How to think about Machine Learning
How to think about Machine LearningMärz 2022
Effektive Ads dank First-Party-Daten und Automatisierung
Menschen, die bereit sind, ihre Daten weiterzugeben, zeigen sich auch offener gegenüber Werbung von Marken. Nur, wie finden Werbetreibende diese Userinnen und User? Hier kommen First-Party-Daten ins Spiel, die in Verbindung mit Machine Learning dabei helfen, Kundinnen und Kunden mit relevanten Botschaften zu versorgen, und ihnen so einen echten Mehrwert bieten. Im Video erklärt Jaylen Baca, Global Product Lead für Datenschutz bei Google, wie das Zusammenspiel von First-Party-Daten und Machine Learning optimal funktioniert und wie Sie so die Effektivität Ihrer Marketingmaßnahmen steigern können.
Nacia Walsh: Hi, and welcome to another episode of our How to Think About series. I’m your host, Nacia. In this video, we’re going to be talking about first-party data and machine learning. You know, one of the great things about first-party data is that it makes identifying your best customers clearer, which means relationship building is easier.
Why? Because studies have shown that people who choose to share their information are more receptive to your ads. You’ve got their buy-in upfront. But receptivity is only one piece of the relevance puzzle. We spoke to our resident privacy expert, Jaylen Baca, a global product lead at Google, to learn more about using first-party data to provide relevant ads to your audience. Over to you, Jaylen.
Jaylen Baca: Thanks, Nacia. Hello, my name’s Jaylen Baca and I’m here to share two key strategies for thinking about driving better performance with your first-party data. So let’s jump into it.
The first strategy is reaching customers where they are in their journeys. And the second is using automation to attract new customers. So what do we mean by reaching customers where they are? Basically, instead of running a campaign and hoping your customers will see it, now you can build an ad and deliver it to people based on where they are in their shopping journey.
By serving ads in the right place at the right time, you’ll help improve engagement because people will be receiving an ad that actually feels relevant and has clear benefits.
Various platforms have tools that can help you accomplish this. For instance, on Google, you can use tools like Customer Match to help reach your prime audience wherever they are on Google, from Search, Shopping, Gmail, YouTube, or other display properties.
In addition to first-party data, automation can help marketers find new qualified customers and improve how your ads are matched with the most relevant users at the most relevant time in their journeys. Google Audiences, for example, can factor in a range of signals in order to reach interested users and optimize which ads to show them.
Signals could include demographics, interests, and their context in the journey. If you think about it, it’s really an exciting time in digital marketing. When we embrace first-party data and machine learning, marketers can better engage with users and deliver ads that better align with people’s needs. Thanks so much for listening. Back to you, Nacia.
Nacia: Thanks for that insight, Jaylen. Let’s recap, shall we? First, rely on your first-party data to best engage with your audiences. And second, lean into automation to help you deliver relevant ads based on your users’ interests, preferences, or context of their engagement journey. Well, that’s it for this How to Think About video. Stay tuned for more expert insight by subscribing to our channel. Glad you can join us and we’ll see you next time.
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