Artificial intelligence (AI) is no doubt the current hot topic everywhere. The technology is leaving its footprint in almost every domain and marketing is no exception. Almost all marketing gurus and experts are busy speculating how AI will influence marketing, consumers’ buying habits, advertising, futures of business, and so on.
Both our personal and professional lives have started experiencing the potential of artificial intelligence, thanks to technology like Alexa and Siri along with other advanced analytics tools that are based on machine learning. Isn’t that enough to give us a glimpse of the exciting future that AI promises to the marketers?
The AI revolution in marketing is the highest it's been within the last year. Thanks to the advanced data analytics tools, which have become both affordable and accessible to many marketers. Although still noisy, the availability of rich and extensive datasets are further empowering a growing number of marketers and encouraging them to adopt data-driven approaches to their marketing decision making process.
Since the winds of development have been blowing in this AI direction -- for now -- almost every marketer is talking and thinking about how AI will change the work they do.
While it is true that AI is still in its budding stage and we are not quite there yet, it is bound to keep getting better and better. As marketers, it is not enough to know how AI is changing marketing as we know it, but also what we need to do with this influx of AI, machine learning and advanced analytics tools. Let’s take a look.
AI is Reinventing Customer Interactions
AI is powering new experiences by creating more personalized marketing opportunities. According to a Google study, “more than 60 percent of U.S. travelers would consider an impulse trip based on a good hotel or flight deal.” While that sounds really exciting, it is also creating higher expectations.
The same study from Google also found that “57 percent of U.S. travelers feel that brands should tailor their information based on personal preferences or past behaviors. Furthermore, if a travel brand tailored its information and overall trip experience based on personal preferences or past behavior, 36 percent (over one in three) would be likely to pay more for their services.”
What does this mean for marketers?
The combination of AI technology with marketing strategies will help them create new levels of consumer interactions, which is not only simpler to conduct but also more instantaneous. However, this means that consumer expectations will be higher as well, posing both new challenges and opportunities for brands.
As far as opportunity is concerned, marketers can now fully realize both personalization and relevance. For instance, digital ad platforms can already achieve better levels of communication than before, thanks to search platforms, YouTube, and other social media sites. When this is combined with "customization" made possible by AI, marketers will be able to tailor-make campaigns to suit the consumer intent in the moment.
Campaigns and customer interactions will eventually become more relevant end-to-end. Marketers can take into account all data they have in their arsenal, including their purchase history and contextual relevance, and optimize them on the go, in real time.
This, however, means that they will have to work with thousands of planners at the same time. This can be a big challenge for many.
What You Need Do?
Focus on data quality. In the age of AI-enabled marketing -- data quality is paramount. Advanced AI systems that are based around neural networks and deep learning need a lot of data. Collecting a large quantity of data is therefore important; however, the quality of the data is something marketers cannot compromise for the sake of quantity.
If you study the algorithms behind AI systems, you will find that it is just data crunching but it is done in more sophisticated ways. It therefore becomes difficult for the algorithms to identify meaningful patterns from noisy or poorly measured data. This will make it almost impossible to make good predictions upon which marketing strategies are based. Hence, data quality is paramount.
So don’t just stop at collecting as many data points as feasible, but also ensure that every data is properly measured and thoroughly documented, before using them in your business decisions. This is the only way to get more value out of the AI analytic tools.
Infusion of AI is Taking Automation to A New Level
Instacart is using Google’s open-source machine-learning platform TensorFlow to predict the sequence its shoppers follow while selecting items at a store. According to the company, “This approach has reduced our shopping times by minutes per trip. At scale, every minute saved will translate into 618 years of shopping time per year.” That’s a lot!
Infusion of AI is taking automation to new levels and that’s basically a good news for decision-making executives, as their time will be freed up. Marketers can now intelligently automate simpler, repetitive tasks and allocate more time to areas where human focus and input is needed the most.
There are some tough, complex and difficult challenges marketers still face and they aren't going anywhere. By intelligently automating some of the mundane tasks, marketers can put more time into these challenges and that’s a good thing.
Besides, marketers and sales can invest more time in human interactions with customers, which is really becoming of utmost importance as consumers are becoming even more digital. Customers are becoming and more used to automation, thanks to their personal smart AI-powered devices and tools.
The human part of a company’s relationship with a customer, therefore, is becoming increasingly important. With their time "freed-up," marketers can focus on spending time with human interactions with their customers and target audiences.
In addition, marketers have now increased time resources to push the boundaries of creativity for their marketing campaigns. They can use AI and machine learning to spark new ideas, creating new media platforms, and finding new ways of telling brand stories, and so on. This eventually can help the potentials to improve the quality of creative work in advertising as a whole -- and that again -- is an interesting prospect.
The challenge for marketers here, will be to have a higher level of digital literacy and a clear understanding of AI and machine learning than they currently have. Besides, marketers must give more emphasis on the decisions that need creative thinking and human input to create a deeper and more meaningful customer relationship.
What You Need Do?
While automation is great, not everything should be automated. Automated (driver-less) driving cars, buses, trains and trucks have already freaked out people enough as they mostly do not understand AI. Recently a self-driving Uber killed a pedestrian in Arizona in a fatal crash. More of these types of accidents are likely to follow this one. Things can happen -- and the bugs will need to be worked out.
So, do you think it will be easy for people to accept AI that easily? Even after concerns with all of these things that can and will happen at first? When people (both customers and the work-force) think about AI, they only think about robots, driverless cars, and tech giants.
The solution is to go slow. Your customers don’t understand algorithms and predictive analytics. For some consumers, seeing ads that are targeted at them (based on their search patterns and history) can be a magical experience -- and they might appreciate it.
Yet others can see them as opportunities for misuse or worse. Consider the chaos and the series of debate going on around how Trump consultants exploited the Facebook data of millions of Americans during the 2016 election. Consumers, in general, distrust many of these smart AI-based systems.
Therefore, automating every aspect of your marketing process is not really a good idea -- especially at this very early stage adoption. How likely are you to really trust the claims of some new startup, stating that they use AI system to write better emails, creative copies, or Facebook posts than other experienced human copywriters? Of course not. Some of your marketing process need to retain the human touch. Go for automation when it has an advantage over humans, when it makes sense to do so -- and not just to lower costs.
Conclusion
A lot is happening in the world of marketing with respect to technologies like AI and machine learning. Marketers need to see this technology beyond its data analytics capabilities. It is time to think of this technology in terms of the consumer needs and not just succumb to the inflow of technology innovation.
It is good if you want to invest in AI but make sure it is a purpose-based, value-creation, and customer-driven innovation. When investing in AI, marketers must first -- themselves -- have an understanding of the powerful potential that AI has. Only then can they shape marketing and build consumers’ trust on this technology.
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