Let’s be honest: when I first started in marketing, I thought I’d spend my days dreaming up clever campaigns and analyzing big wins. Instead, I found myself knee-deep in spreadsheets, copy-pasting competitor prices, and sorting through endless customer comments.
Turns out, I’m not alone – recent stats show the average marketer spends up to 6 hours a day on routine research tasks like tracking competitors, compiling feedback, and building lead lists. That’s a lot of time not spent on the creative, strategic work we actually signed up for.
But here’s the good news: AI tools for marketing teams are flipping the script. With 75 percent of marketers now using AI to cut down on manual tasks, and 88 percent relying on AI in their day-to-day roles, it’s clear that AI marketing automation isn’t just a trend – it’s the new normal.
So, how exactly are marketers using AI to automate the boring stuff and get back to what matters? Here are five ways I’ve seen (and personally enjoyed) AI transform the daily grind.
Why Marketing Research Matters for Modern Marketing Teams
Marketing research is the backbone of every campaign, product launch, and competitive strategy. Whether you’re planning a new feature, scouting out the competition, or figuring out what your customers actually want, you need accurate, up-to-date data.
The catch? Manual research is slow, fragmented, and – let’s be real – pretty soul-sucking. I’ve spent weeks gathering competitor data, only to realize half of it was outdated by the time I finished.
The stakes are high: 94 percent of workers admit they perform time-consuming, repetitive tasks, and marketers are no exception. The good news is that AI tools for marketing teams are changing the landscape, making research faster, more accurate, and a whole lot less painful.
How AI Marketing Automation is Changing Research
AI marketing automation is like having a supercharged research assistant who never sleeps, never makes typos, and doesn’t complain about Mondays.
By automating data collection, analysis, and even reporting, AI tools help marketers reclaim hours each week. According to HubSpot, 86 percent of marketers say AI saves them time – at least an hour or more per day.
The real magic happens when AI web scrapers and other AI-powered tools take over the repetitive stuff – scraping competitor prices, sorting customer feedback, or finding the next big trend.
These tools don’t just make research faster; they make it scalable and more reliable. Let’s dig into five practical ways marketers are using AI to automate the boring research tasks.
1. AI Web Scraper for Competitor Content and Pricing Research
Remember the days of manually checking competitor websites, copying prices into spreadsheets, and hoping you didn’t miss a promo? Yeah, I don’t miss those either.
Now, marketers are using AI web scraper tools to collect competitor product, pricing, and promotional data in just a couple of clicks.
Instead of endless browser tabs and screenshots, Thunderbit’s AI reads the website, suggests which fields to extract (like product name, price, and stock level), and scrapes the data into a neat table.
You can export everything to Excel, Google Sheets, Airtable, or Notion – no coding required. For e-commerce teams, this means you can set up Thunderbit to monitor competitor product pages and get alerts within minutes of any price drop or update.
Thunderbit: The AI Web Scraper Advantage
What I love about Thunderbit is how easy it is to use – even for folks who aren’t tech wizards. Here’s how a typical workflow looks:
- Install the Chrome Extension.
- Navigate to a competitor’s website.
- Click “AI Suggest Fields” – Thunderbit’s AI scans the page and recommends which data to extract.
- Adjust the fields if you want, then hit “Scrape.”
- Export the data to your favorite tool (Excel, Google Sheets, Airtable, Notion – you name it).
Thunderbit even handles subpage scraping (think: visiting every product page in a category) and scheduled scraping, so you can automate regular checks without lifting a finger.
For SaaS teams, it’s just as handy for compiling competitor pricing pages and feature lists. The time savings? Huge. What used to take me hours now takes minutes – and I don’t have to worry about missing a sneaky price change.
2. AI Tools for Customer Review Extraction and Sentiment Analysis
Sorting through hundreds (or thousands) of customer reviews used to be a nightmare. Now, AI tools for marketing teams can extract reviews from multiple platforms and analyze sentiment in seconds. No more manual tagging or endless scrolling – just actionable insights.
Survicate: Automating Feedback Collection
Survicate is a standout here. It centralizes feedback from web surveys, in-app surveys, NPS scores, support chats, and even App Store reviews.
Survicate’s AI then categorizes and tags all incoming feedback by sentiment, topic, and urgency. Instead of reading every comment, you get a dashboard showing what customers are saying – and how they feel about it.
One feature I find especially useful is Survicate’s AI Research Assistant. You can ask it questions like, “What are the most common complaints about our onboarding process?” and get instant, data-backed answers.
This kind of automation means you can spot issues (or wins) in real time and respond before they snowball.
For SaaS marketers, this means better product-market fit data and customer insight with far less grunt work. And for e-commerce teams, it’s a lifesaver for tracking delivery complaints or product feedback across channels.
3. AI-Generated Industry Research Summaries and Reports
Let’s face it: nobody has time to read every industry report, whitepaper, or competitor blog. That’s where AI-powered summarization tools come in. Instead of slogging through 50-page PDFs, you can get the highlights in seconds.
Genei: Accelerating Research Synthesis
Genei is my go-to for summarizing long documents and web pages. You can upload a report or paste a URL, and Genei’s AI will generate an automatic summary, extract keywords, and even answer questions about the text.
For content marketers, this means you can speed up blog research and pull out relevant quotes or data points without reading every word.
Strategy teams use Genei to compile competitive intelligence, while writers love it for generating citations and references. The best part? It handles academic papers and outputs layperson summaries – perfect for B2B marketers who need to digest technical research fast.
4. AI-Powered Trend and Keyword Discovery for SEO
Staying ahead of the next big trend is every marketer’s dream – but finding those trends before everyone else? That’s the tricky part. AI tools now make it possible to spot fast-rising search terms and emerging niches before they hit the mainstream.
Exploding Topics: Staying Ahead of the Curve
Exploding Topics uses AI-driven trend forecasting to surface topics that are just starting to gain traction.
Unlike traditional SEO keyword tools, it identifies what people will be searching for in the coming months. You get a dashboard of trending terms, growth curves, and the ability to filter by category.
For content and SEO teams, this is a goldmine. You can plan content calendars around rising topics, optimize campaigns for emerging keywords, and even align product messaging to tap into new demand.
I’ve used Exploding Topics to spot up-and-coming industry terms and publish content before the competition catches on – giving my sites a real SEO edge.
5. AI Web Scraper for Lead Extraction from Webpages, PDFs, and Social Media
Building lead lists used to mean hours of manual searching, copying names, and hunting down emails. Now, AI web scraper tools can extract potential customer lists from websites, PDFs, and even social media – no more copy-paste marathons.
Phantombuster: Automating Lead Generation
Phantombuster is a favorite among B2B marketers and sales teams. It’s a platform of mini-bots (called “Phantoms”) that can scrape LinkedIn profiles, search for emails, and even automate social media actions.
For example, you can set up a Phantom to scrape LinkedIn for VP-level contacts in your industry, then another to find their business emails. The result? A ready-to-use lead list without any manual copying.
Phantombuster runs in the cloud, so you can schedule tasks to run overnight or refresh your lead list weekly. For agencies and growth hackers, it’s like having a virtual SDR working around the clock.
Key Takeaways: The Future of AI Marketing Automation for Research
AI tools for marketing teams are no longer a luxury – they’re a necessity. By automating the boring research tasks, marketers can focus on what really matters: strategy, creativity, and building relationships.
Whether you’re scraping competitor data with Thunderbit, analyzing feedback with Survicate, summarizing reports with Genei, spotting trends with Exploding Topics, or building lead lists with Phantombuster, there’s an AI tool to make your life easier.
If you’re just starting out, pick one pain point to automate – maybe competitor monitoring or feedback analysis – and prove the value before expanding.
Upskill your team, integrate AI tools with your existing workflows, and always keep a human eye on the outputs. And don’t forget to measure your results: are you launching campaigns faster? Getting better leads? Use those wins to iterate and improve.
