Glimpse vs User Intuition: Trend Data vs Primary Shopper Voice

Glimpse sits in the trend-spotting category. The product analyzes search query trends, social signal velocity, and aggregated web data to surface emerging consumer interests — what categories, ingredients, product attributes, or behaviors are rising, plateauing, or declining across digital signals. For category teams tracking early movement in beverage flavors, beauty ingredients, or health and wellness behaviors, Glimpse is an early-warning tool for what might matter next.

User Intuition is a primary research platform. Rather than inferring consumer interest from search and social signals, User Intuition talks to actual shoppers — 30+ minute AI-moderated voice and video interviews with 5-7 level laddering, conducted with either your own customers or a 4M+ vetted shopper panel. Every interview produces verbatim quotes, full path-to-purchase reconstruction, and ontology-tagged insights that feed a compounding Intelligence Hub.

The platforms are not substitutes — they sit at different stages of the shopper research workflow. Glimpse answers "what trends are rising right now?" User Intuition answers "for the specific shopper segments we care about, what do they actually say, why does it matter, and what should we do about it?" Most sophisticated shopper marketing teams use secondary trend data and primary shopper research together; this comparison clarifies where each belongs.

Glimpse's data is aggregated and secondary by design. A trend score on Glimpse reflects the velocity of search queries or social mentions, not the reasoning of any individual shopper. This is appropriate for what Glimpse does — early signal detection across categories — but it means the evidence is correlational and descriptive. You know "this is rising." You do not know "this specific shopper segment is buying it because X, shifting away from Y, willing to pay Z at retail."

User Intuition's evidence is primary and causal. Every insight in the Intelligence Hub traces back to a specific shopper who said a specific thing in a 30+ minute conversation. A claim like "health-conscious grocery shoppers are switching to private label in the condiments aisle because they trust the retailer more than the legacy brand" is backed by the actual shoppers who said it, with full transcripts available and context preserved. For retail sell-in decks, category reviews, and shopper marketing readouts, the difference between "trend score rising" and "here are 47 shoppers explaining exactly why" is substantial.

The right framing: Glimpse gives you a heatmap. User Intuition gives you the 200 shoppers inside the heatmap explaining themselves in their own words.

In a typical retailer category team or CPG shopper marketing workflow, trend-spotting happens first. A tool like Glimpse surfaces that, for example, search volume for a specific beverage ingredient has risen 40% over six months in a target market. That signal triggers a question: does this matter for our category, which shopper segments are driving it, would it change our shelf set, and should we adjust assortment?

User Intuition answers those questions. A 200-shopper study fielded in 48-72 hours, recruited from the retailer's loyalty list plus a matched panel sample, with the AI moderator probing the last three category purchases and any awareness of the rising ingredient. The output is verbatim quotes tagged by shopper segment, emotional driver, and decision stage. Category teams get evidence to support assortment decisions. Shopper marketing teams get copy that matches how real shoppers talk. Retail sell-in teams get a decks-ready evidence base traceable back to shopper voice.

The handoff between secondary trend data and primary shopper research is where most shopper marketing work actually gets done. Neither platform replaces the other. Glimpse identifies what to investigate; User Intuition produces the shopper evidence that answers it.

Glimpse's SaaS subscription model gives continuous access to trend intelligence across the full dataset. Teams pay a recurring fee for dashboard access, trend monitoring, and alerting. This is the right pricing model for a tool that is used continuously for early signal detection — cost stays flat while usage scales.

User Intuition is priced per interview because primary research costs scale with sample. The Pro plan is $999/month and includes 50 credits at $20 per audio interview (chat $10, video $40), with extra credits at the same per-credit rate. Starter is $0/month with 3 free interviews and no card required. Studies start from $200 for small samples. For a retailer category team running a 200-shopper path-to-purchase study, the all-in cost is predictable and dramatically cheaper than traditional qualitative agency engagements.

Because the two platforms sit at different workflow stages, the pricing models are not directly comparable. Teams running ongoing trend monitoring plus quarterly shopper deep-dives typically budget for both — a SaaS subscription for secondary trend intelligence, plus per-study primary research budget for the shopper validation work.

Category decisions, shelf resets, assortment changes, private label strategy, retail sell-in meetings — these require evidence that holds up when challenged. A retailer category manager defending a shelf reset to the VP of Merchandising cannot rely on a trend score from secondary data. The question will be "show me the shoppers who told us this." Same for a CPG shopper marketing lead bringing a new item to a retailer buyer meeting, or a private label team arguing for expansion against a legacy brand.

User Intuition was built for this evidence requirement. The Intelligence Hub is queryable by shopper segment, decision stage, emotional driver, and competitive reference. Every claim traces to a specific shopper. Retail sell-in decks built on User Intuition evidence carry direct shopper voice — quotes tagged by store type, basket composition, and purchase frequency. Category reviews cite shopper reasoning, not trend inference. Shelf decisions cite what shoppers actually do at the shelf, in their own words.

Glimpse's role is upstream and essential. It flags what deserves investigation. But the investigation itself — the evidence that supports category, shelf, and retail decisions — happens in primary shopper research. User Intuition is the specialist for that work, with $20/interview economics and 48-72 hour fielding that make it feasible to run shopper research continuously rather than once a quarter.

Glimpse's outputs match its data type — trend dashboards, signal reports, data exports for secondary analysis. These are the right outputs for a trend intelligence tool. Teams consume them to understand the signal landscape and decide where to focus primary research.

User Intuition's outputs match primary research depth. Every conversation produces a full transcript, ontology-tagged insights, emotional-driver categorization, and evidence-traced quote access. The Intelligence Hub is queryable by shopper segment, decision stage, or category dimension, with cross-study pattern recognition improving as more studies run. Findings flow through your tech stack via MCP server integrations with OpenAI and Claude, CRM sync with HubSpot, Salesforce, and Pipedrive, Zapier workflows for theme alerts, and Stripe and Shopify integrations for purchase-history-informed recruitment.

For shopper marketing teams, the integrations matter. Shopper insights are most valuable when they flow into merchandising planning tools, campaign platforms, and AI assistants that surface relevant evidence at the moment of decision. User Intuition is built for distribution through the modern tech stack. Glimpse operates as a focused trend intelligence product with its own dashboard interface.