{"id":10542,"date":"2025-11-06T16:50:58","date_gmt":"2025-11-06T22:50:58","guid":{"rendered":"https:\/\/attentionmedia.io\/?p=10542"},"modified":"2025-11-06T16:50:58","modified_gmt":"2025-11-06T22:50:58","slug":"ai-is-your-key-to-better-market-research-and-planning-2","status":"publish","type":"post","link":"https:\/\/attentionmedia.io\/?p=10542","title":{"rendered":"AI is your key to better market research and planning"},"content":{"rendered":"
\"Robots<\/div>\n

Marketers are learning to turn AI into a tireless research partner \u2014 and a faster path to insight.<\/p>\n

At the November MarTech Conference<\/a>, experts from Citrix, Randstad Digital and Qualified Digital joined Susan Ferrari, senior director at EmotionTrac, for a discussion on how AI is transforming market research and planning.<\/p>\n

Panelists for the session included Brian Madden, futurist at Citrix; Steve Bevilacqua, principal consultant, Cella by Randstad Digital; and Katie Templin, chief experience officer, Qualified Digital.<\/p>\n

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MarTech Conference November: Now On-Demand<\/h2>\n

\n You can catch all of the insights from November MarTech Conference on-demand. From Scott Brinker\u2019s keynote on AI agents to six panel discussions on AI agents and marketing \u2014 all for free.\n <\/p>\n<\/div>\n

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From data overload to signal clarity<\/h2>\n

Marketers no longer struggle to find data \u2014 they struggle to make sense of it. The panelists agreed that AI\u2019s real value isn\u2019t in collecting more<\/em>, but in uncovering better<\/em> insights faster and more efficiently.<\/p>\n

1. Comparative analysis, done right<\/h3>\n

Templin uses tools like ChatGPT to perform quick competitor scans and directional analysis. \u201cIt\u2019s great for seeing how competitors are positioned in the market,\u201d she said. \u201cBut I always verify the sources. I never rely on AI alone.\u201d<\/p>\n

She emphasized the importance of understanding where data comes from and using AI only as a guide to where deeper research is needed.<\/p>\n

2. The \u201cdeep research\u201d mindset<\/h3>\n

Bevilacqua recommended activating \u201cdeep research\u201d or \u201csmart analysis\u201d modes in AI tools when doing market scans. His process is two-tiered: a broad pass in GPT or Copilot, followed by deeper dives using niche tools like Speak AI for call analysis or YouScan for social monitoring.<\/p>\n

\u201cDon\u2019t forget the data you already have,\u201d he added. \u201cBefore you chase new inputs, dig into your CRM, your customer calls, your social feedback \u2014 it\u2019s all right there.\u201d<\/p>\n

3. Synthetic focus groups<\/h3>\n

Madden treats AI as a stand-in for audience testing. \u201cIt\u2019s like having a million-person focus group that doesn\u2019t need snacks,\u201d he joked. By assigning LLMs roles like \u201cCIO at a SaaS company,\u201d he tests messaging and gathers multiple reactions with just a few refreshes.<\/p>\n

\u201cIt\u2019s not perfect,\u201d he noted, \u201cbut it\u2019s fast, directional, and often surprisingly human.\u201d<\/p>\n

Turning unstructured data into usable insight<\/h2>\n

AI\u2019s ability to handle unstructured data \u2014 audio transcripts, open-text surveys, social posts \u2014 was a recurring theme.<\/p>\n

Bevilacqua highlighted tools like Brandwatch for visual social listening and Dovetail for qualitative coding. \u201cWe can now surface pain points or themes in hours instead of weeks,\u201d he said.<\/p>\n

Templin\u2019s agency uses a private, fine-tuned AI system for proprietary data. \u201cWe combine large and small models, depending on speed and cost,\u201d she said. \u201cBut we always keep humans in the loop to vet the outputs.\u201d<\/p>\n

Gathering customer and competitor data safely<\/h2>\n

Ferrari and Templin both stressed that data governance matters. When analyzing internal or client data, use private or sandboxed models to protect confidentiality.<\/p>\n

Ferrari also mentioned using simple tools like web scrapers to get an external pulse on how a brand is perceived online \u2014 a low-cost way to complement internal datasets.<\/p>\n

For competitive research, Madden shared a clever twist: \u201cI feed competitors\u2019 blogs, press releases and videos into AI and tell it, \u2018You\u2019re a product strategist at this company \u2014 what\u2019s your next move?\u2019 It\u2019s like opening their playbook.\u201d<\/p>\n

Bevilacqua added that real-time monitoring tools such as Visualping can alert marketers to competitor pricing or messaging changes as they happen.<\/p>\n

Campaign execution at AI speed<\/h2>\n

AI\u2019s impact on campaign design is mostly about velocity and adaptability.<\/p>\n

Templin described how AI helps her team pivot based on live data. \u201cWe can analyze campaign sentiment and behavior changes in real time,\u201d she said. \u201cIf something\u2019s trending negatively, we trigger human outreach or shift the message immediately.\u201d<\/p>\n

She also uses AI to automate \u201cnext-best action\u201d logic \u2014 deciding when a prospect should move to sales or another nurture path. The result: higher engagement and better retention.<\/p>\n

Using AI without losing your critical eye<\/h3>\n

The panel agreed: AI is powerful but can be overly agreeable. \u201cIt\u2019s like a cheerleader \u2014 it always tells you you\u2019re brilliant,\u201d Ferrari joked. Bevilacqua warned against \u201cAI psychosis,\u201d the trap of believing your model\u2019s flattery.<\/p>\n

Instead, he suggested asking why an idea might fail<\/em> or requesting pros and cons to balance optimism. Templin added, \u201cAlways check the sources. AI will invent citations if it has to.\u201d<\/p>\n

Madden pointed out that bias is less risky when you use AI for brainstorming, not for final decisions: \u201cIt\u2019s another input \u2014 not the final authority.\u201d<\/p>\n

Dig deeper: How to get genAI to say it doesn\u2019t know<\/a><\/em><\/strong><\/p>\n

Smarter prompting, cleaner context<\/h2>\n

When sessions get long, Madden advises resetting context: \u201cAsk the model to summarize the conversation for itself, then start fresh.\u201d<\/p>\n

He also previewed what\u2019s next: longer context windows and \u201cpersistent memory\u201d in upcoming GPT releases \u2014 features that will make sustained analysis easier.<\/p>\n

Tools worth exploring<\/h2>\n

Throughout the session, panelists mentioned several go-to AI platforms:<\/p>\n