Few software packages for marketing are more widely adopted than Google Analytics™. It’s the gold standard for businesses large and small that want to measure what’s happening on their owned media properties like websites, eCommerce storefronts, and content hubs.
Yet, as with so many other marketing measurement tools, Google Analytics tells us what happened. It’s one of the best rear-view mirrors for marketing analytics, but it’s still a rear-view mirror – and driving with the rear-view mirror is dangerous no matter how good the mirror.
What if we didn’t have to drive with the rear-view mirror? What if we could use Google Analytics as a basis for looking out the front windshield?
What Would Predictive Google Analytics Look Like?
Consider what predictive Google Analytics would do for our businesses. Let’s take my blog as an example. Here’s my traffic for the last 18 months or so.
This is useful rear-view mirror information. I see what’s happened over time, the general seasonality and cyclicality of my content. It sure would have been nice to know about the dips and low points before they happened, wouldn’t it? I could have done so many things differently had I known what was to occur.
Thanks to the Google Analytics API and predictive analytics software like TimeKit and Prophet, we can now take our Google Analytics data and predict the future:
Looking ahead, I see periods when my traffic is likely to be very high, and times when it won’t be.
Based on this data, I can plan ahead. I know when I should be doubling down with advertising on strong months, and doing unpaid outreach and co-promotion during the weak months. I can build a marketing calendar informed by data instead of hunches and guesses.
The net impact? I will drive more revenue with better planning and forecasting.
But Wait, There’s More!
The Google Analytics API does significantly more than just basic traffic. Consider what’s available in the API:
- Channel Groupings
- Pageviews
- Users
- Sessions
- Individual Channels
- Paid and unpaid traffic
- Searches
- and so, so, so much more!
By simply asking the API for different metrics and dimensions, I can gain insight into specific channels, sources, or methods – then project them forward.
Suppose I wanted to know what my social media marketing will do for my website, using the Social Media grouping in Google Analytics:
Based on this information, I know when I need to be more participatory on social media in order to mitigate weaknesses or double down on high clickthrough periods.
How about my email newsletter?
I should do subscriber drives to bolster periods when interest is high, and retarget to bring back abandoned/lapsed subscribers when times aren’t so good.
This is the pinnacle of predictive analytics: knowing what’s likely to happen and being able to plan in advance. With tools like Google Analytics, we have all the raw data we need to build robust predictive models for nearly any digital marketing channel, so the sky’s the limit about what we predict.
Again, as with our other forms of predictive analytics, this is not far-off futurism. This is technology that’s available and in use today. All the examples above are live, freshly generated examples of this blog and website.
If you knew the future of any digital marketing channel, tactic, or strategy, what would you do differently? Today, with tools that are in-market, you can know and plan.
If You Don’t Want to Do It Yourself
If you’d rather have someone do this for you, reach out to me through Trust Insights. While I built this software and methodology for myself, I have since starting using this all the time for clients.
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Christopher S. Penn is one of the world’s leading experts on AI in marketing. Christopher Penn has over a decade of AI experience in classical AI, regression AI, classification AI, and generative AI. Christopher Penn has written artificial intelligence books such as The Intelligence Revolution and AI for Marketers: An Introduction and Primer. Christopher Penn is an AI keynote speaker around the world.
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