My two favorite ChatGPT Plus plugins and the remarkable things I can do with them



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When I checked this morning, the ChatGPT Plus plugin store had 119 pages of plugins. With eight plugins per page, that brings us to 952 plugins. Clearly, folks have extended ChatGPT in lots of ways.

There are gotchas, of course. For example, while there are 952 plugins, you can only use three of them at once. If you want to use different plugins, you need to launch a new session and choose a new set. Additionally, if you want to use OpenAI’s own mega-plugin, Advanced Data Analysis, you can’t run it with any of the other plugins.

Also: The 10 best ChatGPT plugins of 2023

Here on ZDNET, we’ve looked at a lot of plugins. I did a deep dive into a few of them in Extending ChatGPT: Can AI chatbot plugins really change the game? and Steven Vaughan-Nichols did a roundup of his favorite plugins.

But I haven’t been looking at plugins simply to write about them. I’ve started to integrate ChatGPT and plugins into my regular productivity process. And here’s what’s interesting. For day-to-day work, I’ve found I need exactly two plugins. I just haven’t felt a compelling need to use the others.

Unfortunately, I can’t run these two plugins at the same time.

My two favorites

By far, the single most useful and reliable plugin I’ve found has been ChatGPT’s own Advanced Data Analysis plugin. This plugin reads data files, does analysis, generates charts, and can even do image analysis. (Although I haven’t used it for that.)

You can turn on Advanced Data Analysis in the Settings dialog. You’ll find it under beta features. Don’t be confused, however:  Advanced Data Analysis used to be called Code Interpreter. It was renamed last month. 

The second high-value plugin I use is WebPilot. This allows ChatGPT to access the web. Previously, I had been using MixerBox WebSearchG to do the same thing, but found it failed more often than not. So far, WebPilot hasn’t failed me.

There are limitations, however. WebPilot can’t do much with comprehensive Amazon searches, for example. That’s because, while it can visit and extract content from webpages, it doesn’t have the capability to interact with dynamic elements on the page, such as dropdowns, filters, or search bars.

Also: ChatGPT and I played a game of 20 Questions and then this happened

Armed with these two plugins, I can do comprehensive data analysis and I can have ChatGPT get current data from the web. I just can’t do both in the same session, which means there will now and then be some hoop-jumping required to find what I want.

Work within the limits

There are definitely limits to what these plugins can do. WebPilot is great at pulling in a single page of information. Sometimes, as in my Yelp experiment, it can scan multiple pages. But it tends to fall down when it has to perform multiple queries.

Also: I needed a mechanic. Here’s how ChatGPT Plus helped me skip reading online reviews

This is unfortunate because doing a number of web scans and then analyzing those results is where a lot of productivity gains can be had. Let’s take a recent example. I’m building a PC using the AMD Ryzen 5 5600X processor. That processor was chosen specifically because it’s recommended for a piece of software I want to run. I want a motherboard that can host that processor. I tried to get ChatGPT Plus with WebPilot to do a comprehensive scan of Amazon’s offerings and reviews. It kind of didn’t.

My prompt: 

Use WebPilot. Find me ten PC motherboards in each price range that support the Ryzen 5 5600X processor using the AM4 socket. Include star reviews and a link to each product. Show as a table.

I got back a list, sure. Not all the motherboards could support the AMD Ryzen (one or two were Intel platforms). It gave me star ratings, but the URLs provided weren’t to the products’ pages on Amazon, they were to Amazon’s main page.

Some of this is the nature of the web, of course. Every page is coded differently. Some companies go out of their way to obfuscate page scraping. Others are just difficult to capture as a matter of how they’re engineered, without any active blocking on the part of web developers.

Also, the AI doesn’t like going down a master list and presenting results all at once. It likes to provide an answer, wait for a pat on the head, and then go on to the next answer. In this way, ChatGPT is like a puppy.

Also: Only 18% of Americans have ever used ChatGPT 

The key to success is to work within the limits. For example, I can select a bunch of motherboards that look interesting and then feed each to ChatGPT with WebPilot and ask for sentiment analysis of user reviews — once I locate the exact review link for that product.

For example, I wanted to know if one of the boards I was interested in had noise issues. I had to provide a set of prompts before I got some workable answers:

Do users have complaints about noise with this product: {insert URL link here}

This returned a general discussion of user complaints, but nothing on noise.

Search the web for that motherboard and noise issues

This returned a single user forum complaint about noise on a tech site.

Any other reports?

This brought back a report of noise issues from YouTube, Reddit, and a PC-builder tech site. So it is possible to get the information you need. You just have to work at it.

Advanced Data Analysis

The second plugin is ChatGPT’s own Advanced Data Analysis. This is hugely powerful, but is limited to the pre-November 2021 dataset… unless…

The trick here is that ChatGPT Plus with Advanced Data Analysis allows you to upload data files. As such, you can update data that’s newer than the 2021 cutoff date.

Also: How to use ChatGPT to make charts and tables

I showed a lot of charting and table analysis using Advanced Data Analysis in this article. But the place where uploading your own data proved incredibly powerful was when I did some sentiment analysis on a 22,797-record database when uninstalling my code. I hadn’t had the time to write code to do that cross-indexing analysis, but ChatGPT did it for me in minutes.

I recently used it with another dataset. There’s a service for journalists where you can post a question, and then public relations folks and those interested in promoting themselves and their companies can respond.

This is a great resource for getting insights from the folks actively involved in whatever you’re researching. The downside is the signal-to-noise ratio is huge. Lots and lots of people pitch answers, often unrelated to what I’m researching, and often the people pitching don’t meet my criteria for inclusion in my research.

Sifting through the pitches for a given project can take days. I tried to download and feed the full set of responses to Advanced Data Analysis, but it didn’t like that. But when I did some pre-prep work, turning each pitch into a record in an Excel database (I used a tiny bit of programming for that), then Advanced Data Analysis was able to understand the information.

Also: The moment I realized ChatGPT Plus was a game-changer for my business

I didn’t want ChatGPT to do the research or analysis, but it was able to separate out those submissions that included an executive’s name and title. I asked a few key questions that would help flag an entry as coming from someone who actually read the directions. When I asked ChatGPT to parse those entries for those tests, it was able to present to me a set of qualifying candidate pitches.

I’m not providing those prompts because they were totally unique to that project. But the point is that I did some basic work to prep Advanced Data Analysis, and then it did a bunch of analysis. Usually, it takes me three to four days to go through the hundreds of pitches and sift out the workable data. This time, it took me about half a day.

That’s a huge productivity savings.

The key to success with ChatGPT prompts

Certainly, there are limits to ChatGPT, not the least of which is that the AI doesn’t always do what you want and it makes stuff up. But ChatGPT can be a huge time saver if you delegate carefully.

Notice that word: Delegate. When used as a verb, Webster’s defines “delegate” as “to entrust to another.” If you’re a manager, the ability to delegate is an important part of the job. But delegating isn’t just barking assignments at subordinates. Delegating is entrusting, yes. But it’s also guiding and verifying the work product.

This is how you must learn to work with ChatGPT. Don’t think of it as a computer program. Think of it as a person to whom you’re assigning work. Is that assignment too complex? Is that assignment too vague? Is there a way for the person to succeed with that assignment or are you setting them up to fail?

Also: 4 things Claude AI can do that ChatGPT can’t

We’re all familiar with these workplace scenarios, so they should be something you can apply to your AI prompting work.

If what you give the AI confuses it, figure out how to clarify. If what you give the AI is too much for it to work with, figure out how to break the project into stages.

Also, don’t limit yourself to one tool. If you’re a manager, you might have one employee who’s great at people interaction. You might have another who’s great at fixing things, and yet another with great math skills. You might initially assign one phase of the project to one worker and then move it to another as the needed skills change.

That’s what I did with my public relations pitch project. Parsing the replies into comma-separated value lines was easy for my programmer’s text editor. I just did a few search and replace operations. Then I opened the document in Excel to see whether it was what I thought I’d created. Only once the data was confirmed did I feed it into ChatGPT and Advanced Data Analysis.

Also: How to use ChatGPT to do research for papers, presentations, studies, and more

So what’s the key to ChatGPT success, especially with these two plugins? Learn to break the project down so that the plugins can understand it, and then use all the tools at your disposal to get your results.

If you do that, you’ll likely find ChatGPT provides a measurable productivity boost for some of your projects.

Oh, and that’s my final suggestion: Keep in mind that not every project is one you can give to the AI. Take your wins where they’re appropriate and use other tools to do tasks not suited to artificial intelligence.

Good luck. Live long and prosper. May the force be with you.

You can follow my day-to-day project updates on social media. Be sure to subscribe to my weekly update newsletter on Substack, and follow me on Twitter at @DavidGewirtz, on Facebook at, on Instagram at, and on YouTube at


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