Digital marketing needs you to manage different channels that include digital direct, search, email, websites, and social media. Media managers of different companies are always looking for multiple tools to improve marketing efficiency. Also, tools reduce manual labor and save time and money.
Machine learning is gaining traction as one of the best ways for cost optimization, trend recognition, and task automation. However, adopting machine learning will not guarantee immediate results. It is imperative to understand how machine learning can help in digital marketing.
Then, you have to figure out strategies that are in sync with your business objectives.
Now, when you are looking for ways to implement machine learning in digital marketing, you will come across artificial intelligence. There is a difference between machine learning and artificial intelligence.
What is the fundamental work process of machine learning?
Machine learning is a sub-category of artificial intelligence (AI). In the case of AI, it uses algorithm-driven machines for completing its tasks in an intelligent way. Whereas, machine learning involves feeding “data” to teach itself on how to improve and optimize the insights gained from the data.
As you continue to feed more data into the machine, it will improve and refine the algorithms. The changes will be reflected in the output. The more data it analyses, the more accurate the algorithm or model will be.
Why is machine learning influencing digital marketing?
The primary reason why machine learning is influencing is that machines are capable of quickly analyzing a wide range of data. They are efficient and chances of human error are almost non-existent. A machine can identify patterns and trends.
It helps the marketing team members to save a lot of time to create campaign strategies and specialize in other areas. Also, analyzing the data helps the marketing team to get in-depth insights into optimizing the marketing strategies.
By the end of 2020, developers will add some sort of AI functionality in at least one service or application. Along with that, by 2020, 85% of the customer interactions will be managed by AI’s with no human involvement.
The primary goal of machine learning is not to take away the jobs of digital marketers. Its main objective is to make the jobs of digital marketers easy.
Why is the sales process suitable for automation?
Automation is useful when it is applied correctly. However in sales, instead of automation, artificial intelligence is the key. The process of sales conversation has changed a lot. Customers these days are looking for a more personalized experience.
To offer a compelling and customized experience the sellers need to utilize a fusion of human intelligence, AI, and empathy. The sales engagement tools that use automation for streamlining workflows and eradicate mundane administrative tasks can save time for salespeople. They can use the time to make connections with their customers.
Selling is an art, especially while working in a remote environment. When a genuine human connection is combined with AI, it creates a significant impact with more conversions.
What are the primary elements to ensure success?
Customer engagement should be prioritized. To provide maximum value to the customers and meet their demands, salespeople need to be equipped with proper content and guidance. They should know what to say, what to do, and what to show in every conversation with potential buyers.
Intelligent content management, clear guidance and better buyer engagement data is important for success. Collaboration across go-to-market teams is also important for customer acquisition and retention. Teams need to work in true partnership.
How is machine learning used in digital marketing?
Machine learning is already being used in multiple areas of digital marketing. Here are the following ways businesses are using it to enhance marketing efforts.
1. Customization/personalization
Every customer wants to speak directly to a brand. 52% of the customers tend to switch brands if they don’t personalize their responses with them. With advanced machine learning, it is possible to implement customized communication to make your customers feel special.
Personalization in e-commerce means offering the customers with the right information/update/content at the right time. This could be as small as an email with information about products they are interested in, like the “recommended products”.
2. Optimized content
Machine learning can help in crafting content that resonates with your target audience in a better way. There are a lot of tools that help in changing the message tone and individual words that can impact your audience.
Machine learning uses A/B testing to learn more about the products and services you offer. You can experiment with different content on every email, article, headlines, paid social media ads, and call-to-action.
Google is the best example of this scenario. The search engine has become extremely intuitive. It has improved the capability to learn about your intent and searches. All this has become possible due to the machine learning capabilities. At present, it can offer you with more relevant search results.
3. Better bidding
PPC is the most data-heavy channel of marketing. Previously, the PPC executives and managers used to spend long hours in analyzing the datasets and gain workable insights. Machine learning has eased out the process.
With Google’s Smart Bidding option, you will have the help of machine learning to optimize each campaign to increase conversions. Automation is also useful for budget allocation, retargeting the right audience, and reporting as well.
The role of a PPC manager is shifting. At present, they are needed to take on a more strategic advisory role and let the machines do the work. Facebook, Instagram, and LinkedIn have developed sophisticated advertising platforms.
4. Chatbots
Chatbots have revolutionized customer support services, especially of e-commerce stores. It is common to see a chatbot popup in the bottom corner of a website these days. This is done through machine learning to offer better service to customers.
Chatbots are used by multiple e-commerce businesses to answer basic questions and queries immediately. They learn from customer queries and responses to expand their array of data. Thus, it helps the auto-bots to answer better in future queries.
They are available 24/7 without any waiting time for the customer. Chatbots are the best ways to meet the demands of modern customers. Live chat support has the highest satisfaction level of any customer service channel.
At the end, it can be said that the machines cannot replace humans. It is used to improve the experience for both the customers and digital marketing teams. At present, people are craving for more in-person interaction. The true power of AI and machine learning is realized when it is combined with human empathy.
