Trending-product buy list · TikTok + Instagram × Hotspex emotion
A buy list to compete with Showcase. 500 socially-trending impulse products — gadgets, novelties, problem-solvers — each scored two ways: trend momentum (velocity and acceleration, not lagging volume) and the Hotspex emotional connection that actually drives the unplanned purchase. Blended into one Idea Score.
The ranked buy list · scored live in your browser
Idea Score = 0.45 × trend momentum + 0.55 × emotional connection. Emotion is weighted higher because for impulse retail the emotional trigger is what converts the unplanned buy — trend momentum just gets the product discovered. Filter, search, and re-sort below.
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| # | Product | Category | Lead | Trend | Hotspex zone · core emotions · right-space | Emotion | Idea | Est. ON demand /yr | Buy rationale |
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Trend momentum: per-platform velocity (Δ engagement) + acceleration (Δ velocity) across three windows, converged across TikTok + Instagram, normalised 0-100. Emotional connection: each product placed on the Hotspex Emotion Map, scored 0-100 on how strongly and distinctively it fires its dominant driver. Same engine as the Python build, ported to JS.
Est. ON demand: a MODELED annual unit estimate (low–high band), not measured sales. Method: ~6.2M Ontario households (3.6M pet-owning) × category penetration × trend-heat multiplier (0.4–1.8×) × emotional-conversion multiplier (0.75–1.25×). Treat as directional sizing to validate against real search and point-of-sale data before committing buy quantities.
Hotspex emotion map · the predictive layer
Trend tells you what's moving. Emotion tells you what will sell and repeat. Every product is placed on the canonical Hotspex Personality Wheel — eight emotional zones, each with its own core emotions — and scored on the connection it owns. Below is the actual wheel for the whole buy list, then where it's crowded and where the white space is.
Architecture
TikTok Research API + Instagram Graph API, decoupled behind a queue. Rate-limit backoff, token refresh, sponsored-post and boycott-sentiment filtering before anything is scored.
Per-product velocity and acceleration across three windows, with a smoothed denominator and a cross-platform convergence score that penalises single-platform flukes.
Each product placed on the Hotspex Emotion Map, scored on the dominant driver it fires — the predictive layer no trend tool has. This is what separates a fad from a repeat-purchase.
Trend momentum and emotional connection blend into one ranked buy list, weighted toward emotion because that's what converts the impulse purchase.
The business case
Anyone can buy a trend dashboard. They all surface the same viral products. The edge is the emotional layer — knowing why a product will convert, not just that it's trending.
Showcase merchandises on "what's hot." That's a trend signal everyone sees. A buy list ranked on trend and emotional pull lets you out-select them on the products that actually repeat-purchase, not just the ones that spike.
Trend tools (Spate, Trendalytics, Exploding Topics) see the same viral gadgets. Only the Hotspex Emotion Map tells you which driver a product owns and whether that driver is over-supplied — turning a buy list into a portfolio strategy.
Sell the ranked buy list as a quarterly merchandising service ($25–75K) — highest margin, plays to interpretation not raw data. An always-on API feed ($80–150K/yr) is stickier but exposes the proxy / data-broker margin trap.
Durable value sits in the emotional interpretation, then the product ontology, then the trend math. Sell which products will convert and why, not a feed of what's trending. That's the moat Showcase can't copy.