AI Is Shaping The Future Of Digital Marketing - What To Expect In 2021?

By Dhanesh Haridas, Epixel Solutions LLC

The first thing that comes to mind if you hear about AI will be robots. Why is that so? The reason is the recognition ability of a human being. We consolidate and encode every memory using some associations so that we can easily retrieve the memory in time. What if such abilities of human beings are leveraged using artificial intelligence?

Marketing needs great sales force skills to acquire customers and it doesn’t happen overnight. Even people with multiple skills won’t be able to make it, why? It’s important to learn customer behavior but what if the customer group is broader? AI can help companies and sales force to analyze not just a group, in fact, everyone! All it matters is to feed the machine with enough data so that it can analyze patterns and generate insights.

Let’s see how AI shapes the future of digital marketing and what to expect in 2020.

AI In Digital Marketing: From Predictive Analysis To Image Recognition

Digital marketing aims to spread brand awareness and drive more sales in business. If a business can provide customers the products, they want then sales will be achieved. AI in digital marketing is evolving and still in the first phase. Let’s see the first phase of AI which is applied and experimented by different brands to the upcoming phases under development.

Predictive Analytics

Predictive analytics, where the system or machine predicts the future of business, backed with proper data. That is, the present data and historic data are together analyzed to make predictions about future business events. Forecasting is the exact term to use in this context and it’s highly demanding nowadays in digital marketing.

Benefits Of Using Predictive Analytics

• Increase business efficiency with data forecasting
• Gaining upper hand over competitors
• Make smart decisions based on the generated insights
• Meet consumer expectations based on demand

Case Study: Predictive Analytics In Digital Marketing

Now that we learned how predictive analytics works and its benefits, let’s see a case study on how it can be implemented.

Caira started a ceramic product manufacturing company back in 2015 and was making a good profit. At the end of 2019, she wanted to make some strategy to focus on increasing less popular products. She invested in data analytics and generated the much-needed output for making her strategy into reality, i.e. predictions based on present and previous year sales.

The system generated some useful predictions to increase the sales backed with enough data. Caira, inspired by the data-driven insights, made a strategy and got expected results.

Unsupervised Learning & Data Clustering

Discovering the hidden patterns in business is the basic goal of unsupervised learning. In this type of learning, the algorithm isn’t provided with any data labels, the algorithm itself has to find the data structure. This method of finding data groups in unsupervised learning is clustering.

This process is carried out for problem-solving and structuring the unlabeled collection of data. Data categorizing or clustering is preferably applied in machine learning. This process is known by various terms like data management, data classification, etc. However, the contexts also differ for each term, also in terms of the objectives. Digital marketing strategies can be thus made with more accuracy by meeting the goals of all customer groups.

Benefits Of Using Data Clustering

• Find hidden business patterns
• Get control of your business with complete data analysis
• Leverage the machine’s problem-solving ability
• Data grouping is made easier

Case Study: Data Clustering In Digital Marketing

Caira after implementing her strategies found out that warehouse management is inefficient. The warehouse staff was called and asked the reason. The warehouse data looks insignificant as they weren’t using the previous year’s stats for comparison. She later found that they weren’t even properly categorized for easy analysis.

She collected all the spreadsheets and digital data, fed them on the system without any segmentation. The machine analyzed the unlabeled data and found the hidden warehouse patterns.

She used these so-far unused data to find business patterns and implemented them quickly. With demand forecasting, she is now able to keep stocks based on the demand. She then collected all other business-related data and fed it to the system so that she won’t miss them anymore.

Natural Language Processing (NLP)

How far do you think the data is structured and in a useful form? Guess what, only 10-20% of business data is in a structured form, the rest is still unequipped for analysis. Unlock this unstructured data with natural language processing. Machines are now taught to find patterns from textual forms used during human conversations.

First, the machines have to learn natural language understanding and then proceed forward to natural language generation. Understanding is a hectic task for machines than generating natural language! It follows certain steps for understanding the process and the final output helps just like data clustering. In the digital marketing sector, NLP is in the processing stages, and if this becomes a reality then we will witness a whole new brand revolution.

Benefits Of NLP

• Unstructured data can be unlocked to find useful insights
• The best tool for sentimental analysis and other AI applications
• The efficiency of documentation processing and accuracy can be increased
• Personalized chatbots and speech recognition engines can be built

Case Study: NLP In Digital Marketing

Caira faced a challenge while feeding the machine with data, her staff were sending information via WhatsApp but not recorded in spreadsheets. These unrecorded data are known as unstructured data.

Caira can’t go through the entire chat to find these data, so she went for NLP to unlock the insights from them. These data after analysis helped her to arrange the products in her e-commerce store based on the sales rate. She even made strategies using combo sales, auto-shipping, auto-generated personalized emails for customers with abandon cart features, etc.

Psychographic Analysis

The vital part of every marketing strategy will be consumer analysis. Psychographic analysis plays a major role in understanding consumer behavior based on their interest, emotions, buying persona, lifestyle choices, etc.

A complete consumer persona can be built using the combination of psychographic analysis with demographics. It’s equally important to understand why people buy just like the way we analyze who the buyer is. A detailed picture is important in digital marketing. With these data, it’s easy for companies to set target-specific buyer groups and add more values as per change in their interests. The new phase of digital marketing is going to witness a great deal of psychographic analysis.

Benefits Of Psychographic Analysis

• Learn different groups of consumer persona
• Make interest-based marketing strategies
• Understand the emotional attachment of consumers over the brand value
• A new paradigm of selling can be established

Case Study: Psychographic Analysis

Understanding customer behavior was Caira’s next goal, she wanted to expand her business by acquiring a new service - uber-like transportation. A new segment that is worth trying for and for that she collected data from various resources. She used demographics to understand the age and gender of people who prefer taxi services.

But that wasn’t enough, she has to learn why they prefer it when they prefer, and many more values. Their lifestyle changes in time and psychographic was her best option. With combined efforts of demographics and psychographics, she could now learn the customer personas. So far, she was happy to find the behavioral patterns, and her new venture was again successful as she always makes smart decisions using data-driven technologies & artificial intelligence.

Is That It Or Are There More To Know?

That’s not it, AI has many other subsets of applications to shape the future. In time, you’ll learn more AI patterns and, in this phase, (2020), understand the above schemas. However, if you want to head more into this AI game in your digital marketing profile, it’s important to go for deep learning in each area.

The most important thing you must understand is that these insights might not be accurate and human logic must be applied. The deficit of human intervention can lead digital marketers or companies into a pitfall of wrong choices. Add human value to these machine-generated insights or predictions and then make the final decision. After a certain time, analyze the output, even these insights about goal analysis will be done by machines.

In short, the new phase of digital marketing will be based on artificial intelligence. Lots of experiments as well as applications are launching nowadays. Keep yourself on this track, use business intelligence tools to keep track of your business, thereby analyzing different key business metrics.

About The Author

Dhanesh Haridas, a passionate and enthusiastic businessperson who enjoys ever-changing technological updates. He is the CTO of Epixel Solutions LLC and has more than 10 years of experience in developing MLM systems for businesses ranging from startups to enterprises. He blogs about technologies like AI, blockchain, IoT, etc., and its importance in enhancing productivity and motivation in business.