Introduction
Welcome to the 12 Days of Data 2021 Edition, our look back at the data that made marketing in 2021. We’re looking at the year that was (and oh, what a year it was… again…) from an analytics perspective to see what insights we can take into the next year. Sit up, get your coffee ready, and let’s celebrate some data and look forward to the year ahead.
2022 Marketing Campaign Forecast (USA)
One of our favorite forecasts for marketers, B2B and B2C, is our annual marketing campaign forecast. With this forecast, we look at what’s likely to happen over the coming year so that you can plan your marketing appropriately. What weeks will our campaigns do best or worst?
How do we know what’s a good time for marketing and what isn’t? By people’s behaviors. Our audience, our customers may not tell us when the best time to market to them is, but they do tell search engines, and those searches help us understand when they’re likely to be doing something.
For example, what is someone about to do when they type in a search like “Outlook out of office” or “GMail out of office”? Unsurprisingly, they are looking for how to manage the out of office feature in these software products so that they can go on vacation, or at least be away from work, away from the office.
If we know when people are searching for these terms, then by default we know when they won’t be in the office. And if we know when they won’t be in the office, then we know when not to launch major marketing campaigns that will simply fall on deaf ears or flooded inboxes.
So, if we use some predictive analytics to forecast ahead the next 12 months, when will people be searching for these terms the most? Those are the times not to launch major campaigns. When will people be searching for these terms the least? Those are the times when major marketing campaigns will at least be made available to people while they’re in the office:
When volume is highest, people are leaving the office shortly. We shouldn’t be doing any kind of major marketing campaigns then if we can avoid it. This data also applies to efforts such as sales; note how difficult quarter-end will be at the end of Q2. Note that this data is based on USA search volume; if you do business in another nation and especially in the Southern Hemisphere, your regional calendar is likely to look different.
The power of predictive analytics helps us to understand what we should be doing and when. We know the broad generalities of when people are in or out of the office, but predictive analytics helps us nail down the specifics.
Methodology
Trust Insights used its proprietary software combined with data from AHREFS and Google Trends to produce this forecast. The timeframe of the training data for the machine learning model is January 1, 2016 to December 16, 2021. The date of prediction is December 20, 2021. Trust Insights is the sole sponsor of the study and neither gave nor received compensation for data used, beyond applicable service fees to software vendors, and declares no competing interests.
[12days2021]
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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.
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