What happens when search data shows your organization’s content isn’t being served?
You dig deeper into the data.
That’s what Brian Piper does as director of content strategy and assessment at the University of Rochester. At Marketing Analytics and Data Science Conference, he explained what his team did and how they expanded their SEO work in the age of artificial intelligence.
See organic traffic drop to almost zero
At one point, a new article on the University of Rochester’s NewsCenter, promoted in a newsletter and on social media, attracted traffic in the first week before dropping to almost zero.
This increase in traffic was beneficial to the university’s business objective: to raise awareness – and the main content KPIs – page views and new visitors. But Brian and his team knew that these occasional traffic problems wouldn’t be enough.
So they analyzed the audience and developed a strategy to create and optimize content so that future visitors asking similar questions would see the University of Rochester in their search results.
Their data-driven strategy worked. Organic search traffic page views between July 1, 2022 and June 30, 2023 increased by 540% compared to July 1, 2017 and June 30, 2018.
Improve rankings and organic search traffic
If you’re like many marketing analytics and data analysts, SEO remains one of your organization’s top KPIs. However, today SEO World is even less predictable than it used to be (and it’s always been a mystery).
Investigating small things could have a significant impact on your organic traffic. Brian says the process begins and ends with data. Analyze current metrics against your strategy and your objective. Then make changes and measure the impact of those changes. Let’s look at several ways the University of Rochester does this and how you can too:
Meta descriptions: The data showed that the University of Rochester ranked well for several high-volume search terms, but searchers weren’t clicking on their content. Brian optimized meta descriptions adding the names of specific programs (e.g., Simon Admissions Team) and researchers began clicking through and visiting program sites.
Images and social networks: Conventional wisdom says not to post images with text because search engine crawlers don’t read text. But that conclusion is no longer true, Brian says.
His team now advises schools and programs within the institution to put their logo on their published images. Now, when their images appear in search, users can see the name of the institution, Brian says.
The same in-image text tips apply to visual social media assets, including covers, banners, and headers.
Not only do social media images appear, but your social accounts may also appear in search. Brian says this makes it even more important to include the right keywords in your profiles.
Voice search: As more and more people, especially Generation Z and Generation Alpha, use voice search More frequently, Brian spends time testing voice platforms to see if responses include branded search terms and strategic keywords.
“The problem with voice search is that there is only one result,” explains Brian. The university’s strategy for inclusion in this answer is to become a featured snippet in text search results. Then, it modifies this content to include its brand in voice search results.
Brian explains, “When someone asks a question about good research universities in New York, we want them to say that the University of Rochester is one of those schools. »
Community search: The data also tells Brian that traditional search engines aren’t enough for the University of Rochester to attract an organic audience. Gen Z and Gen Alpha frequently prefer to search community sites like Reddit. So Brian monitors these communities.
“We’re trying to figure out how to get our subject matter experts to participate in these communities, add value to these communities, step in, answer questions and help solve problems without offering or selling anything on these channels,” he said. .
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Optimize content for AI-generated results
Voice and community searches aren’t the only differences in modern search traffic. These days, it’s also important to have data on where your content and brand appears. generative AI resultschatbots and search engines.
Brian and his team see where the University of Rochester appears for its targeted keywords – branded and unbranded – in ChatGPT And Gemini. “We look for those in these different tools and see what content comes back and how we can change that and influence that,” he says.
For example, the University of Rochester published a paper titled Why did the United States enter World War I?» It featured the ideas of Hein Goemans, associate professor of political science and author of War and Punishment: The Causes of War Termination and the First World War.
The title should work well for people asking this question in research: most likely high school students writing a paper for their history class and the ideal customer profile for college. Expecting search traffic, adds Brian calls to action on the page allowing visitors to learn more about the University of Rochester’s history program.
But when Brian asked ChatGPT “Why did the United States enter World War I,” the answer obviously didn’t mention the University of Rochester paper.
“The great thing about using ChatGPT is that you can just ask it, ‘Well, what are the sources?’ Where do you get your information from? And he’ll tell you,” Brian said.
It turns out that the ChatGPT search did cite the article, but the ChatGPT response didn’t show it.
Next, the team looked at the cited content to see how they could modify the university’s content to have a greater impact on the AI-generated response.
After Brian’s presentation, I did a Google search asking, “Why did the United States enter World War I?” » The Google AI preview featured the University of Rochester paper as the source.
She also appeared as the fourth source listed when the question was asked via Google’s Gemini:
Although the University of Rochester paper is not yet shared in a ChatGPT response, the paper is cited for the same research by Perplexity, an AI search engine:
Using AI to help with SEO analysis
Designing content to appear in generative AI quick replies and search results isn’t the only way artificial intelligence can help your marketing analytics. He can do an analysis.
Brian says that while Google Search Console has a ton of useful data, it doesn’t present it in an easy-to-use way. “You can’t see the page URL and keyword in the same view. And when you export from Google Search Console, it only gives you part of the actual data,” he says.
So Brian got help from Google. Studio Looker (free). They connected Looker Data Studio to their Google Search Console account so they could access all the data in a single dashboard view. It displays data from the university’s NewsCenter content: search query, URL, impressions, clicks, and average content ranking position.
“You can actually put the URL at the top and it will tell you all the different terms that you’re ranking for on that page. So when you’re looking to optimize your content, this is a great resource. We use it all the time, and [analyzes] 929,000 results on our NewsCenter site.
But AI’s assistance doesn’t stop there. Brian exported the Looker Studio dashboard metrics to a spreadsheet and uploaded the CSV file to ChatGPT.
He created a prompt using Christopher Penn from Trust Insights RACE frame — role, action, context, execution.
Role: “You are a content marketing expert.”
Action: “You will provide strategic recommendations on new content we could create that would support our strategic priorities and be relevant to future undergraduates, graduate students or knowledge seekers. »
Context: “Use the attached Search Console data to see areas where we currently have search potential, compare this to the general interest of our target audience, and determine what content could also support our strategic priorities on http ://boundless.rochester.edu.”
Execute: “Create 20 new content ideas, please. Take your time.”
ChatGPT immediately returned strategically relevant content ideas for areas the University of Rochester already ranks for. “This will help us establish our expertise and authority in certain areas so we can start ranking even more terms, which will add additional search power to us,” says Brian.
Experimenting with AI, SEO and AI SEO
The opaque nature of AI engines means that, like Brian, marketers and data analysts will need to explore, observe and experiment.
Make data-driven recommendations. Try some things and see if they work. If not, try something else. If so, be aware that it might not last when the search formula changes.
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Cover image by Joseph Kalinowski/Content Marketing Institute
