverse perspectives. However, some key themes emerged that the report covers…
- Firstly we pulled out some big trends and the current direction in AI that our participants observed. Hyper-personalisation looks at the opportunity to use machine learning in marketing to move towards an audience of one Automation anxiety looks at some of the potential fears and challenges that applying AI in marketing and communications can bring The tech transition explores the period of shifting activities and roles across machines and people The need for speed looks at business models and disruption in a world where startups can exploit the power of AI as a cloud service and compete with global giants Finally, rise of the machines picked out some practical principles for bringing machine learning into the daily role of marketers.
- Welcome to the machine. If you take a step back and look at the “iPhone decade” we’ve just finished living in, it’s clear that it’s been pretty transformative. We’ve seen a number of science-fiction predictions come to pass and that has set the bar VERY high for consumer expectations of what’s possible with digital. [Examples: video calls, geo-location services, passive health metrics). However, it’s also true that while we can create a very compelling individual experience (say on a device or at an event) what we haven’t been able to do it make that a experience coherent and contextual – because that demands a level of machine intelligence that just hasn’t been possible before.
- So what we’re seeing is all the big players, including these four, invest massively in AI research, either buying up companies that are progressing in this area, or building in-house capability. [Mark Zuckerberg reference to Iron Man’s JARVIS.] Why? Because they all recognise that this is a key battleground for customers over the coming years. If these businesses can move from very simple rules on how to engage with customer and in what way, and get towards interacting based on emotion, context and nuances of language then they have the potential to connect in a much deeper way with customers and embed themselves into their lives.
- And we’re making progress… In 2014 a computer program successfully passed one interpretation of the Turing test by convincing 10 out of 30 judges that it was a real 13 year old Ukranian boy for whom English is a second language. Even though this was a very flawed and limited approach, it’s clear we’re heading into territory where machines have much more sophisticated and comprehensive ability to engage with humans in a seamless and naturalistic way.
- Much more recently, Google announced that it’s DeepMind team had used their AlphaGo AI to defeat a Go grandmaster (exponentially more complex than chess). This is important because it demands much more flexibility of thinking, much more visual intelligence, and much more understanding of possible scenarios. These can then be applied to other areas. Again, in itself not that huge a leap forward but another chipping away – another milestone.
- So what’s the appeal? Where is all this investment leading us? Well for marketers, the primary attraction is that it moves us towards a market of one. We know that people want a seamless and coherent experience, with things tying together across devices, across visits, and bringing in a whole bunch of personal context that we know people carry around with them online. That’s impossible to do currently, because we can’t make sense of all that big data and we certainly can’t do it at scale across all our potential customers. But if we can, we know it’s possible to weave these experiences together in a much more compelling way.
- Facebook M here is currently run primarily by people with superficial requests delivered automatically, but as AI takes on that service more and more, then the customer’s experience can be genuinely seamless as they just ask their digital concierge to sort out these things in conversation. For a customer, that’s great. But as a brand, think about the potential implications on our ability to market effectively. In the old world, if a customer saw something they liked online they would follow a link, see a product in context and maybe related things, be exposed to cross-sell and upsell, and be far more exposed to the brand message. In the new world, the customer sees your brand through the lens of a digital concierge. One implication might end up being that it’s far more important how easy it is for an AI to access your services, rather than the customer directly. In effect, we may have to become better at marketing to machines.
- So we have amazing potential, but there are risks, and I don’t just mean the Stephen Hawking, robot terminator apocalypse risks. One clear risks is that people really value human engagement and connection. We’ve seen this with all forms of automation. While there are efficiencies and it works well under some circumstances, in others it creates resentment and frustration. But with AI there is a new concern in that customers may not know whether they are communicating with a real person or not, and this creates a lack of trust.
- One brilliant example of AI being used to subvert marketing is this. One guy (Roger) set up a basic system that identified predictive telemarketing numbers and then routes them through to his AI. This consists of a set of basic sound snippets and some larger sequences that it uses to try and keep telemarketers on the phone as long as possible. The AI is training itself to get better at keeping telesales people on the phone for longer. He’s now trying to get Kickstarter funding to progress this further.
- So the reality is many of us are already using machine intelligence to support marketing activity, we just may not be aware of it. Everything from A/B & multivariate testing, programmatic advertising, sentiment analysis all use machine learning tools to augment our capabilities. We’ve seen lots of tools recently use facial recognition to layer on emotional context to marketing and allow better understanding of engagement. The key difference is that while a few years ago trying to leverage any of this would have meant multi-million R&D budgets, they are now being made available through 3rd parties as cloud SaaS models. The marketer of today is genuinely able to stand on the shoulders of giants.
- But what does this transition from people to machines look like? Well, one view that came out strongly was that we’re not looking at machines taking people’s jobs. Throughout history we’re seen technology advancements have created far more jobs than they’ve removed, but they do change roles. For marketing, it’s clear that the focus will be on things that machines are typically poor at: intuition, creativity, empathy, freeform problem solving – essentially what makes us human.
- It’s a massive cliché to say that we’re living in a time of acceleration. We get that. But we often think that the need for speed is about technology. In our conversations, it emerged that the need for speed is really about being able to adapt to changing business models and consumer demands. Yes, technology can be an enabler to that, but it’s not the focus. Now where AI and machine learning become really interesting is that they enables us to collapse down the time taken to trial something, iterate, gain feedback and then move forward. It’s about helping us gain insights from data more rapidly so we can make decisions and outmanoeuvre the competition. [Legacy of old systems and buildings for example can be a real anchor – important to be flexible to survive]
- The final theme that emerged was around the challenge of embedding AI principles and tools into our daily work. We pulled those out into some key stages: Definition: Define and validate the problems you feel your business faces and how AI could support this. Business value: Before any investment - will it increase speed to market or help make your products/services more personal to customers? Feedback: Robust and rapid feedback model to allow your AI technology to adapt to new data and changing needs. People-centred: Your team is still your most critical asset - put them in the driving seat of any AI implementation as their buy-in and adoption is critical for success. Keep looking forward: For new opportunities to use AI to automate existing processes, freeing up the team to flex, adapt and add even more value for customers in other ways.
- It’s very easy to see AI as some kind of existential threat. A kind of sinister HAL monster that will ultimately consume us. But it’s far more likely that AI will for the foreseeable future be a tool that enables us to augment our existing abilities and create far more compelling touch-points for customers. Embrace it.