In many ways, Artificial Intelligence and marketing seem fairly connected and cannot be considered separately from each other. Brands have been using this multi layered technology to engage with customers, by analyzing data to derive a far deeper understanding of what their consumers want. According to research from Demandbase, 80% of marketers believe that AI will revolutionize their industry by 2020 and change the way how marketing is done. However, only 10 per cent are actually using it today. This clearly depicts that even when marketers have recognized the vitality of AI adoption in campaigns and content, few have put this into practice. No wonder as AI advances, so will the opportunities for marketers but only if they act proactively to take advantage of them. Below are 6 applications of Artificial Intelligence in Marketing:
1. Conversational interfaces
Brands have been using AI powered conversational interfaces to bolster customer engagement. Chances are you’ve already used a conversational interface, may be in the form of an automated assistant, a chatbot, or simply Siri/Cortana. Natural Language Processing (NLP), is helping marketers to gather personalized data about individuals over time. For example, quality chatbots like Amazon’s Alexa note your preferences and offer tailored or customized recommendations – to which you then reply. These dialogues help marketers to identify important factors to customize their marketing campaigns. In the near future, seamless vocal interactions will characterise how humans communicate with technology.
2. AI powered content creation
For the most part, machine learning techniques focus on deriving meaningful interpretation by processing corpus of data. Eventually, their application will extend beyond this to take on creative work. By 2018, Gartner predicts, 20% of all business content will be authored by machines. Currently, machines can create content with simple and structured rule sets and formats such as:
- Profit and loss summaries
- Quarterly business reports
- Hotel descriptions
- Real-time stock insights
- Sports game recaps
Coca Cola, for example, has shown interest in automated narratives. These narratives are used to convey key data insights and trends in colloquial human language. In future, marketers can use such insights to make relevant ads. Likewise, Athletic clothing brand Under Armour has put another content creation concept into practice. In cooperation with IBM Watson, it has built Record app which combines app data with third party metrics to offer training and nutrition advice. If you are training to run a marathon, for example, it would take into account the weather, the time of day and your nutritional intake when offering personalised routes.
3. Personalized and Targeted ads
How can businesses squeeze more ROI out of ads?
One would say: Better targeting = Better ROI
But there are two aspects of targeting: one is Retargeting and second is Predictive Targeting. Retargeting absolutely is not the same as Predictive Targeting. Predictive Targeting goes beyond a user’s browsing history (Retargeting) and takes a lot more into account and will often expose hidden patterns that are sometimes counter-intuitive. Companies that have true predictive product recommendations will use a greater variety of user and item affinities, and these recommendations will learn over time from thousands of data points, and keep changing and adapting along with your users.
Retail brands know which products each customer really wants and they also know for each product, on any given day: who are all the users that have an “affinity”. And these lists change every day, along with each users’ activities. They rely on customer info to send personalized offers and recommendations that will resonate with their market. Team this with AI’s ability to create quality content, and marketing campaigns will automatically fine-tune themselves to meet individual requirements.
M&C Saatchi showcased the extent of future ad targeting with an AI poster campaign based in London. With the help of a camera and genetic algorithm, poster measures the emotions of onlookers, evolving to accommodate them. And, if a certain ad doesn’t provoke the intended reaction, it can be regenerated to gauge onlookers’ interest.
4. Visual AI
Visual technology is helping marketers to transform the way a brand connects with a consumer. It is going to create a major disruption in industries like Fashion & Apparels. Amazon Echo Look is a prime example of this which encourages consumers to share their favorite outfits.
To date, Amazon has mostly relied on customers browsing on their website for products and clothes to buy. Echo Look is their first step toward empowering their customers to purchase products via Selfies instead, and it equips the company with trends of visual data so their artificial intelligence algorithms can learn our favorite clothes, styles and products and suggest the best of recommendations in future.
Visual AI is helping companies to take personalization to a new level and make shopping experience even more frictionless because undoubtedly, a consumer who is visible as more than a name is far more useful to craft marketing campaigns and gain consumer trust.
5. AI-driven Sales Forecasting
AI-driven sales forecasting aims to give marketers, CROs, sales leaders, reps and sales operations executives 360-degree visibility into sales forecasts, pipeline health and sales performance. Marketers can now compare sophisticated inbound communication side-by-side against traditional metrics to help answer difficult strategy questions. With AI marketing, there are no longer questions about whether or not a prospect is ready for a discussion, the data provides the answer and accordingly, engagement activities can be planned.
6. AI tracked customer journey
It’s all well and good putting together a remarkable AI powered campaign, but knowing exactly when and why a customer engages with a message is quite arduous. Marketers often attribute customer decisions to the last action they made, trimming out many touch points and limiting how much can be understood about the customer journey, referred to as on-boarding in marketing terms.
However, Google’s new service “Attribution” is able to track and measure the results of marketing across personal devices and channels. By consolidating and analyzing data from different Google services like AdWords and Analytics, Attribution creates a more complete picture of customer on-boarding, right from the initial brand impression to final sale.
It goes without saying that marketers need to keep a check on the increasingly fast paced AI development. Unsurprisingly, big resource rich companies have edge in leading the way. But whilst applying new technology is part of a successful strategy, the crux of marketing always remains the same – focus on the customer journey. If a marketer can use AI to track that journey from beginning to end, and then create a data informed dialogue, it would ease the task of finding out what people really want. Perhaps AI powered “Smart” marketing could even solve the ongoing millennial dilemma. The question is, if AI can tackle so many marketing tasks, where does it leave marketers themselves?