Machine learning, natural language processing, big data, chatbots.
There are a lot of buzzwords thrown around when it comes to artificial intelligence, but not a lot of knowledge about what they are.
What is Artificial Intelligence?
One way of thinking about artificial intelligence is to define it simply as algorithms we don’t quite understand yet.
For example, 20 years ago finding point-to-point directions in something such as Google Maps would have been considered artificial intelligence.
These days, pathfinding algorithms are a part of core curriculum for most computer science undergraduates.
As algorithms advance, it’s no longer seen that way.
Some examples of artificial intelligence today include:
- Google Translate, an application where you can plug in text in one language and get the text in another language which uses Natural Language Processing
- Self-driving cars, which use Machine Vision
- The software behind deciding whether someone should get a credit card
- Siri, Echo, Google Assistant, and Cortana use automated speech recognition, natural language understanding, informational retrieval, and natural language generation all together.
What’s the Use Case for Artificial Intelligence in Marketing?
One example of AI in marketing is the technology Wordsmith.
Wordsmith uses natural language processing to create news articles.
Many low-level sports and financial articles are written by this or similar software today.
WordSmith isn’t true AI however, because it’s not intelligent.
Rather it uses pre-specified templates; regardless it’s a pretty nifty idea.
In marketing, AI is used in the following ways:
- Automated content creation: Artificial intelligence examines the search history of customers and prospects to automatically generate a newsletter email based on that history.
- Lead scoring: Before artificial intelligence, marketers would assign points for lead scoring based on intuition. Today , machines can learn what lead scoring attributions should look like to most accurately reflect a qualified lead by its score.
- Chatbots: AI-driven chatbots are increasingly helping to give customers and prospects customized advice.
Current Content Marketing Challenges
Everyone Wants to Be Different and Everyone Wants to Be Better
Marketing is a field where everyone is always trying to “one up” one another.
If a competitor is doing a marketing strategy, other marketers want to do something different and better.
As a result, standardization is a bad thing.
When it comes to artificial intelligence, standardization helps solve a problem over and over.
For instance, with Uber, everyone wants to get from point A to point B.
Uber is looking to make that same model better and better.
The challenge with marketing is rather than standardize, everyone wants to solve a problem in a different way, or solve a different problem.
As artificial intelligence is more widely adopted, this hurdle will become obsolete.
Baseline models will provide value on day one without customization.
Over time, artificial intelligence software will learn and become more specific to your needs.
Pandora is already doing this with music.
If you create a jazz station, Pandora already knows what jazz is and will deliver roughly what you want.
If there’s a certain type of jazz you like, over time, Pandora customizes your jazz station based on which songs you give the thumbs up or down to.
Data Management
Another challenge in marketing is to be better at collecting and storing data to make it more useable.
Applications that can leverage data better are still being created.
Companies today already have plenty of internal data.
Smart marketers will focus on capturing this data, organizing it, and combining it with external data so that as advanced AI technology comes to market, they can leverage it effectively.
Even More Ways to Use Artificial Intelligence in Marketing
Artificial intelligence is already automating content creation from personalized newsletter emails to writing basic sports and financial stories.
It’s also automating lead scoring, powering chatbots, and tracking content performance from the top of the funnel through to the amount of revenue generated by a single blog post.
Further automation and personalization advantages from artificial intelligence in marketing advances are imminent in 2017.
