In terms of digital marketing, the cost of a click marketers pay should get meaningful engagement.
However, most of the time, this is not true. This is because most people bounce out of a page in just a few seconds. Only a small percentage of those visitors can really translate to leads.
This is called digital marketing waste, and it is something inevitable in the growing web.
The problem for marketers isn't limited to that, since they are less likely to know which part of their advertising budget is wasted.
With native advertising spending budget increasing year after year, if tens of billions of dollars are spent, many of those billions are going to waste. this digital marketing waste is becoming an increasing concern.
The case is even worse for those marketers who pay on advertisements based on an impression basis (CPM).
One solution for this, is using AI.
As an intelligence demonstrated by machines, AI is the ability of a system to perform tasks that typically require human intelligence, such as reasoning, generalizing, and making decisions. Machine learning, which spawns out of AI, uses algorithms to parse and analyze data it is fed on, finds patterns, and utilizes them to inform decisions and take action.
Many big marketing and tech companies are using some form of AI to aid their campaign, and this is by embedding the technology to improve targeting and real-time bidding.
With machine learning, marketing platforms gather and analyze data from multiple sources, such as search behavior. And from the resulting analysis, the platforms can discern what type of experience and result the consumer is expecting.
This way, they can better identify the needs of web visitors and online shoppers, and deliver the best marketing message in that micro-moment.
Read: How Artificial Intelligence Is Changing Sales And Marketing For The Greater Good
While AI may not eliminate digital marketing waste, it can decrease its number, making marketing budget more meaningful.
And since AI learns by doing, with access to a very large quantities of data, it should learn faster to become a lot better. And with the right amount of data, AI can also improve things like in programmatic paid media.
This model doesn’t just reduce waste, it also reduces fraud and brand safety concerns, by reducing the importance of impressions and clicks in favor of engagement.
Looking back to the old days, connecting marketers with consumers was like a guessing game. Advertisers needed to select the media channels they thought might give the best chance of attracting buyers, by relying on past experience, instinct, relationship and competition.
But with AI, automation is going a step further.
AI changed the game by giving marketers a way to skip the haystack process, and directly get the needles in ways more quickly and more efficiently. This is possible by AI in targeting active shoppers with highly-relevant marketing messages.
Machine learning can also help marketers to "win back" potential customers who have not yet converted. AI-assisted bidding for example, enables marketers to prioritize self-declared likely buyers with more aggressive retargeting efforts, across the web and across devices, with the messages predicted to be most compelling.
And because things can be automated, marketers can simply specify their inventory turn strategy, and allow the technology to take care of the execution. Here, they can focus on managing their inventory and optimizing the sales process.
What this means, marketers can go straight to the advantage by putting aside most of the old days' uncertainties, minimizing wasted money on ads.