When did AI for marketers become so common?
It’s already here. Artificial intelligence – the broad term describing the ways computers are getting better at solving complex challenges – is being used to tame data across the marketing industry.
You might have heard the terms “artificial intelligence” and “AI” associated with media planning software and ad buying platforms. You might even be using AI to run a campaign, albeit without realising.
But what are we actually talking about when we talk about AI? We aim to answer that question and more as we unpack artificial intelligence:
- The definition of AI
- What is the difference between AI and machine learning?
- 3 ways marketers already use AI
- How marketers can use AI to improve campaign performance
Artificial intelligence (AI) is machines demonstrating intelligence. Any time a machine or software follows these steps, you’re dealing with AI:
- Receives data, usually in large amounts
- Processes those data into an output
- Performs an action that maximises its chances of achieving a goal
We often use the term AI to describe anything a computer does that mimics a cognitive function. Computers playing chess? That’s AI. Asking Alexa to play a song on the office stereo? AI. Programmatic advertising placing banner ads to optimise CTR? You guessed it, AI.
But we think it’s important to understand the different types of AI used in marketing, and how the technology is changing the way our industry runs campaigns.
AI is becoming commonplace across the world as the technology continues to evolve. High-profile examples like self-driving cars, smartphone assistants, chatbots and online advertising have been around for so long that we hardly consider them AI anymore. This is called the AI effect, and it’s worth reading about if you’re interested.
Closer to home in media planning, AI is integral to delivering complex campaigns. Here are some of the ways you might already be using AI:
Machine learning might be the most prevalent subset of AI. It’s a type of intelligence focusing on improving computer systems and algorithms when exposed to new data. The algorithms evolve, making better decisions based on what worked or didn’t work in the past.
When humans do this, it’s called statistical analysis. The main difference is machine learning algorithms can analyse terabytes of data in the time it takes a human to find the right spreadsheet. And they can continually improve in real-time as new data feeds in.
Example: Programmatic ad campaign
Programmatic advertising uses an automated bidding system to fill ad space online. In 2019, 83.9% of all digital display transactions in the US were automated. That includes placements through publishers’ APIs, real-time bidding platforms, and ads on social networks like Facebook and LinkedIn.
Machine learning optimises ad placement based on the advertiser’s goals. It then automates the bidding process based on the competitive landscape and continually adjusts to fill available ad space. All of this happens in milliseconds.
Between April and June last year, 4.1 million smart speakers shipped to Europe, bringing the total market up nearly 18% across the region to 22 million units. Every time a user asks Alexa, Google, Siri or Cortana a question, the digital brain whirs and sends back an answer.
Natural language processing (NLP) is another type of AI used in marketing. And you still have time to be an early adopter in this exciting space.
Example: Searching for solutions online
Voice assistants are changing the way people search online.
- Search terms are getting longer
- Words like “what”, “how” and “where” are increasingly used
- Local search results are more prominent
For marketers, this means optimising PPC campaigns to align with search behaviour. In the past, we might have optimised for “media+planning+tool+marketing”. But considering the trend towards conversational search terms, we might see better results by targeting “best media planning tool in Europe”.
Undoubtedly, every marketer wants to position the right content in front of the right person at the right time. AI is making it much easier by using consumer data to categorise and predict behaviour.
Machine learning comes in to play again to analyse behaviour, but in a different way to programmatic advertising. In this case, machine learning simulates the human decision-making process on a grand scale. Algorithms are given vast amounts of behavioural data points and asked to make projections about behaviour, often linked to spending and brand loyalty.
Example: Audience segmentation
Let’s take a step back now and look at one of the main focus areas for marketers in 2020, building an engaged audience. Machine learning goes beyond traditional segmentation (by location, age, income) to identify audiences based on behaviour.
- What they are talking about online
- Viewed pages/products
- Search behaviour
- Predicted purchase intent
- Personal preferences
These algorithms rely on human interpretation to continually improve. They are powerful, wide-ranging, and have access to unprecedented amounts of data. But they can’t replace a human sense-checking the customer’s apparent needs or predict human behaviour.
AI does what humans can’t, by:
- Synthesising data in large quantities
- Automatically performing tasks at lightspeed
- Using real-time data feeds to improve decision-making
- Scouring user behaviour to predict trends
But, conversely, humans do something AI never could. We use flexible logic and emotion to influence decision-making. Computer processing can’t replace human insight into audience behaviour or in-depth knowledge of a client’s business. It’s when you put those two together that the magic happens.
High-performing brands and media agencies are always looking for ways to achieve better results, optimise investments, and work faster. AI is enabling these performance improvements already and will continue to do so as the technology improves.
And as leaders in the media planning software space, our developers can’t wait to see where AI for marketers leads. For now, we’re focused on integrating the outcomes of AI into the best marketing campaign management tool on the market, giving you the means to deliver better results.