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Connect the data
Combine consumer signals, product and portfolio data, sales history, market inputs, and business constraints.
ConsumerPortfolioSalesMarketConstraints
For CPG insights, innovation, brand & category teams
One AI workflow from market understanding to launch decisions
Simporter turns consumer, product, and market signals into decision-ready intelligence—so innovation teams can understand the market and consumers, create evidence-based concepts, and forecast launches in one connected workflow.
Trusted by CPG insights and category teams
The problem
CPG product decisions are fragmented from insight to launch
Consumer signals, product ideas, portfolio data, and launch forecasts are often managed in separate tools and spreadsheets. Teams lose context between stages, rely on inconsistent assumptions, and struggle to trace decisions back to the evidence behind them.
Fragmented consumer evidence
Social conversations, reviews, product data, research, and internal knowledge are analyzed separately, making it difficult to build one consistent view of the category.
Ideas disconnected from opportunity
Innovation teams generate ideas but struggle to connect each concept to a meaningful consumer need, portfolio gap, or white space.
Forecasts built on hidden assumptions
New products have little or no sales history, so teams rely on manually selected analogs, spreadsheets, and assumptions that are difficult to explain.
Context lost between teams
Evidence, ideas, and forecasts move across disconnected workflows, slowing collaboration and creating inconsistent versions of the truth.
Platform overview
Understand the market. Create the concept. Forecast the launch.
Three products, one workflow — connected by Colton, the AI agent that carries context across all three.
Insights
Millions of social posts, e-commerce reviews, and product descriptions for your category — cleaned, labeled against a custom ontology, and explorable through dashboards or by asking Colton.
Explore InsightsConcepts
Turn consumer needs, category trends, and your business constraints into structured new product concept ideas — each grounded in consumer evidence and ready to feed a forecasting scenario.
Explore ConceptsForecasting
Create, compare, and explain new product launch forecasts using your sales history, product master data, consumer insights from e-commerce and social data, and ML forecasting models.
Explore Forecasting
How It Works
One connected foundation across every product decision
Consumer, portfolio, sales, and market data are prepared once and used across Insights, Concepts, Forecasting, and Colton. Evidence, product definitions, and assumptions stay connected as teams move from opportunity discovery to launch planning.
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Structure the intelligence
Clean, enrich, and organize the data using category-specific topics, needs, attributes, brands, SKUs, markets, and time periods.
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Carry context forward
Move opportunities from Insights into Concepts and transfer selected concepts, attributes, and assumptions into Forecasting.
Insights
→
Concepts
→
Forecasting
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Explain the decision
Use Colton to explore evidence, compare alternatives, understand assumptions, and receive a recommended next step.
Recommended next step
Evaluate Concept A in Forecasting
Nothing gets lost between stages
Consumer evidence, concept rationale, scenario assumptions, and parameter sources remain connected throughout the workflow.
Colton AI Agent
Meet Colton, your AI partner across the product lifecycle
Colton connects Insights, Concepts, and Forecasting in one conversational workflow. Ask a business question, generate a concept, or build launch scenarios without losing context.
Knows your category
Understands your ontology, consumer signals, portfolio, and business dimensions.
Moves across products
Carries opportunities from Insights into Concepts and then into Forecasting.
Keeps the context
Remembers the project, constraints, assumptions, and previous decisions.
Explains the answer
Shows what was analyzed, what was assumed, and why it recommends a next step.
Every Colton response can include
What was analyzed
Key findings
Concept recommendation
Forecast scenarios
Source traceability
Recommended next step
Beyond social listening
From consumer signals to product decisions
Simporter goes beyond monitoring conversations. It connects category-specific consumer evidence with portfolio, sales, concept, and forecasting data to help CPG teams move from understanding the market to creating products and evaluating launches.
Built for CPG decision-making
Every category is configured with a tailored ontology covering topics, needs, pain points, benefits, attributes, claims, personas, occasions, brands, and products.
One connected intelligence foundation
Social posts, e-commerce reviews, images, videos, product data, portfolio structure, and sales signals are cleaned, enriched, and organized into one decision-ready data foundation.
Evidence that leads to action
Every insight can be traced to the underlying consumer evidence and carried into concept generation, scenario assumptions, and launch recommendations.
Who uses Simporter
Built for the teams shaping products from insight to launch
Simporter gives consumer insights, innovation, brand, commercial, forecasting, and leadership teams one connected workflow to understand category demand, create stronger concepts, and make more defensible launch decisions.
Consumer Insights
Turn consumer signals into decision-ready intelligence. Explore needs, pain points, personas, attributes, trends, sentiment, and white spaces with source-linked evidence and category-specific analysis.
Innovation & R&D
Move from opportunity to structured product concepts. Identify promising spaces, generate and refine evidence-based concepts, prioritize attributes and claims, and prepare stronger ideas for validation and forecasting.
Brand Management & Marketing
Shape products and positioning around real demand. Use consumer language, category signals, portfolio context, and competitive evidence to guide benefits, claims, messaging, formats, and launch positioning.
Revenue Growth & Commercial Planning
Pressure-test price, promotion, and distribution. Model how pricing, pack size, promotional support, customer reach, distribution, and cannibalization could affect launch revenue and volume.
Forecasting & Demand Planning
Build and compare transparent launch scenarios. Forecast products with limited or no direct history using sales data, comparable products, consumer demand signals, and clearly sourced assumptions.
Leadership & Finance
Make faster, more defensible investment decisions. Review opportunity evidence, concept rationale, scenario comparisons, forecast drivers, risks, and recommendations in one connected decision process.
FAQ
Frequently asked questions
What is the Simporter AI platform?
Simporter is a consumer and product intelligence platform for CPG teams. It connects category insights, evidence-based concept development, and new-product forecasting in one workflow—from understanding consumer demand to evaluating launch potential.
Which products are included?
The platform includes:
- Simporter Insights for category and consumer intelligence
- Simporter Concepts for evidence-based product concept development
- Simporter Forecasting for creating and comparing new-product launch scenarios
- Colton, the AI agent that works across all three products
The products can be used individually or together as one connected workflow.
How do Insights, Concepts, and Forecasting work together?
Insights identifies consumer needs, pain points, trends, attributes, and white spaces. Concepts turns those opportunities into structured product ideas with supporting evidence. Forecasting then evaluates the commercial potential of selected concepts using sales data, consumer demand signals, and transparent scenario assumptions.
What data does Simporter use?
Depending on the product and client scope, Simporter can combine:
- social media posts, comments, images, and videos
- e-commerce reviews, product descriptions, and product images
- category-specific communities and forums
- client product master and portfolio data
- historical sell-in and sell-out data
- market, seasonality, holiday, pricing, and distribution inputs
- business objectives, constraints, and project context
The data is cleaned, enriched, labeled, and structured for each category.
What can Colton do across the platform?
Colton can answer category questions, identify opportunities, generate and refine concepts, create launch scenarios, compare alternatives, and explain recommendations in plain language.
It keeps the project context across conversations and shows what data, evidence, and assumptions were used.
Can Simporter support products with no sales history?
Yes. Simporter Forecasting is designed for new products and innovations with limited or no direct sales history. It uses historical patterns from related products, portfolio and category data, consumer demand signals, and machine-learning models to create transparent launch scenarios.
Historical sales data is still required to train and calibrate the forecasting models.
How is Simporter different from social listening or generic AI tools?
Social listening primarily tracks conversation volume and sentiment. Generic AI tools usually answer from broad public knowledge.
Simporter uses category-specific ontologies, structured consumer and business data, product portfolio context, sales information, and forecasting methodology. Its outputs can be traced to the underlying evidence and carried forward into concepts and launch decisions.
Who is Simporter designed for?
Simporter supports the teams involved in product decisions across the CPG lifecycle, including:
- consumer insights
- innovation and R&D
- brand management and marketing
- revenue growth and commercial planning
- forecasting and demand planning
- finance and leadership
Each team works from the same connected evidence, concepts, assumptions, and scenarios.
Can the products be used separately?
Yes. Insights, Concepts, and Forecasting can each be deployed independently. Their value increases when connected, because consumer evidence, product definitions, assumptions, and project context can move between products without manual rework.
See it live
Tell us your category and target markets
We'll show you Simporter running on a category like yours — the ontology, the dashboards, and Colton answering real business questions.