Digital Marketing in the Machine Learning Era

April 30, 2019

By Hari Krishna K

According to a research, the future of marketing lies in the way digital marketers work alongside machine learning (ML) based tools. Not surprising, considering artificial intelligence (AI) is already playing a huge role in streamlining marketing processes and making businesses more effective. As ML & AI become more commonplace in the digital marketing landscape, it’s imperative that digital marketers learn how to apply ML to their digital marketing campaigns.

Digital Marketing in the Machine Learning Era

What is machine learning?

Machine learning can be defined as an advanced tool that uses data to provide effective solutions to a host of complex digital marketing problems. ML benefits businesses by helping them discover business insights in available consumer data to streamline marketing processes.

Machine learning and artificial intelligence share a close relationship – while artificial intelligence (AI) develops the cognitive capabilities to augment or even surpass human intellect, machine learning (ML) optimizes certain problems by helping humans in a more efficient way.

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Impact on digital marketing

Although the long-term implications of ML are unclear, it’s already impacting the digital marketing landscape as we know it. ML tools have the ability to analyze extremely large sets of data and present understandable analytics that marketing teams can use to their advantage. In organizations using ML tools, marketing teams can find more time to specialize in other areas and use ML findings to gain new insights, optimizing their marketing strategies.

ML is being used by businesses to expand the understanding of their target consumers and optimize their interactions with them. However, with more information comes change, which will occur much faster than what digital marketers anticipate. This year, IDC Futurescapes expects that 75% of developer teams will include some type of AI functionality in at least one service or application. In addition, by 2020, 85% of customer interactions will be managed without human intervention, according to Gartner.

Regardless of the buzz, ML isn’t here to take over the jobs of digital marketers. Rather, its main use is to help enhance digital marketing strategies and make the jobs of digital marketers easier. By utilizing ML tools and capabilities, you can streamline your digital strategy and align yourself with an AI and ML-dependent future.

Machine learning in digital marketing

ML is being implemented in digital marketing departments around the globe. Its implications involve utilizing data, content, and online channels to increase productivity and help digital marketers understand their target audience better. But how exactly are ML tools being used in digital marketing strategies today? The experts at Smart Insights have compiled a few examples of how ML can make its way into your digital strategy.

Content marketing: In recent years, digital marketers, bloggers, and businesses of all sizes have been busy creating content of all types to engage their target audience. Whether it’s in the form of informative blog posts, customer testimonial videos, or recorded webinars, content is everywhere online.

LinkedIn defines the top three things that make content truly effective as:

  • Audience relevance – 58%
  • Engaging and compelling storytelling – 57%
  • The ability to trigger an action or response – 54%

ML tools can be a beneficial part of helping digital marketers uncover and understand this data better. By tracking consumer trends and producing actionable insights, ML tools allow you to spend time streamlining your tasks to reach more leads with your content.

Pay per click campaigns: Gone are the days of marketers trying to analyze data sets to measure the effectiveness of pay per click (PPC) campaigns. ML tools can help you level-up your PPC campaigns by providing information that demonstrates:

  • The metrics you need to help drive your business forward.
  • How you can make better, strategic decisions based on the top performance drivers.
  • Overcome the struggles that keep you from meeting PPC goals.

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Search engine optimization (SEO): SEO is still a major player in a well-rounded digital strategy, with many digital marketers choosing to specialize in this highly sought after skill. However, as SEO algorithms change across major search platforms, the insights from searchable content may become more relevant than specific keywords in the search process, thanks to AI and ML tools.

To ensure that your web pages and online resources maintain their high-ranking place on search engine result pages, start considering the quality of your content rather than simply the keywords included. By doing so, you’ll be ahead of the game when it comes to future-forward content creation and SEO.

Content management: To drive brand awareness and build engagement, digital marketers must create meaningful relationships with leads, prospects, and customers alike. As you attempt to optimize your dialogue and develop engagement across multiple online platforms, ML tools will be immensely helpful in analyzing what type of content, keywords, and phrases are most relevant to your desired audience.

The rise of the machine learning chatbot

Chances are, you’ve already read about the rise of the machine learning chatbot. Or perhaps, you’ve already chatted with a robot on a brand’s website. However, how are chatbots and ML related, and how are they impacting digital marketing?

In short, a chatbot is a virtual robot that can hold a conversation with humans either through text, voice commands, or both. Many large brands have already implemented chatbots into their interface, including Apple’s Siri feature. Siri and similar chatbots can perform searches, answer queries, and even tell you when the next bus is.

For example, Facebook is already implementing methods as to how they can develop chatbots for brands that advertise on their platform, with messenger being the go-to channel for consumer-to-virtual ambassador interaction. From a digital marketing perspective, chatbots can help you engage with targeted audiences on a personal level. Because of the natural language processing (NLP) abilities of chatbots, they can carry out a human conversation while being hard to detect. ML and ongoing conversation allows chatbots to collect data surrounding particular users, including personal information such as where they live and their product preferences.

Conclusion

To begin a career in digital marketing, a person must be driven, passionate, and willing to adapt to changing professional landscapes. The job of a digital marketer has transformed from a business storyteller to a technological manager. To streamline processes and increase productivity, digital marketers – both present and future – must begin to use ML tools to automate processes and utilize data more effectively.

Digital marketing is an industry ripe with opportunities and challenges, and it isn’t showing signs of slowing down anytime soon. If the goal of digital marketers is to increase engagement and brand awareness with leads, it’s vital that they understand their customers. ML won’t replace existing digital marketing jobs. Rather, it will help broaden the capabilities of the modern digital marketer, providing a base to do and be better at what you do.

As we move into the digital future, machines and people will begin to work together to take marketing initiatives to the next level. No longer will marketing products or services be a tireless campaign of creating, curating, and sharing high-value information. Instead, digital marketers will be able to spread brand awareness in a way that’s more efficient and personal than ever.

Embrace the power of artificial intelligence and machine learning to level-up the capabilities of you and your marketing team, and start making a future-forward impact that inspires engagement and meaningful relationship development.


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