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Moving towards a machine learning economy in marketing

As the world evolves to a more digitised era, new and emerging innovations will disrupt the way different industries operate. In the field of marketing, we have witnessed the transformation of marketing strategies to meet evolving consumer expectations. Traditionally, consumers are pulled to a physical shopping space and today, it has transformed to one which is highly digitised where products are now pushed according to the data received and analyzed by various businesses online.

With the Big Data Revolution, the processes involved in making sense of such data become even more complex. But the dawn of artificial intelligence (AI) and machine learning might assist in simplifying these processes. From various sets of algorithms to chatbots, how can these technologies really help enhance marketing performance?

Understanding the differences between AI & machine learning
Firstly, it is important to understand the difference between AI and machine learning as they are often used interchangeably. Machine learning enables computers and the applications that run on them to improve on their own as they do not require additional programming. This technology detects and predicts data, speech and certain patterns , which gets better over time as it is fed with more data.

On the other hand, AI is an umbrella term to describe the various ways a machine to emulate the different facets of human cognition, such as thinking. The latter builds up on the first, allowing for more accuracy to a similar query.

What we usually encounter on a daily basis is the technology of machine learning.

Machine learning in the market space
Machine learning can be an important tool in a marketer’s toolbox, as it brings shopping and content together. As consumers search for visuals online and take photos of items they like, machine learning will be able to give them recommendations based on AI-generated models. This reflects its great ability to analyse in real time every click on a particular item online to better understand a consumer’s preference, thus, building a personalized shopping experience.
The growth of digital media – specifically social media, shows that consumer trends can have far-reaching effects even within a short time span. However, the vast amount of data received by companies makes identifying and processing these patterns a very complex and resource-intensive task. As such, they are unable to take advantage of it before a consumer moves on, resulting in many lost opportunities.

Machine learning streamlines the process, by immediately identifying underlying patterns in data from a variety of sources. While humans are still needed to verify and explain these trends, machine learning helps in speeding up the analysis process. This allows us to focus on a speedy response to these trends instead of struggling to decipher what they imply.

Challenges in implementing machine learning
While machine learning has proven its competence in making marketing processes efficient, the fact that it is in its early stages poses some concerns to marketers. One concern in particular is its possibility to replace human jobs in various industries due to the speed at which it can process data . Yet despite its impressive performance, it is still unable to understand human-like nuances of communication. Due to these concerns, getting acquainted and comfortable with an autonomous system that lacks human-like facets poses a question on whether these systems would eventually acquire this ability in order to provide satisfactory, “human” service to a customer.

The future of machine learning in marketing
Marketers should be aware that the amount of data produced online will continue to grow, and thus, help from artificial intelligence and machine learning systems to assess it will be essential.

As machine learning is in its early stages, it seems that it still has a long way to go in terms of its technological maturity. Thus, humans will still maintain an important role which will be bolstered by these technologies as they can focus more on marketing and are able to direct and guide algorithms. Despite machine learning’s impressive capabilities, it is still only a tool as only humans can decide on the important questions, such as what solutions are needed for a company’s critical business problems.

As we witness these technologies and their functions evolve rapidly, machine learning has proven that it can enhance marketing performance due to its ability to process a vast amount of data while easily spotting trends to let marketers seize the opportunity while they stay fresh and relevant.

Scott Anderson

Scott Anderson is the Chief Marketing Officer at Sitecore. As the Chief Marketing Officer, Scott Anderson is responsible for all aspects of the company’s global marketing organization, including strategy, branding, product marketing, corporate communications and field-marketing. Scott has developed and led growth and digital innovation strategies for more than 20 years, primarily in the enterprise tech industry. He is a change agent that believes in the power of participation and the evolving role technology plays in connecting businesses with their customers.