5 Artificial Intelligence Trends in Marketing 2020


While Artificial Intelligence is starting to become commonplace across business functions (Chaffey, 2019), below are 5 of the AI trends which are believed to impact in the marketing domain in the coming decade.

Conversational search: AI technologies will boost Machine Learning (ML) capabilities associated with Voice search (Balkhi, 2018) and Natural Language Processing (NLP) which will eventually lead to the new era of conversational marketing. Brands like Air Canada are already using NLP technologies like Persado to boost customer engagement (Chaffey, 2020)

Content Marketing: With advancements in NLP, there is great interest in adopting Natural Language Generation (NLG) as well for the automation of content marketing. NLG solutions like Quill, Wordsmith are already being used by some companies, while others like Amazon are developing their own NLG systems like Polly and Washington Post’s Heliograf which are customized to their specific organizational needs. (Marr, 2019). These not only just save time in generating the content, but they can personalize the communication en masse according to the customer preferences by linking them with their Customer Analytics.

Customer Service: While Chatbots have already being used by many businesses, their functionality is still limited to sending template messages and responding only to specific commands. (Cannella, 2018). But with advancements in NLP and NLG, AI-powered Chatbots will be able to respond to customer queries, offer them support and resolve their issues in a much better fashion. (Mitchell (CMO), 2018)

Customer Data Analytics: Customer Data Platforms are improving Customer Data Analytics by integrating AI-powered Predictive Analytics which can generate valuable insights like Purchase predictions, Campaign Engagement Predictions, and Demand analysis (Exponea, 2019).

Marketing Automation:  All the above AI trends once they become mainstream, will eventually bring in more levels of automation in all areas of Marketing. (Stephen, 2017). Eventually, the AI systems though deep learning will be able to predict customer response, optimize content, trigger personalized ads, push conversions and respond to customer queries. (Sterne, 2017).

While it may take some years for AI systems to become perfect, there is no doubt they will transform the landscape of marketing as we know it.

References:

  • Balkhi, S. (2018) 4 Artificial Intelligence Trends to Watch for in 2019, Entrepreneur. Available at: https://www.entrepreneur.com/article/323761 (Accessed: 20 February 2020).
  • Cannella, J. (2018) ‘Artificial Intelligence In Marketing’, p. 132.
  • Chaffey, D. (2019) Latest Gartner Hype Cycles, Smart Insights. Available at: https://www.smartinsights.com/managing-digital-marketing/marketing-innovation/technology-for-innovation-in-marketing/ (Accessed: 20 February 2020).
  • Chaffey, D. (2020) 6 essential marketing trends for 2020, Smart Insights. Available at: https://www.smartinsights.com/managing-digital-marketing/marketing-innovation/6-essential-marketing-trends-for-2020/ (Accessed: 20 February 2020).
  • Exponea (2019) CDP  Predictive Analytics.pdf. Available at: https://elearning.dbs.ie/pluginfile.php/1129284/mod_resource/content/1/CDP%20%20Predictive%20Analytics.pdf (Accessed: 18 February 2020).
  • Marr, B. (2019) Artificial Intelligence Can Now Write Amazing Content -- What Does That Mean For Humans?, Forbes. Available at: https://www.forbes.com/sites/bernardmarr/2019/03/29/artificial-intelligence-can-now-write-amazing-content-what-does-that-mean-for-humans/ (Accessed: 20 February 2020).
  • Mitchell (CMO), V. (2018) Predictions: 9 AI trends in marketing for 2019. Available at: https://www.cmo.com.au/article/650692/predictions-9-ai-trends-marketing-2019/ (Accessed: 20 February 2020).
  • Stephen, A. (2017) AI Is Changing Marketing As We Know It, And That’s A Good Thing, Forbes. Available at: https://www.forbes.com/sites/andrewstephen/2017/10/30/ai-is-changing-marketing-as-we-know-it-and-thats-a-good-thing/ (Accessed: 20 February 2020).
  • Sterne, J. (2017) Artificial Intelligence for Marketing: Practical Applications. John Wiley & Sons.

Comments

  1. Aishwarya Venkatesh20 February 2020 at 21:08

    Well explained article. Keep it up!

    ReplyDelete
  2. Leonard20 February 2020 at 22:30

    Well explaining about ai in marketing! It's booming.

    ReplyDelete
  3. Serial.Blogger20 February 2020 at 23:00

    True and also, Business are putting a lot of money in AI Marketing.
    Good Blog.

    ReplyDelete
    Replies
    1. MJ21 February 2020 at 10:13

      And they are right to do so! Thank you!

      Delete
  4. Aniket Malvankar20 February 2020 at 23:47

    Current trends of AI in Marketing are covered very well.
    Great work MJ!

    ReplyDelete
  5. Rishi Suvarna21 February 2020 at 15:18

    Very well put MJ! Thanks for the insights.

    ReplyDelete
  6. Sam DBS21 February 2020 at 15:57

    Very well explained MJ 👍

    ReplyDelete
  7. Elina22 February 2020 at 14:17

    Great job! My latest post also talks about AI. I will appreciate your comment!

    ReplyDelete
  8. Manikandan Dhanapal23 February 2020 at 17:01

    Intellectual !!!
    Thanks MJ.

    ReplyDelete
  9. Martina23 February 2020 at 20:01

    The post is such an easy and thorough read. I appreciate that you have broken down the impacts in a clear and concise manner. Great share!

    ReplyDelete
  10. Svetlana23 February 2020 at 20:03

    Great post MJ! Thank you very much for sharing. Very interesting and informative!

    ReplyDelete
  11. (ADI)GIT_blog23 February 2020 at 20:44

    Always is pleasure to read your blog posts. Keep writing

    ReplyDelete
  12. Colin Almeida24 February 2020 at 18:49

    AI is the future for marketers to reach their audience and your blog explains how we can use it. Thank You.

    ReplyDelete
  13. Wayne D25 February 2020 at 20:12

    Great work MJ. Enjoyed this

    ReplyDelete

Post a Comment

Popular posts from this blog

Dimensions of Big Data - The 3V's

Image
Big data is not just large very large sets of data. While Big Data has many characteristics (Kitchin and McArdle, 2016), there must be 3 main dimensions for a dataset to get qualified as Big Data often referred as the 3V’s, namely Volume, Velocity and Variety. To simply explain these dimensions, let’s take the example of the online retailer Amazon.com. Volume : Volume refers to the size of data that is being collected, processed, analysed and stored. For example, Amazon.com’s average monthly traffic is more than 2 billion which includes its 150 million App users who browse through the estimated 120 million products sold by around 2.5 million sellers (Oberlo.com, 2019) . This huge traffic base generates a great volume of data points, in terms of orders, transactions, inventory changes, customer communications etc and need to be managed properly. Velocity :  Velocity refers to the speed with which data is collected, processed, analysed and stored. Amazon.com sells around 40
Read more

Big Data - What's the Big Deal?

Image
Big data is one of the popular buzzwords in business today across most industries if not all. Even though the term was originated in the 1990s (Lohr, 2013) , it gained more traction in the early 2000s among the tech community with the advent of digital storage systems. As mobile broadband and social media networks took off in the early 2010s, Big data was getting recognised as a marketing tool and in 2012, it was a featured topic in the World Economic Forum, thus entering the mainstream. For a casual observer, Big Data might seem like just large volumes of data and rightfully so. But the most crucial aspect of Big Data is that it is fundamentally networked and the relationality between varied sets of data. (Boyd and Crawford, 2017) . While there are many characteristics attributed to Big Data, they are often defined using the 3V’s Volume – This denotes not only the breadth of the data but also the depth of data collected which essentially covers every interaction of user acr
Read more