Marketing is the business process of creating relationships with customers and finding the perfect conditions to satisfy their needs. This is probably why it's one of the fields that collects and uses a huge amount of data about a lot of things, including customers, website traffic, products and services, delivery, pricing and payment conditions etc.
With the explosion of online commerce and so many attractive offers, companies are urged to find innovative solutions to stay ahead of the curve. Continuing to keep current customers happy while winning over new ones requires a lot of work. Carefully analyzing and wisely using the collected data is one of the means companies can take advantage of to achieve their marketing goals.
This is where new technology is brought into play. Artificial intelligence and machine learning (ML) are an increasingly integral part of the marketing industry, helping digital marketers bridge the gap between data science and execution.
According to a PwC study published in 2017, 72% of business owners viewed AI as a “business advantage.” A different report by Smart Insights reveals that out of 100 senior marketers from different industries, 55% of them are implementing or already considering using AI in their practices.
In marketing, artificial intelligence is turning out to be of real help, allowing companies to process large amounts of data faster and more efficiently, to deliver customized messages, to identify trends and to predict outcomes. All these translate into high quality products and services, better customer support, more personalized offers and a stronger relationship with customers.
Let's have a look at the mentioned use cases and see how AI and ML are taking marketing to the next level.
Analyzing and filtering the data
As mentioned, marketing is a data-driven field. Understanding and properly using that data is key to enhancing the customers' experience, targeting, personalized services and many more.
The process of collecting, grouping, analyzing and interpreting the data is really time consuming and quite difficult for individuals. Companies can miss great opportunities because the data is too exhaustive or, in some cases, not relevant, or it takes too much to understand it and draw a conclusion. Moreover, humans can misunderstand or omit some information that could turn out to be crucial.
In this case, what artificial intelligence does is analyze the data, identify patterns and predict results or insights. And it does this much faster than any individual.
Analyzing the data is only the first step. Artificial intelligence can provide companies with fundamental information about their current or prospective customers. Based on the purchasing history, views, social conversations, to name but a few, this technology can tell marketing professionals what the customers like, dislike and how they really feel about the company, products and services.
Using natural language processing (NLP), marketers can take the pulse of the industry and analyse their brand presence, which can afterwards help them take the necessary measures to improve certain aspects. For instance, if there are customers in a certain age range or geographical location they don't currently serve, they can learn this with the help of AI and then create customizable products and launch targeted campaigns.
The same goes for performing sentiment analysis on social conversations. As an example, Samsung was able to detect and counteract customer dissatisfaction with a red tint on the screen of its newly-released S8 smartphone model. The company works with AI consumer insights provider Crimson Hexagon.
The “State of the Connected Customer” report indicates that 76% of customers expect companies to understand their needs and expectations. With the help of AI, marketers can understand who exactly their target audience is, thus creating a personal experience for customers/users.
Amazon, Netflix and Spotify have built their product offerings around the ability to provide highly relevant and personalized products. The same goes for Sky, which is asking customers what mood they are in and then use machine learning to provide the best recommendations.
Online searches provide a lot of information on what customers are looking for and it can be an important metric for marketers who want to use any piece of information to improve their products and offers.
With this purpose in mind, numerous ecommerce websites, Amazon included, have integrated AI capabilities into their search engines to make products searching smarter. The pioneer in this was Google, which introduced its machine learning-based algorithm RankBrain in 2015, encouraging many companies to follow in their footsteps.
Why are smart searches so relevant in marketing? Search engines can determine the links between products and suggest similar items, find relevant search results, and auto-correct mistakes. This way, customers can discover products much easier, even if they don't know exactly what they're looking for.
AI-driven chatbots have become the new norm in many industries, marketing included. Many online retailers are allowing customers to interact with chatbots to ask questions about the products or services. Some can even handle customer complaints, although they do not have the final saying in the matter, an individual is usually also involved in the end.
The introduction of such systems has saved marketers a lot of time on social conversation and has significantly increased the customer experience. Companies are also experimenting with smart chatbots, that can do much more the answer frequently asked questions. They can communicate with people using real-time, originally generated responses, while learning and upgrading with each new conversation.
While still in its inception, this technology is already being used by brands and retailers to sell their products. How exactly does it work? The same as traditional search only, instead of recommending product based on previous searches (using text), you can see products that are visually similar to one another. You upload an image of an item and the system recommends you similar items from different other websites.
This can even be taken to the next level. In fashion, for instance, visual search technology can recommend relevant products based on how customers look, helping them find items of a similar or complementary style.
More and more companies are keen on adding AI capabilities into their businesses, especially for marketing practices. Machine learning, NLP, deep learning and big data analysis are great tools for companies to gain more insights into their customers' preferences. This allows them to upgrade their services, provide more personalized experiences and even make sales forecasting and predict whether or not their goals will be met.
However, human presence will continue to be of utmost importance, as AI alone cannot be that creative and innovative, cannot design or execute a marketing campaign, nor can it understand cultural context. Also, companies and marketers alike need to fully understand artificial intelligence and what it can do to help them achieve their goals. Thus, it's best not to rush into adopting a technology just because it's a hot topic.
If you're planning to adopt AI, but do not know where to start from, have a look at this article Ready to implement AI into your business?