While most marketers are still unsure exactly how intelligent machines—namely Artificial Intelligence (AI) and machine learning (ML)—will impact advertising, most believe that the potential is there to revolutionize the industry.
In a recent study on this topic, marketers listed some of the ways that AI is helping them already with accelerating growth, getting more actionable insights, reducing the time spent on repetitive tasks, and more.
These are certainly fantastic outcomes for marketers who face an ever-evolving landscape of competitors looking to capture market share and win customers however and whenever they can.
Getting negative keywords right is key in search-triggered advertising
When it comes to Paid Search and Retail Media advertising, one of the most important aspects for practitioners to manage closely is their keyword lists.
This can be a rather arduous task for some marketers because of just how many keywords can be part of enterprise-level accounts. It’s not rare for these programs to be comprised of thousands of them—if not tens or hundreds of thousands, or in extreme cases, millions of keywords. Given how many other campaign elements that search marketers must maintain, managing large keyword lists can be unwieldy and tough to keep on track.
While figuring out which keywords to bid on is an important factor for Paid Search and Retail Media success, sometimes one of the best optimization tactics is to apply negative keywords to ensure that the wrong keywords don’t waste your budget. This can happen fairly often in the channel due to the way that match types work to cast a wide net to ensure that brands are able to reach consumers interested in their relevant keywords without having to come up with every possible variation an individual user may use when querying a search engine.
For example, a pet food brand could bid on dog food using broad/phrase match without having to iterate every combination the hundreds of known breeds of dogs, i.e. Doberman dog food, Boxer dog food, Dalmatian dog food, etc.
That’s where broad/phrase match works really well. But, what about an online grocery store that delivered fresh fruit and vegetables would commonly sell apples. Because Apple is also a company, using negatives such as -computer, -tablet, and -phone would make sure that the grocer doesn’t get pulled into any MacBook, iPad, or iPhone searches. Appearing for those searches with your grocery ads could waste your budget on clicks from people that might have a passing interest, but don’t convert because it wasn’t what they went to the search engine to look for in the first place. Even worse, appearing in too many irrelevant searches may have problematic effects on your click-through rate. This could hurt your program’s Quality Score and damage your ability to appear as often for actual, relevant searches.
Google Search Ad’s help article on the topic echoes this advice:
“One key to a highly targeted campaign is choosing what not to target. When selecting negative keywords for search campaigns, look for search terms that are similar to your keywords, but might cater to customers searching for a different product. For example, let’s say you’re an optometrist who sells eyeglasses. In this case, you may want to add negative keywords for search terms like ‘wine glasses’ and ‘drinking glasses.”
Figuring out which terms to bid on is an important search marketing task, but then layering in negative keywords to better control your ad delivery is an advanced tactic that can take many, many hours of deep analysis to get right.
Kenshoo’s AI-enabled Search Term Analysis feature helps marketers save time and money
Intelligent machines can’t do all of the things that humans can, but some things they are really good at—namely recognizing patterns in large data sets in seconds. In this first era of intelligent machines in marketing, it is in these areas of pattern recognition and data analysis where they can be of most help to practitioners.
Kenshoo now has a new AI-enabled feature to help Search and Retail Media marketers figure out where they can apply negative keywords to decrease budget wasted to appearing in the least-valuable searches. Through a proprietary data mining process, Kenshoo’s technology compares the performance of keyword combinations to offer suggestions for search practitioners to investigate for possible negative keyword usage.
Take for example a company that sells Vitamin-E oil. Applying broad/phrase match on the term Vitamin-E makes a lot of sense in order to capture as many user searches as possible. While some consumers searching for Vitamin-E will be open to oil, they may not convert because they prefer pill forms such as capsules, soft gels, and tablets. Based on the performance of these terms—Kenshoo’s AI feature may find that data that suggests the brand should add those terms to their negative keyword lists to avoid appearing in those specific user searches.
Just because you sell Vitamin-E doesn’t mean you want to show up in every Vitamin-E search
As great as AI can be, marketers may still have a bit of hesitation turning over the actual decision-making process to machines. Kenshoo’s Search Term Analysis doesn’t make the change for practitioners but rather suggests terms to investigate on their own so marketers can make changes themselves.
To uncover insights like these would take a lot of time manually (hours and hours) and because it’s like looking for a needle in a haystack, it would be very easy for even the most experienced search analyst to miss.
There’s also a true, cross-channel opportunity for Paid Search to learn from Retail Media keyword performance, and vice-versa.
The Search Term Analysis features can examine Amazon Advertising keyword performance as part of the analysis for search marketers but also use Google keyword performance as part of the analysis for Retail Media marketers to use in their Amazon Advertising campaigns. This insight-gathering from one channel to another is a truly unique feature that only a partner like Kenshoo that is connected to both Google and Amazon Advertising can offer.
Interested to learn more about Kenshoo’s innovative AI-enabled features?
Kenshoo has a 15+ year history of being an enterprise-level paid search, social advertising, and retail media platform for the biggest brands and agencies in the world to manage their marketing.
We pride ourselves on our cutting-edge, innovative technology and we are actively looking for more ways to embed AI and ML into our feature-rich suite of marketing tools.