Big data and AI are the future of global marketing.
Working in the 21st century is a great challenge, because we chase higher effectiveness in a hyper dynamic environment, where our competitors are working 24/7. This review aims to explore and explain how big data and AI as a digital marketing tools can influence the customer decision making to become more predictable.
What are Big Data and AI?
Big Data and Artificial Intelligence (AI) are inevitably becoming a crucial part of businesses worldwide. No matter if they are big enterprises or medium and small companies, locally or globally oriented, the adoption of these tools can utilise performance by stimulating innovation and disruption. Therefore, to initiate the exploration of the topic, we need to answer to the essential question – ‘’What exactly do Big Data and AI mean?’’. (Positively, the terms have many interpretations, but analysing all of them is not the purpose of this review.)
Big Data is usually associated with two main concepts: data storage and data analysis (Ward & Baker, 2013). So basically, big data is collecting, managing, analysing and keeping information in a scale much larger than a regular set would do.
On the other hand, Artificial Intelligence is using computers and machines, programmed to act in a way that will facilitate our work. It ultimately differs from human intellect, because it cannot react like we do, it follows a code.
Why are Big Data and AI important?
Nowadays, due to big data opportunities, it can successfully collaborate with AI, enhancing the capabilities of computers while guiding them through patterns, based on collected information and vice versa – AI convert the collected data into series of decision and actions which lead to certain outcomes. Big data and artificial intelligence are notably important for developing a business, because by properly implementing them into the business strategy. There are several reasons to consider them as helpful management tools:
1. They are reliable. One thing is certain - computers do work day and night for weeks without the need of rest (of course they still need good maintenance and actualisation of systems). Computers are not subjective like humans and that is why they are more precise in their acts. Moreover, they can’t be affected by any emotions whatsoever.
2. Facilitate the processes. A computer can surely deal with more information than a human and it can do it faster and more accurate than us. (Dalio, 2018)
3. Provide better services. Following the first two principles then we can assume big data and AI help to serve better, because they also help to understand customers’ needs (e.g. personalisation) and provide them in a better way.
4. Raise efficiency and effectiveness of the company – Since industrial revolutions, machines produce more, which simply saves time, money and gives more opportunities to focus on improvements.
However, some limitations exist in to contradict the above-mentioned statements. For example, the computers and machines have more durability, but they cannot distinct right from wrong. They do not have the same perceptions as we are and most our important decisions are made under the subjective factor. Moreover, many people are afraid that robots will overtake the jobs and unemployment and poorness will rise. Another issue is the capability of processing information, because it grows every second and we start wondering if we would be able to handle it with available tools.
Plenty of points may be written on this area, but we are now approaching to our main topic:
How are companies using AI and Big Data to influence our consumer behaviour?
On the graph below, you can see the amount of used data since 2009 and compare it with 2017. It speaks for itself, doesn’t it? The truth is simple: the usage of big data will continue to increase according to the statistics and for the sake of their own wellbeing, the right way is to adapt and benefit from it.
Source 1: Official statistics, big data and human development
Examples of the impact of using big data and AI are circulating around us. In fact, 20% of all Google searches through the app, were made by voice for 2016. Imagine what will be the numbers by 2020? Users will expect better assistance by different tools in a way that their access to desired service will become easier (Google Data, Google App, Android, U.S., May 2016).
On the other hand, companies like Netflix, have adopted the Big data analytics and successfully implemented it into their strategy. Nowadays, simply by analysing the types of shows you preferred e.g. series or motion pictures, comedies or crime, European or American, the platform builds up a profile and next time you turn your device on – boom, you can find the newest shows that might be interesting for you.
In terms of consumption, it is challenging to shape one’s opinion, especially when a single reputation can be influenced by a photo of the bar posted on social media, while waiting to be served. One thing is certain: soon, even daily actions like vacuum cleaning, picking books from library, washing your car or going for a walk in the neighbourhood will be easily measured as an experience. Then, by analysing the data, companies can predict the behaviour of their customers, while following their psychological indicators and guide them toward the better product or service.
Doing so would be possible by optimizing the pleasure-arousal-dominance model and has been used form retailors to track down preferences of consumers. According to a research in the field of social media, people would continue to experience pleasure while on Facebook. The hypotheses were based on surveys regarding what users feel, do and expect during spending time on Facebook.
Other important areas where Big Data and AI may influence is post-purchasing experience and evaluation. Releasing our product or service, boosting it and create awareness until actual purchase is extremely hard. But after comes the hardest – consumer’s verdict. Brands can now be compared worldwide 24/7 by using tools like blogs, vlogs, reviews and critique sites. So is it possible to create a new type of Big data space, which would be based entirely on the opinions of consumers.
Engaging with people remains a great challenge for the companies, due to rapidly evolving environment and constantly changing needs of people. In such case, organisations need to develop tools to gain trust, build reputation and try to make the customers to spread this reputation. One possibility is the collaborative filtering, which combines techniques for evaluating experience by building network of exchanged comments, reviews etc. based on individual experience. Then imagine how companies can change our customer journey experience from the beginning by providing us with large amount of filtered information. For example, by searching reviews for hiking equipment, we may end up snowboarding in the Alps.
We unraveled in brief what Big Data and AI are, so now we may bring some examples from B2C and B2B companies to illustrate how do they work. Burberry is an English fashion company that has successfully implemented AI through big data into their systems. The way it operates is simple, but effective. They collect data from the mobile application about purchases, most common bought items, preference of order – online, click and collect etc. After they analyze the gathered information, an individual profile is created and each time the customer is in a Burberry store, the attendant is signalized. In this way, customers are offered about special prices, promotions and loyalty discounts. Moreover, the retail consultant can suggest different items that suits a recently bought product.
Naturally, players in b2b space also expect to be facilitated in their options. And there comes Watson - a system developed by IBM that is used to generate solutions. It can operate in different environments and provide detailed information on complexed topics. For instance, Watson capabilities for assimilating are higher than human’s. It expands to an extent which this AI can compress the process of what doctors learn through their education faster. That’s precisely why some hospitals are using the platform for various operations (not in surgery…yet).
However, according to the vice-president for global operations for Amadeus – Wolfgang Krips, the distinction between b2b and b2c is shifting away in IT area. It’s not a secret that not only people, but companies as well are becoming more reliable on computers. Considering this fact, it may be inevitable to replace people with machines, which means that a lot of jobs are already under threat.
Conclusion
The key factors for building a modern organisation are laying on developing strategies with digital presence. Keeping in mind that today's customers are more impatient, easily distracted and more unwilling to stay loyal, companies must become more creative to predict users’ behaviour. Collaborating with Big Data and AI are great possibility to enhance performance of organisations and change the prospects for customers’ mind in a way to guide their thoughts.