How Marketers Are Using AI to Automate Boring Research Tasks and Save Hours Every Week

5 Ways Marketers Are Using AI to Automate Boring Research Tasks

May 29, 2025

When I started in marketing, I imagined spending my days crafting clever campaigns and celebrating wins. Instead, I was buried in spreadsheets, copy-pasting competitor prices, and sifting through endless customer comments. This isn’t unique—marketers spend up to 6 hours daily on routine research tasks like competitor tracking, feedback compilation, and lead list building. That’s time taken away from the creative and strategic work marketing demands.

Thankfully, AI tools have changed how marketing teams handle these tasks. With 75% of marketers using AI to reduce manual work and 88% depending on it daily, AI marketing automation is now standard practice.

Why Marketing Research Matters for Modern Marketing Teams

Marketing research is essential for campaigns, product launches, and competitive strategies. Whether planning new features, analyzing competitors, or understanding customers, accurate and current data is crucial. Manual research can be slow and frustrating. Weeks of gathering competitor data often become outdated fast. Since 94% of workers perform repetitive tasks, marketers aren’t exempt. AI tools are speeding up research, improving accuracy, and making the process less painful.

How AI Marketing Automation is Changing Research

Think of AI marketing automation as a tireless research assistant. It automates data collection, analysis, and reporting, freeing marketers from repetitive work. HubSpot reports 86% of marketers save at least an hour daily thanks to AI. AI-powered web scrapers and analytics tools handle tedious tasks like scraping competitor prices, sorting feedback, and spotting trends—making research faster, scalable, and more reliable.

1. AI Web Scraper for Competitor Content and Pricing Research

Manual competitor price checks and data copying are things of the past. AI web scrapers gather product, price, and promotional data in a few clicks. For example, Thunderbit’s AI reads competitor websites, suggests relevant data fields, and scrapes the info into organized tables. Exporting to Excel, Google Sheets, Airtable, or Notion requires no coding.

E-commerce teams can monitor competitor product pages with alerts for price changes or updates. SaaS teams benefit from compiling competitor pricing and feature lists quickly.

Thunderbit: The AI Web Scraper Advantage

• Install the Chrome Extension.
• Visit a competitor’s website.
• Click “AI Suggest Fields” for data extraction recommendations.
• Adjust fields as needed and hit “Scrape.”
• Export data to your preferred tool.

Thunderbit also handles subpage scraping and scheduled scraping for automated ongoing monitoring. What once took hours now takes minutes, with no risk of missing price updates.

2. AI Tools for Customer Review Extraction and Sentiment Analysis

Sorting through hundreds or thousands of customer reviews used to be overwhelming. AI now extracts reviews from multiple platforms and analyzes sentiment instantly. No more manual tagging or scrolling—just clear, actionable insights.

Survicate: Automating Feedback Collection

Survicate centralizes feedback from web and in-app surveys, NPS scores, support chats, and app store reviews. Its AI tags feedback by sentiment, topic, and urgency. Instead of reading every comment, marketers see dashboards highlighting key customer sentiments.

Survicate’s AI Research Assistant answers questions like, "What are the most common complaints about our onboarding?" in real time. This helps teams fix issues quickly or capitalize on wins. SaaS marketers get better product-market fit data, and e-commerce teams can track delivery or product concerns across channels.

3. AI-Generated Industry Research Summaries and Reports

Reading every industry report or competitor blog isn’t feasible. AI summarization tools create quick highlights, saving hours.

Genei: Accelerating Research Synthesis

Upload reports or share URLs, and Genei generates summaries, extracts keywords, and answers questions about the text. Content marketers use it to speed up blog research and find quotes or data points fast. Strategy teams compile competitive intelligence, while writers generate citations. Genei handles academic papers and outputs simple summaries, ideal for B2B marketers digesting technical content.

4. AI-Powered Trend and Keyword Discovery for SEO

Spotting emerging trends and keywords ahead of competitors is key to SEO success. AI tools now forecast rising search terms and niches before they become mainstream.

Exploding Topics: Staying Ahead of the Curve

Exploding Topics uses AI to identify fast-growing topics and provides dashboards with trending terms and growth data. Marketers can filter by category and plan content around rising keywords, optimizing campaigns and product messaging to capture new demand. Using this tool, I’ve published content on up-and-coming terms before others, gaining an SEO advantage.

5. AI Web Scraper for Lead Extraction from Webpages, PDFs, and Social Media

Lead list building no longer means hours of manual searches and copying. AI web scrapers extract potential leads from websites, PDFs, and social media quickly.

Phantombuster: Automating Lead Generation

Phantombuster offers mini-bots (“Phantoms”) that scrape LinkedIn profiles, find emails, and automate social media actions. You can set a Phantom to find VP-level contacts and another to gather business emails, creating ready-to-use lead lists without manual effort. Running in the cloud, it schedules tasks for overnight or weekly updates. For B2B marketers, agencies, and growth hackers, it’s like having a virtual SDR working nonstop.

Key Takeaways: The Future of AI Marketing Automation for Research

AI tools are essential for marketing teams, automating tedious research so you can focus on strategy, creativity, and relationships. Whether using Thunderbit for competitor data, Survicate for feedback, Genei for summaries, Exploding Topics for trends, or Phantombuster for leads, AI can simplify your workflow.

Start by automating one pain point like competitor monitoring or feedback analysis. Prove the value, then expand. Train your team, integrate AI with your current tools, and always review outputs carefully. Measure results: Are campaigns launching faster? Are leads better? Use these insights to improve continuously.

Explore more AI marketing automation tools and training options at Complete AI Training to stay efficient and competitive.