Machine learning (ML) utilizes Artificial Intelligence (AI) to enable a system to learn a particular thing autonomously. While AI seeks to mimic human intelligence, ML forms historical data and applies that information independently to the performance of specific tasks. Eventually, with the increasing amount of data, the machine can learn from previous projects and enhance the accuracy of predictions and decision-making. Note that businesses accumulate a massive amount of data from direct marketing.
Direct marketing refers to how businesses communicate directly with their target customers, delivering messages through direct communication channels like email campaigns, social media, and phone calls. For instance, some enterprises leverage automatic dialing software like Call Cowboy and other similar options to automatically dial their customers’ numbers without manually entering each phone number.
Regarding the value of machine learning in direct marketing, a 2019 study revealed that 84% of business marketers expect to witness a significant amount of return on their investments in ML within a year. Some of the critical benefits of machine learning include helping a business analyze a substantial amount of data efficiently, enhancing the quality of data analysis, adapting to modifications and new data, and allowing a company to automate marketing processes to avoid routine tasks.
Furthermore, ML algorithms can help businesses understand trends in user behavior to predict how valuable these certain users might be in the long run. ML also plays a critical role in personalization, customer segmentation, faster evaluation, and so on.
To further emphasize the value of machine learning, read below for a list of a few advantages of machine learning in direct marketing.
1.Automated Email Marketing
The email subject lines of any business play a crucial part in determining the success of email marketing campaigns. These subject lines can draw people’s attention and encourage them to open the email from their inboxes. The good thing is that digital marketers can utilize machine learning in their email marketing campaigns to create highly effective email subject lines. With machine learning, marketers can use natural language processing and language generation tools to craft the most persuasive email copy and subject lines for their marketing campaigns.
Additionally, machine language can incorporate several components in the email copy. These include the formatting, narratives, descriptions, emotions, and call to action. Also, ML tools listen to a brand’s voice and email copies that catch the target audience’s attention. Furthermore,ML technologies can help marketers select and schedule the most suitable time for sending their company’s newsletters. They do this by predicting when email recipients tend to open newsletters. Consequently, such email scheduling can boost open rates and click-through rates.
On top of automated email marketing, it’s also worth mentioning that some businesses even utilize voicemail and SMS marketing software like Unlimited Ringless Voicemail and similar options to send personalized messages that’ll reach their target customers and grab their attention.
The role of marketers in a business is to develop hypotheses, test them, then evaluate and analyze them. This task is time-consuming, and the results can be incorrect sometimes due to the changes of information at each moment.For instance, marketers may require over four hours to evaluate a significant number of advertising campaigns. If they perform this evaluation daily, they’ll spend half their time considering the quality of marketing campaigns. But with the help of machine learning, this evaluation only takes a few minutes.
Additionally, one of the primary functions of machine learning in direct marketing helps businesses quickly make decisions based on a large amount of business data. Thus, companies can respond rapidly to modifications in the quality of traffic that advertising campaigns make if they utilize ML. Consequently, they can spend more time developing hypotheses instead of doing routine tasks.
3.Better Social Media Marketing
Social media marketing has become the focal point for digital marketing. Businesses today are conducting several marketing efforts such as content marketing and customer support on various social media platforms. In addition to these marketing efforts, thriving companies also leverage machine learning to use the power of big business data and improve their social media resources.
As a result, ML in social media marketing has become a powerful tool that helps many businesses optimize their marketing strategy. For instance, regarding reputation management, ML helps digital marketers recognize customer interactions, complaints, and reviews that require quick responses on social media.
Furthermore, note that ML can analyze terabytes of data to learn how customers interact with particular content types and themes. And with social listening tools partnered with machine learning, businesses can automatically track hashtags, keywords, and brand mentions on various social media sources. Moreover, the insights that digital marketers or business people gathered from such analyses help them create content that significantly impacts their target customers.
Thriving businesses aim to know their target customers using descriptive data such as gender, age, and hobbies. It’s because the more they learn about their customers, the more machine learning can develop a personalized experience for them. Hence, to become a market leader, many digital marketers today focus seriously on improving their personalization efforts. However, note that delivering highly personalized experiences requires automation. Thus, machine learning comes into the scene.
When it comes to ML-powered automation, this approach helps businesses provide a scalable strategy to personalize all aspects of their company. Machine learning algorithms’ operating principle automatically identifies the relationships between data and learns the better data-driven experiences to deliver. It also provides a variety of techniques that can help in the personalization efforts of the businesses for their customers.
Additionally, since customer experience and conversion are the primary objectives of any business, it’s crucial for business leaders to keep themselves updated regarding the current ML algorithms. This helps them achieve their personalization goals and stay ahead of the competition.
Advertising is a crucial marketing avenue for digital marketers. In previous years, marketers conducted advertising manually using decision-making strategies like considering which advertising channels are effective, the most suitable timing of the ad, and the appropriate duration of an advertising campaign. However, certain human limitations restrict this manual advertising process.
But with machine learning, businesses today can improve their marketing campaigns’ performance by reaching potential customers at the appropriate time. ML’s predictive capabilities can efficiently improve advertising campaigns during a customer’s life cycle to optimize conversions, improve Key Performance Indicators (KPIs), and increase a company’s return on investment.
On top of boosting ad performance, ML can also access relevant data sources from social media platforms to generate inputs that’ll help businesses reach their primary target customers more accurately. For instance, after analyzing a big pile of relevant data, business systems that utilize machine learning might conclude that young females who like a particular type of music and are interested in the beauty industry are more likely to download an app.
6.Improve Customer Acquisition
Leveraging machine learning is one of the best strategies of successful marketers when it comes to customer acquisition. It’s because ML can be a highly effective technology to combine with a company’s customer and prospect database. While AI can think independently, machine learning can automate routine tasks and utilize predictive analytics that boosts significant growth. It’s AI’s central point for a company’s customer relationship management (CRM) tool and can be one of the core elements to improving customer acquisition.
That said, many businesses incorporate ML with CRM due to several incredible features these tools provide. For instance, CRM with machine learning helps digital marketers collect essential customer data, track engagements, monitor purchases, and help them deliver an excellent customer experience. CRM combined with ML can also save companies time and money, which allows them to use funds in other aspects of their businesses, especially regarding developing strategies to improve their customer acquisition efforts.
7.Maximize Customer Lifetime Value
Since acquiring new customers can be costly and often influence a company’s bottom line, retaining customers and developing customer lifetime value is vital to increasing conversion rates. And the good thing is that machine learning can help businesses keep their existing customers and boost customer lifetime value. Notably, digital marketers can take advantage of critical data by using machine learning to create a comprehensive marketing approach that causes customers to purchase more. Also, ML-empowered marketers can build long-term customer loyalty and predict what customers might need after their previous purchases.
In the long run, ML-driven direct marketing empowers all businesses to see better ROI from their marketing efforts. It helps them make data-driven decisions, determine what strategy works and doesn’t work by forecasting sales, and accelerate customers’ purchasing decisions. As a result of leveraging machine learning in direct marketing efforts, digital marketers can grow their customer lifetime value at a proportion of the cost when acquiring new customers.
8.Better Customer Segmentation
Sorting customers into segments to find patterns in their behavior is paramount to successful marketing. Instead of relying on traditional marketing methods like intuition for segmenting customers, digital marketers today can employ ML-empowered technology to ensure better customer segmentation and excellent marketing campaign results.Since machine learning can handle complex data analysis on its own, it can sort through an endless number and size of segments and only requires little human maintenance.
Furthermore, regarding analyzing behavioral patterns, humans have biases that can give an inaccurate picture of the situation. For instance, digital marketers might assume that most video game players are just young males and completely neglect other segments of video game lovers. But with machine learning, digital marketers today utilize this technology to find hidden behavioral patterns that an average marketer might not see.
ML algorithms can look at business data without human biases, understand several dimensions based on customer data, and deal with how customers move from one segment to another in the long run.
9.Provide Excellent Customer Experience
ML algorithms can coordinate and manage workloads associated with tools, including keyword searching algorithms, neural network chips, and data analytics programs. Generally, digital marketers can leverage ML to improve the speed and efficiency of these tools. Thus, with machine learning, digital marketers can provide quick and more efficient customer service. Also, with ML algorithms, marketers have a higher chance of quickly determining what customers need and guiding them where they intend to go.
On top of enhancing the customers’ overall experiences with a particular brand, machine learning can also help improve a company’s ability to determine fraud. ML algorithms can scan and review more business transactions quickly and more accurately. After some time, ML algorithms can learn better to determine indications of potential fraud or identity theft.
Furthermore, robust ML algorithms can even learn about customers’ intentions when they engage with specific brands. They can do that by gathering previous customer data related to the customers’ location or the product that causes a problem. Eventually, by implementing all these approaches with machine learning, digital marketers can effectively deliver an excellent customer experience that helps them get and retain customers.
Chatbots are an effective customer support tool that enhances the customer experience online. With chatbots, digital marketers don’t need to manually respond to customers as ML-powered chatbots can automatically respond to customer queries with a high rate of accuracy. Since chatbots are learning and improving autonomously, they’ll deliver a far better customer experience with more chats.
Furthermore, with relevant data gathered by ML-powered chatbots, marketers can analyze them using another ML algorithm to develop insights that they can utilize to maximize their marketing efforts.
Overall, machine learning is one the most valuable technologies of today that digital marketers leverage in their direct marketing activities. ML opens a new age of understanding customers effectively and improving customer experience. Furthermore, digital marketers utilize ML algorithms to process and analyze critical business data and get insights into the customers’ behavioral patterns and purchase history.
As a result, many businesses have become more informed about their potential customers and the marketing strategies they must implement to captivate their target audience’s attention. In the long run, it’s likely to become more apparent how machine learning significantly impacts the way businesses interact with customers and provide a more personalized customer experience.