digital marketing myths

3 digital marketing myths that we should dispel in 2020

Some common digital marketing myths are repeated so frequently and by so many people, that in the end we tend to assume that they are true. As in popular culture, it has always been and always will be.

There is a way, however, sometimes to stop and reflect more closely on these myths and what emerges often allows you to move the bar of your marketing strategies to a next level.

So here are three digital marketing myths that we should debunk this year …

Myth 1: The video is slow and expensive to produce

Marketing experts understand that they should adapt and optimize creative assets to the specific characteristics of the platform where the videos will be used.

The myth of the industry is that making videos in this way is expensive and time consuming. You have to hire a director and a great team who have to shoot some glamorous place, bringing their expensive equipment with them. Before going to post-production, it will take many months and a lot of money. The final work, however beautiful it may be, must be broadcast everywhere – in a format suitable for all channels – without time or resources for any adaptations or customization.

Actually, producing a video doesn’t have to be that way. Instead, it is possible to produce digital videos faster, cheaper and more effectively.

For example, for the launch of Google Home Hub, we took a basic video and launched it through a tool called Directors Mix, which allows you to create personalized videos on a large scale. In the end, we made 80 versions of the ad, each tailored to a different context.

Myth 2: The more data you have, the better!

In digital marketing, we collect all types of data to understand if our creative and multimedia strategies will work. We can see how long someone has spent watching a video, how far someone has scrolled down the page, or how many visitors leave our website. And the list goes on and on.

But really just because you can measure something, does that mean you should do it? We realized that, even when it comes to data, “less is more”.

When we verified the analyzes shared with our leadership by the Google Marketing teams, we found that together we were reporting 70 different metrics globally. How did we expect our CMOs and VPs to make consistent decisions, comparing one campaign or strategy with another, when our teams didn’t speak the same language?

We reduced all that data to just six relevant metrics. Why this number? Because we run two types of campaigns: brand and performance. In all these campaigns, we worry about three things: if we catch people’s attention, how they behave in response and what the result is.

So now, rather than drowning in metrics, we only have one for each of the results we are interested in measuring.

Myth 3: Humans are replaced by machines

“As advertisers in the age of machine learning and AI, it’s easy to think of ourselves in an epic confrontation with machines,” Ben Jones wrote in a Think with Google article from last year.

This digital marketing myths create fear that machines will replace us is normal and certainly not limited to the marketing sector. But the fear is unfounded. Instead, as we discovered through our experiments last year, it is a matter of understanding what tasks the machines perform better than we do and letting them operate, thus leaving human beings free to do what they really know how to do in a unique way: intuit, inspire and be creative.

For anyone who is not a mathematician, it would literally take a lifetime to understand what it means. But even the most analytical people would take some time to solve this problem manually, which is why CLV is usually calculated only every six months.

To carry out this operation much faster we turned to machine learning and used a tool called TensorFlow. We went from having access to a CLV every six months, to having 2,000 predicted customer value (pLV) per day. This allowed us to regularly optimize and update our ad serving strategy.

Machines can also save us time in the area of advertising creativity. For example, we were able to use smart creative technology to optimize the display and search of ads in real time based on how people respond to them.

The format has significantly outperformed the legacy static displays and search ads that we have been using for more than a decade.

Computers are well designed for these highly manual decisions. So let them do this job, leaving us the opportunity to focus on the things that machines can’t do.

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