IGNITE leverages AI to enhance market research by accelerating insights, uncovering hidden insights, and enabling more confident decisions
AI Enhancements
At IGNITE, insight has always been at the core of how we help brands grow. As data sources become more complex and decision timelines continue to shrink, AI-powered tools offer a powerful opportunity to enhance (not replace) human-led market research. When applied thoughtfully, AI can accelerate analysis, uncover deeper patterns across qualitative and quantitative data, and elevate how insights are delivered.
AI Strategic Insights
By integrating AI-enabled tools into research, IGNITE can streamline data processing, identify emerging themes faster, and enhance visual storytelling. AI strengthens our ability to deliver clearer, faster, and more impactful insights that drive confident decision-making.
Enhance Insights with AI Driven Competitive Analysis
An AI driven competitive analysis evaluates category data across reviews, social, ads, claims, and brand content to strengthen market research programs by making them more focused, more efficient, and more strategic before, during, or after data is collected.
Creates smarter research focus before fielding: how brands are actually perceived in the category, which attributes are overused vs under-owned, where true differentiation or whitespace may exist
Improves survey & discussion guide design: competitive themes become attributes, claims, or statements in quant, emerging language can be used in qual stimulus and probes, redundant or less important measures can be eliminated from the research phase
Strengthens insight generation: links consumer attitudes to real-world brand behavior, flags inconsistencies between what brands claim and what consumers believe, identifies opportunities competitors are not effectively owning
Enables more confident strategic recommendations: supports positioning and messaging decisions, prioritizes opportunities with lower competitive risk, provides confidence to decisions and strategy
The Power of Natural Language Processing (NLP)
IGNITE uses NLP to deepen our understanding of consumers by unlocking the full value of unstructured feedback, such as open-ended survey responses, IDIs, and social media conversations. NLP allows us to identify patterns, sentiment, and emotional drivers in how people naturally express their thoughts, helping surface insights that go beyond what traditional metrics alone can reveal.
By combining NLP with our qualitative and quantitative expertise, we transform large volumes of language into clear, actionable insight. This approach accelerates discovery, enhances consistency, and ensures our recommendations are grounded in real respondent voice, so you can make confident, insight-driven brand decisions.
Case Study: Leveraging NLP to evaluate verbatims to better understand why men buy the same brand across men’s grooming products
Key insight: Men consolidate grooming brands to reduce risk, effort, and inconsistency.
The 5 drivers of cross-category brand loyalty
1. TRUST
One positive experience creates confidence across the brand
Lowers perceived risk of trying adjacent products
“If it worked once, it’ll work again”
2. PERFORMANCE
Products reliably “get the job done”
Functional results outweigh novelty
“It works — that’s enough”
3. FAMILIARITY
Routine and repetition drive default behavior
Switching feels unnecessary and risky
“I’m used to it”
4. CONSISTENCY
Predictable quality, results, and scent across products
Belief that products are designed to work together
“I know what to expect”
5. SIMPLICITY
Fewer decisions, faster shopping
Price validates staying loyal
“Easy, affordable, no thinking required”
What this means for men’s grooming brands
Win with one hero product, then extend trust across the routine
Maintain scent and performance cohesion across categories
Position portfolios as bundles, not individual SKUs
Case Study: Leveraging AI to compare survey results to current market reality
At IGNITE, we use AI to move beyond what consumers say and understand how insights show up in the real world. By combining primary survey data with AI driven analysis of current market data, such as brand messaging, product portfolios, pricing, reviews, and digital presence, we rapidly compare stated consumer needs to what brands are actually delivering today.
AI allows us to scan and structure large volumes of data, identify patterns and gaps, and benchmark survey findings against competitive and category realities in real time. This ensures our insights are not only statistically sound, but also grounded in the current marketplace, highlighting how brands are aligned or leaving growth opportunities untapped.
The results provide actionable guidance leading to clearer direction and optimization strategy.
What are the strategic changes?
Product X was designed to win through focused hero products and defined grooming segments, but has evolved into a broader, lifestyle-led grooming ecosystem.
Where the strategy has shifted?
From study results…
Segment-driven targeting (core 25–35 high-level groomers)
Hero products as growth engines (shampoo, conditioner, styling)
Functional, performance-led brand building
Premium positioning anchored in science and “natural” white space
To real time realities…
Broader male grooming audience
Full portfolio + routine-based bundles
Lifestyle, ingredient-forward storytelling
Premium and accessible pricing via kits and value bundles
What’s working?
Strong benefit-led messaging (clean, natural, modern)
Compelling DTC + national retail footprint
Bundling reinforces daily grooming routines
Clear premium quality perception without price barrier
Where does opportunity remain?
Hero products are under-leveraged as entry points
Target grooming intensity is diluted
Science/technology differentiation is not fully owned
“Natural” positioning is present but not yet defensible
What’s the next move?
Reconnect focused hero-product credibility by:
Using hero SKUs as trial and acquisition gateways
Layering science + performance proof into benefit-led messaging
Re-introduce grooming intensity segmentation without narrowing reach
Conclusion
Product X doesn’t need a new strategy, it just needs sharper focus.