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Buki Froelke: Creating more accurate forecasts for customer demand and seasonality can help marketers like you stay agile and meet customers where they are with relevant messaging.
But accurately predicting customer demand or digital media performance can be daunting without the right data or resources.
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With Google Cloud’s data and AI capabilities, you can use this technology to accurately forecast and plan for customer demand, helping you deliver digital and creative experiences at scale.
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Hi everyone, Buki here. I’m the senior product lead for data and AI cloud for marketing at Google. You’ve found your way to How to Think About. And today, we’re talking about using Google Cloud to plan for and forecast customer demand.
I’m excited to share some key methods and solutions that can help you accomplish that.
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First comes forecasting demand.
Using your historical campaign data from Google Ads in BigQuery, you can use machine learning to build a KPI forecast that will help you plan for spikes and ensure you have the budget to meet your customers where they are.
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These predictive capabilities can be applied to predicting customer web or foot traffic. You can leverage data like holiday variables, store visits, or even weather trends.
And with that data, you can build a powerful predictive model to optimise your budget and better anticipate traffic and demand.
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Ok, let’s jump to the next method: Creative Analysis.
As a marketer, I’m sure you know the quality of your creative can either make or break your campaign performance. In fact, when creative best practices are used, there’s an average 30% lift in the likelihood of short-term sales and a 17% lift in the long-term brand contribution.
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So we know creative is important. But how do you know which elements within help to move the needle?
Well, machine learning technology within BigQuery allows for scaled creative analysis. It can generate insights from successful creative to understand their impact on ads performance.
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Assessing elements as specific as objects, emoticons, text, or colors can help you determine what is driving the most impact.
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Speaking of AI, I’m most excited about generative AI and how it will change how we create content and marketing assets.
Advancements in generative AI can make it easier and faster than ever before to make improvements to the customer experience.
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While it’s still in its early stages, we can start to imagine how easy things will become.
You’ll start with a single hero asset. And that’s it. AI can take it from there. It can build relevant social posts, landing pages, emails, and more all from that single hero asset.
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OK, let’s walk through a high-level version of everything we chatted about today.
You have incredible tools like demand forecasting and creative analysis that can help you drive better and more personalised customer experiences at scale.
And soon you can add generative AI to that list too.
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That’s all for this episode of How to Think About, and I’m so glad you could join me in rethinking the customer experience.
To learn more about how Google Cloud can empower your marketing strategies, be sure to subscribe to the Think with Google YouTube channel. See you next time.
Sources:
McKinsey & Company, Personalising the Customer Experience: Driving Differentiation in Retail, April 28, 2020.
Google/Kantar Link AI, Global, The Short and the Long of ABCDs Effectiveness, 2021.
