AI and machine learning in paid advertising has changed the landscape in so many ways, including streamlining processes and eliminating unnecessary manual tasks. That being said, there are many ways that advertisers can and should be actively optimizing their AI-backed tactics to ensure the best possible results.
- Start with Clear Goals and Baselines: Before deploying an AI campaign or asset, be sure that you’ve discussed your goals and primary KPIs with your team or client. For example, are you more interested in acquiring new customers than driving short-term revenue? In that case, a tCPA bidding strategy might be a better fit than a value-based (or revenue-driven) strategy. It’s also extremely helpful to have baseline historical performance data so you understand what typical costs look like, and set bids accordingly.
- Invest in Data Quality: I’ve said it before and I’ll say it again – the most valuable resource a modern, digitally activated brand has is its first party data. Campaign algorithms benefit enormously from rich data such as offline conversion tracking, customer lifetime value, and even profit margins, which can train the bidder to pursue the leads that will result in the highest ROI (or whatever business goal – such as acquisition of new customers – you set). The better the data signals, the better your campaigns will perform. You’ll also want to be sure you’re regularly auditing your data sources – be sure that offline datasets are being imported frequently, and that conversions are tracking as you intend. Stale data or redundant/incomplete conversions can confuse the algorithm.
- Maintain Human Oversight and Creativity: Even though I’ve boarded the AI train and fully believe in its power, I can’t stress enough that these tools still require thoughtful oversight. AI is great at automating mundane tasks, but nothing can replace years of experience (and that special gut instinct we develop for when to change a bid, when a campaign is a flop, when a keyword is irrelevant). Algorithms can absolutely make mistakes, like overspending on broad terms, and there are certainly tasks such as creative strategy that it simply cannot do. Be vigilant about reviewing performance at every level, and continue to brainstorm new ways to guide overall campaign strategy.
- Stay Informed on New Features: I highly recommend subscribing to the Google Ads and Microsoft Ads blogs if you don’t have a rep sending regular updates. LLMs also make it incredibly easy to stay up-to-date on relevant news (try setting up weekly automated news dumps directly into Slack!). Early adopters of new products often gain an edge with lower costs, so don’t be afraid to test.
Continual guidance and refinement of AI strategies can lead to tangible performance benefits, and automation of tasks frees us up for more strategic work. These tactics and more are a great start at ensuring your Paid Search campaign strategy is as lean and competitive as possible. Be on the lookout for future IgniteIQ blog posts on more actionable recommendations for improving your workflows.
Happy automating!
