Depending on your disposition regarding technology and the amount of sci-fi you consume, reading and talking about artificial intelligence (AI) can either be exciting or nightmarish.
Personally, after most of the things I see or read about AI, I usually have the same question: so what am I actually supposed to do with any of this information? Having done a very scientific poll in which I asked three people for their opinions, I can say that I’m not alone in this reaction.
That’s why I’m happy to be able to provide a look at a real-world AI application happening right here at Simple Machines. I’m even happier to report that, from my perspective, it’s a positive thing and is not directly contributing to job loss or the enslavement of the human race at the hands of resentful robots (at least not at this time, to the best of my knowledge).
Pre-AI Google Ads Management
If you’re familiar with the ins-and-outs of managing an Google Ads campaign, you know that running it effectively involves a lot more than writing a few ads and setting your budget.
For starters, there’s:
- Creating and testing different landing pages (the pages you’re sending visitors to)
- Monitoring competitors to ensure your bidding strategy is receiving cost-effective placement (i.e. ensuring you’re not paying too much for good rank in search results)
- Analyzing searched keywords to filter out the poor performers and give more weight to those more likely to turn into customers (not paying for visitors you don’t want)
Sure, you can put it on autopilot, but if you care about getting the best ROI from this channel, these are the things that should be actively managed.
Back in the olden days (say, last year), this involved a LOT of time-consuming manual work. A campaign with several ad groups and landing pages would have hundreds of clicks to sort through and analyze every week.
For a human to take all that data, analyze it, develop recommendations and implement them on a consistent, ongoing basis is a big undertaking to manage – and that’s just one campaign.
For an agency that manages several campaigns for various clients, scaling becomes a challenge pretty quickly.
Google Ads Management with AI
There are a number of AI tools that can be used for pay-per-click optimization – including some built-in Google capabilities that are being rolled out. Currently, we’re using one called Optmyzer.
This technology is evolving quickly and we’re continuing to reassess how to best make use of it, but here’s what I can say at this point. AI doesn’t replace humans when it comes to Google Ads; we’re still actively managing the campaigns we’re in charge of, but AI does help us make better use of our time and gives us insights we can leverage to manage them better.
Here are a few of examples of Optmyzer tools we leverage:
- Daily reports with keyword analysis and recommendations for improvement
- Automated split testing using AI-generated insights into the keywords and ads most likely to convert visitors
- Alerts regarding anomalies and issues with the campaign
- Detection of broken links
- Detection of expensive keywords that aren’t converting
- Hour of the week analysis
Not all of the recommendations AI supplies are good ones, and not all alerts are relevant. The AI is being used to process data and identify trends — and it’s on us to use our own judgement, experience and common sense to parse what should be implemented, what should potentially be considered or tweaked and what should be ignored completely.
But having the auto-generated help saves us from having to manually wade through mountains of data in search for those trends, which means we can spend more time on things like analysis, strategy and creative.
The level of AI we’re using in this example is just the beginning. Sure, it’s cutting edge compared to the spreadsheets we were using before, but I’m confident that in a couple years, reading this post will feel like watching someone today marvel at how fast you can get online with AOL and a dial-up modem.
There are plenty out there making predictions about where AI is going and when it’s going to hit. Most of the predictions so far have been wrong, which is why I now mostly tune them out.
But when you get past the hype, it’s easy to see why there’s a lot of excitement around AI. Given that it’s helping us get out of the weeds, do work more efficiently and generate better returns for our clients by serving more relevant ads to their audiences, I’m finding it to be more exciting than nightmarish.
For now, at least.