While being transformative as a concept, we’re still not fully aware of how revolutionary will artificial intelligence (AI), and machine learning (ML) truly become. We are just beginning to find out different applications of these technologies in the marketing and advertising industry. Combining human efforts with algorithms is the way forward.
“What can a machine do without a human?”
At Adssets we always strive to automate and simplify creative work. The goal is to use as much relevant content (decided by a human) as input, and match that we conditional data to increase relevance and engagement.
Algorithms all the way
The machine lets us write algorithms that select different sources of data based on predefined scenarios. In this case, the defined scenarios are basically twofold, (1) machine controlled outcomes and (2) predicted models. We use these both to apply control points that match our client’s predictions.
“Algorithms help our clients optimize and make informed decisions based on real-time data and ultimately improve their campaign results.”
Let me explain with an example both of these.
Machine controlled the outcome.
At Adssets we use Ad Decisioners to manage and control the outcomes of our customer’s campaigns. Our vision for the Ad Decisioners is to help clients get real-time insights about their campaign performance and user behaviour. For example, adding 10 different ads into A/B Simple could result in four different optimizations; (I) score based on viewability, (II) score based on Engagement/Interactions, (III) score based on clicks and (IV) combined scores from any of the above.
The algorithm is easy to understand, you rank the ad and then you can let the machine combine different scoring from different parameters to get a combined score.
Naturally, you automate so that only the top ranking ad will get traffic…but for how long? Another job for the AI or not?
In this scenario, you have insights into the desired outcome with a set of control points. You know that if the following parameters are met your registrations will be maximized. Parameters would look like this (i) You reach above 0.5% in clicks, (ii) View time is above 2secs and (iii) the add is shown with an audience-specific message.
This is easy to automate and optimize for, but you need more data then just ten ads. Preferably you need 100’s if not 1000’s, hence ad automation is needed.
“What if we want to feed learning into the Predictive Model? Ex. when the skies are blue which content works best? Is that AI?”
To keep it simple we need to know what we want to achieve.
To get the right outcome, therefore, is a combination of human and machine better and cheaper than only AI. With only AI you have unknown elements to be able to calculate outcomes, what happens when it is working, you’re unsure.
It will be extremely hard to visualize WHY the AI made these decisions and HOW it’s better than other scenarios. You‘re basically handing over the trust to a Machine with an undefined algorithm if you automate it.
Then again, AI may be the right way to visualize scenarios that you then stick into your Machine Learning tools…like we do at Adssets!