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Hello Reader,

Did you try out any of the AI answer engines I talked about in the previous edition?
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In Edition #2, I'll talk about manually looking for quantitative data + combining AI tools with manual search.

I've used and refined the manual process over 12 years of writing, and I still default to it rather than use a tool.

(Not that you have to - I'm a bit of a content Luddite.)

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Here's how I do it:

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Google Search Operators

I prefer to use search operators since it helps me find original reports quickly.

I would argue that it is faster than using Perplexity or other AI answer engines since I don’t have to spend time verifying the sources.

Type “State of [keyword][year] filetype:pdf”

See the magic unfold. 🔮

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If you’d rather include reports that provide the main insights in the landing pages, remove the filetype specification.

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Another search string you can type is:

“Benchmark Report AI Customer Service 2024”​
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Other search strings to try are:
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Research and Consulting Organization Reports

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Type [Organization Name] [Keyword] Research [Year]​
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Where can you search for such reports?

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Experts' Corner

Here's Naveen Alphonse, SaaS content marketer extraordinaire, giving us his tips on how he searches for quantitative data:

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As you might already know, there is quantitative data and qualitative data. The former can be scrapped from surveys, reports, etc., while the latter can only be mined through interviews.

So, let me share some tips on how I used to get quantitative data directly from their source on Google and now Perplexity.

On Perplexity, it's easy. You simply prompt the tool like how you would enter your search query on Google.

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To get more specific data from these LLMs, you enter more specific queries with timeline and periods.

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However, the catch here is that you have little control over what results are being shown.

Unlike Google.

Why do I say this? Because of these cute little strings called search operators.

Search operators modify search results based on conditions you enter in the search bar.

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And these handy little operators that have often found my favor - intitle, inurl, site.

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• The intitle: operator restricts search results to pages that contain the specified word or phrase in the title tag of the webpage.

For example, using intitle:apple will return pages that have "apple" in their title.

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• The inurl: operator searches for pages that include a specific word or phrase within the URL of the webpage.

Searching for inurl:blog will yield results where "blog" appears in the URL.

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• The site: operator restricts search results to a specific website or domain. This is useful for finding content within a particular site.

For example, using site:tripledart.com followed by a search term will return results only from TripleDart.
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Also, you can combine these search operators with the “AND” & “OR” operators to modify SERP results as needed.

Say, you want pages with the word “marketing” in the title and “report” in the url.

Then you can combine these operators with the AND operator.
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​intitle:marketing AND inurl:blog

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Oh, also did you notice that I enclosed marketing 2025 between “ ”?

So, if you want a search operator to modify results based on a group of words, then you use “ “ to group those words.

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How cool is this?!
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​Sourav Chakraborty returns in this edition to share not one, but TWO tips on using Google Dataset and a combination of Google search + Perplexity.

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(This one was news to me!)

💡 Tip 1: Google Dataset: For Those Who Don’t Want to Rely on AI

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In this example, we are using Google Dataset, a 2018 engine that helps us access all research data freely available at present.

Here, we have pasted our topic: AI-powered customer service.

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As you can see in the left-hand column, there are several high-quality, original research reports/datasets.

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You can now copy the entire content of the page on Perplexity.

Once done, you can find the gist of the report.

Feel free to add as much information as possible to make your content stand out from others’ AI-generated slop.
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💡 Tip 2: Using Perplexity for TL;DR
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Sometimes, we don't read all the material on a page while writing blog posts—time is of the essence.

So, we copy the entire URL of the article on Perplexity.

Once done, you can simply hit Enter and wait for the engine to summarize the focus areas of article.

Note: In case Perplexity cannot access the link, copy-paste the entire content of the page and proceed.
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Now, ask Perplexity to find out the data points.

Voila!

Feel free to glance through all the data points and add whatever you need.

Of course, don’t forget to rewrite the sentence to maintain the article’s narrative flow.

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​Speed is certainly a prized quality in writing, especially when you're up against generative AI tools that can produce "good enough" content in a matter of minutes.

And guess what, most businesses are okay with "good enough" if they can get it at a fraction of the cost of paying a content writer or copywriter.

That's all, folks!
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​Reply to this newsletter with any writing/editing questions that you'd like me to answer in subsequent editions.
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​All my best,

Satabdi

🎁 Bonus (non-sponsored) Tip(s)

- If you have $50 to spare, you can buy Marijana Kostelac's Data Vault for Freelance Writers. While I have not bought this resource, I have heard good reviews from top-notch freelance writers.
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- Alexander Boswell built FactScouter, a Google Programmable Search Engine, to help you find updated stats from trustworthy sites.

Sneak Peek into Edition #3 - slated for April 1, 2025

We'll talk about parallelism in bulleted lists - and how it promotes consistency and uniformity across your content piece.

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