Using Artificial Intelligence for Marketing Part 4

Welcome to the final post of this four part series regarding using artificial intelligence for marketing. A small review to start.

There are 3 main types of Artificial Intelligence:

  1. Machine learning techniques: using algorithms to learn from previous data or successful campaigns and adapt to current trends in the marketplace.
  2. Applied Propensity Models: used to predict events based on the probability to convert into sales.
  3. AI Applications: used to perform tasks that can also be done by humans. ex. answering human questions, writing content.

Each one has different advantages and disadvantages. Some are better for attracting customers; others conversation or re-engaging drifting customers. Today we are focusing on the three artificial applications.

15 apps for content markeitng

There are 3 AI Applications:

  1. AI Generated Content
  2. Voice Search
  3. Chatbots

AI Generated Content

AI writers are useful for reporting on regular, data-focused events. Examples include quarterly earnings reports, sports matches, and market data. AI generated content is used in niche markets such as the financial markets for the best results. It is useful for developing a content marketing strategy.

The key to using AI generated content is to pick relevant data.  For certain functions AI content writing programs are able to pick elements from a dataset and structure a ‘human sounding’ article. An AI writing program called ‘WordSmith’ produced 1.5 billion pieces of content in 2016, and is expected to grow further in popularity in the coming years.

Not to be used for political opinion, industry-specific blogs or specific  advice.


AI generated contents falls under the Reach section of the RACE framework.

Reach: Attracts visitors with a wide range of inbound techniques.

Voice Search

Voice Search utilizes technology developed by major players such as Amazon, Google and Apple. It is predicted to change the future of SEO strategies and brands and marketers need to keep up.

The key to succeeding with Voice search is by leveraging big gains in organic traffic with high purchase intent thanks to increased voice search traffic due to AI driven virtual personal assistants.


Voice Search falls under the Reach section of the RACE framework.

Reach: Attracts visitors with a wide range of inbound techniques.


Chatbots mimic human intelligence by being able to interpret consumer’s queries and complete orders for them. You might think chatbots are extremely difficult to develop and only huge brands with massive budgets will be able to develop them. But actually, using open chatbot development platforms, it’s relatively easy to create your own chatbot without a big team of developers.

Facebook is interested in facilitating the development of chatbots for brands. It wants to make its Messenger app the go-to place for people to have conversations with brand’s virtual ambassadors. The good news for brands is that this means they can use some of Facebook’s powerful bot development tools. Using the lessons they’ve learned from the beta tests of ‘M’ (Facebook Messenger’s own chatbot), Facebook has created the bot engine which allows you to train bots with sample conversations and have your bots continually learn from interacting with customers. If you are interested in building a chatbot for your brand within the Messenger platform Facebook has created useful instructions for how to do so, which you can find on their Facebook for developers site.


Chatsbots fall under the convert section of the RACE framework.

Convert: involves getting your audience to take that vital next step which turns them into paying customers whether the payment is taken through online E-commerce transactions or offline channels.

For more information on Chatbots:

6 Ways Chatbots Can Benefit Your Marketing Strategy

Thank you for reading!

Feel free to comment with your thoughts and ideas! I always welcome new ideas.

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Allen, R. (2017, June & July). 15 Applications of Artificial Intelligence in Marketing. Retrieved July & aug., 2017, from