🔬 Intelligent Market Research Tool

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📊 Research Dashboard Overview

Total Responses
0
Surveys Completed
0
Interviews Done
0
Active Invites
0

📊 Response Breakdown

Brand Awareness 0
NPS Survey 0
Purchase Intent 0
Interviews 0
Focus Groups 0
Sentiment Analysis 0

💡 Recent Insights

🚀 Decision Board (Outcome & ROI)

Immediate next moves, ROI focus, and confidence-driven guidance

High-Value Opportunities
0
Prioritized by impact / effort
At-Risk Accounts
0
Sentiment + NPS signals
Top Segment Focus
—
Ranked by intent & upside
Estimated Profit Uplift (model-based)
0
Profit estimate from signals (sales + rental + maintenance + retention)

🎯 Segment Priorities & ROI

📈 Impact vs Effort

Bubble size = expected uplift

🧭 Next Moves (Auto-suggested)

    🔍 Hidden Truths & Signals

    🛡️ Churn Watchlist

      🚀 Expansion Watchlist

        📉 Churn vs Expansion

        Left = churn risk count, Right = expansion opportunities

        💬 Sentiment Trend

        Recent sentiment mix across all responses

        💰 Revenue Mix Uplift (Sales vs Rental vs Maintenance)

        Stacked uplift estimate by segment. Tuned to support rental + maintenance growth.

        🏁 Competitor / Low-Cost Import Signals

        Flags mentions of cheap imports / Chinese machinery / competitor pressure.

        🧾 Evidence Snippets — Risks

        ✅ Evidence Snippets — Opportunities

        🗺️ Segment Playbooks (Data-driven)

        Copper=growth, Diamond=defend/retain, Construction=develop. Moves adapt as signals change.

        🚨 Alerts (Root Cause → Next Move)

        These are evidence-led alerts (recency-weighted). Each alert includes the likely root cause and a recommended next move.

        🧩 Segment Issues & Opportunities (Top 3 each)

        Each segment card shows the strongest issues/opportunities, with impact/effort, time-to-value, urgency, confidence, and evidence.

        🧠 Theme Explorer (Clustering)

        Themes are grouped from verbatims + survey text. Recency-weighted.

        🧩 Top Emerging Themes

        🧾 Vocabulary Coverage (Signal Strength)

        Coverage Score
        0%
        How well responses cover key decision drivers
        Strong Themes
        0
        Themes with strong evidence
        Gaps to Probe
        0
        Themes needing more verbatims

        📌 Coverage Mix

        Donut shows which decision drivers dominate current evidence.

        🎯 Next Questions to Ask (Based on Gaps)

          🧷 What We’re Hearing Most

            ❓ Strategic Research Questions Framework

            Four-level framework covering Market, Competitive, Customer, and Company Capability questions

            🧭 Recommended invite types per level (Which link gets sent to whom)

            These Level 1–4 questions are the strategy guide. To collect evidence, use the invite links below (Admin → Survey Management → Create Invite Link).

            Level 1 — Market & Industry

            • Who answers: Admin/research team (desk research) + a few senior operators for validation
            • Send links: Brand Awareness (for market perception) + Interviews (for context)
            • Also: Use Focus Groups when you need consensus on trends/assumptions

            Level 2 — Competitive

            • Who answers: Buyers/prospects + internal sales team
            • Send links: Competitor Snapshot (Buyer/Prospect) + Win/Loss (Internal Sales)
            • Optional: Sentiment / Communication Log for competitor mentions in calls/emails/tickets

            Level 3 — Customer & Demand

            • Who answers: Customers + high-intent prospects (by segment)
            • Send links: NPS Survey + Purchase Intent + Interviews
            • Also: Focus Groups to test packages (rental + maintenance + financing) and pricing ranges

            Level 4 — Company Capability

            • Who answers: Internal teams (sales, service, parts, finance) + select customers for service expectations
            • Send links: Win/Loss (Internal Sales) + Sentiment / Communication Log + Interviews
            • Outcome: Capability roadmap (what to build first to win on value + profit)
            Tip: Create separate invite links per segment (Copper/Diamond/Construction) by using a clear custom title and sending to the right respondent list.

            Level 1: Market & Industry

            🔍 Diagnostic: Root Causes

            • Why is mining equipment market consolidating around 2 vendors?
              Explain
              We want the main forces causing consolidation (procurement rules, risk aversion, service coverage, financing, supply chain, brand trust). Ask for examples of decisions that favored “safe” vendors.
            • What caused Debswana's capex reduction and recovery timeline?
              Explain
              This identifies the market shock and when spending returns. Ask what changed (commodity prices, regulations, budgets, operational priorities) and what would trigger new equipment spend again.
            • Why is copper mining projected to expand 35% while diamond contracts?
              Explain
              We’re separating growth drivers from decline drivers. Ask: “What projects are driving copper growth?” and “What constraints are limiting diamond expansion?”

            📊 Descriptive: Market Patterns

            • What is TAM size by segment (diamond, copper, construction)?
              Explain
              This measures the “size of the prize” per segment. Ask for ranges and assumptions (fleet sizes, replacement cycles, project pipelines) so the estimate is defensible.
            • How is customer demand shifting (rental vs purchase, features)?
              Explain
              We want evidence of a demand shift and why. Ask what customers are choosing more often (rent/lease) and what they’re optimizing for (cashflow, flexibility, uptime, ESG, automation).
            • What are competitive market share dynamics?
              Explain
              This captures who is gaining/losing share and where. Ask: “Which segment is changing fastest?” and “What’s driving it—price, service, availability, financing?”

            🔮 Predictive: Forecasting

            • Equipment spending forecast for 12-24 months by segment?
              Explain
              We’re forecasting demand timing. Ask for expected budgets, replacement cycles, and key project start dates, by segment.
            • Technology adoption impact (automation, electric)?
              Explain
              This tells us if tech is changing purchase criteria (safer, lower TCO, ESG compliance). Ask which features are becoming “must-haves” and how soon.
            • Economic scenarios impacting market size?
              Explain
              We map best/base/worst-case drivers (commodity prices, regulations, financing rates, project delays). Ask what would change spending up or down.

            ✅ Prescriptive: Recommendations

            • Which segments to prioritize for growth investment?
              Explain
              This is about focusing resources where profit and momentum are highest. Ask what segments have budget, urgency, and switching willingness—then rank them.
            • What product/service innovations capture demand?
              Explain
              We want the most valuable “next offers” (rental packages, maintenance contracts, uptime guarantees, refurb programs). Ask what would remove pain fastest and what customers would pay for.
            • How to position against consolidation trend?
              Explain
              We decide how to win when buyers prefer “safe” vendors. Ask what proof reduces risk (references, SLAs, warranty, TCO tools) and what claims buyers trust.

            Level 2: Competitive

            🔍 Diagnostic: Root Causes

            • Why do customers choose a competitor even when service quality is weaker?
              Explain
              We’re trying to find the real reason customers stay with a competitor (price, habit, financing terms, brand trust, availability, fear of change). Ask for a real example and what would have changed the decision.
            • What is the competitor’s “default win” advantage in deals (price, perception, availability, financing, procurement policy)?
              Explain
              This identifies why they win without trying. Ask clients to describe the last deal they won and the deciding factor (in the buyer’s words).
            • Where exactly do we lose: specification, procurement rules, lead time, uptime history, credit/terms, after-sales coverage?
              Explain
              This helps you pinpoint the step where deals collapse. Ask for the “moment of loss” and what proof/offer would have saved it.

            📊 Descriptive: What’s happening (patterns)

            • Which competitor offers are customers comparing most often (buy vs rent vs lease, warranties, service plans)?
              Explain
              You want the buyer’s comparison set. Ask what options were on the table and what each option included (terms, maintenance, uptime guarantees).
            • What is the buyer’s language for each competitor (e.g., “cheap but risky”, “safe choice”, “best support”)?
              Explain
              This gives you messaging/positioning data. Ask: “How would you describe them in one sentence?” and “Why?”
            • What complaints are most frequent about competitors (downtime, parts, reliability, hidden costs)?
              Explain
              We want competitor weaknesses customers already feel. Ask for a specific incident and the cost/impact it caused.

            🔮 Predictive: What will happen next?

            • How will “cheap imports” change decisions in the next 6–12 months (more rentals, more breakdowns, more maintenance demand)?
              Explain
              This forecasts the market’s direction. Ask: “If you buy cheaper equipment, what do you expect will happen to downtime and service needs?”
            • Which competitor moves would most threaten us (price cuts, rental fleet expansion, service coverage, financing)?
              Explain
              This identifies likely threats. Ask: “What would make you switch away from us quickly?”
            • Which customers are most likely to switch in the next 90 days—and why?
              Explain
              We’re looking for early warning indicators (cashflow constraints, new projects, service dissatisfaction). Ask for signals they’re seeing internally.

            ✅ Prescriptive: What should we do?

            • What “proof pack” would win against competitors (TCO calculator, uptime SLA, warranty, references, demo)?
              Explain
              Ask clients what evidence they trust: numbers, references, trials, uptime guarantees. This becomes your sales/marketing asset plan.
            • What bundle beats cheap imports: rental + maintenance + response time guarantees + refurbishment options?
              Explain
              We’re designing an offer that wins on value—not just price. Ask: “What package makes the premium worth it?”
            • What competitor-specific plays should we run (e.g., “take-back” offers, financing bridge, service recovery)?
              Explain
              Turn insights into action. Ask what would convince them to switch and how fast it could happen.

            Level 3: Customer & Demand

            🔍 Diagnostic: Root Causes

            • What is the real blocker to buying (cashflow, CAPEX approvals, project uncertainty, procurement rules)?
              Explain
              We’re identifying why customers delay purchases. Ask: “What specifically stops you from buying today?” and “What would remove that barrier?”
            • Why are customers shifting to rental/lease—what risk are they avoiding?
              Explain
              This finds the reason behind rental preference: uncertainty, maintenance risk, flexibility, cashflow. Ask for a real situation where rental saved them.
            • What causes downtime and maintenance cost pain (parts, skill gaps, response time, equipment age, poor fit)?
              Explain
              We want the drivers of total cost of ownership. Ask: “What was the last expensive breakdown and what did it cost you?”

            📊 Descriptive: What customers do (behaviors)

            • What is the typical buying journey (who initiates, who approves, who blocks)?
              Explain
              Map the decision chain: operations, finance, procurement, GM. Ask: “Who must say yes?” and “Who can veto?”
            • What are the top 5 decision drivers in the customer’s own words (cost, ROI, uptime, terms, convenience)?
              Explain
              This is your “why people buy” list. Ask them to rank the drivers and give a short story for each.
            • What budgets exist for rental monthly (BWP) and maintenance annual (BWP), and how are they decided?
              Explain
              This helps you price packages. Ask: “What range feels acceptable and why?” and “What would make you pay more?”

            🔮 Predictive: Demand outlook

            • What will increase demand next quarter (new projects, expansion, replacements, regulations)?
              Explain
              Ask what events will create purchasing or rental demand and when those events happen.
            • What will push customers further toward rentals (rates, cashflow pressure, uncertainty) or back to buying?
              Explain
              We’re identifying the tipping point. Ask: “At what price/terms would you buy instead of rent?”
            • What are early warning signals of churn or switching (service incidents, pricing, procurement changes)?
              Explain
              These signals become your monitoring and alert rules. Ask: “What happens right before you switch vendors?”

            ✅ Prescriptive: What should we offer?

            • What rental packages would be “no-brainers” (duration, rate, swap unit policy, uptime SLA)?
              Explain
              Design the rental product. Ask for required features and the minimum acceptable service response time.
            • What maintenance contract structure is most attractive (preventative, parts included, response guarantees)?
              Explain
              Design recurring revenue. Ask what the contract must include, what exclusions are acceptable, and what success looks like.
            • What messaging wins: “cheap now” vs “durable + uptime + lower TCO”—what proof do they trust?
              Explain
              This informs positioning. Ask what evidence convinces them: downtime cost, warranty history, peer references, trials.

            Level 4: Company Capability

            🔍 Diagnostic: Capability gaps

            • Where do we fail operationally (parts availability, response time, technician capacity, coverage)?
              Explain
              We’re identifying internal bottlenecks that cause customer pain. Ask: “Where do we miss SLAs and why?”
            • Which capabilities are weakest against cheap imports (pricing flexibility, rental fleet scale, service reach)?
              Explain
              This highlights what needs strengthening to compete. Focus on gaps that directly affect customer buying decisions.
            • What prevents us from scaling rental + maintenance as recurring profit (systems, CRM, dispatch, inventory)?
              Explain
              We’re checking readiness for the new model: rental operations and maintenance delivery need systems and discipline.

            📊 Descriptive: Current performance

            • What is current performance by segment (win rate, churn risk, service response times, contract attach rates)?
              Explain
              We need a baseline to improve. Ask for current metrics (even rough): response time, uptime, renewal rates, attach rates.
            • Which offers are selling best today (rental, maintenance contracts, buy + warranty bundles)?
              Explain
              This shows what’s already working. Ask what customers say when they buy and what objections still remain.
            • What are the top recurring reasons for lost deals (in the team’s words)?
              Explain
              This turns internal experience into structured data. Ask for examples and the exact competitor offer that won.

            🔮 Predictive: Readiness & scaling

            • If rental demand doubles, what breaks first (fleet, dispatch, maintenance capacity, parts, financing)?
              Explain
              We’re stress-testing the operating model. Identify the “first bottleneck” and what investment removes it.
            • What capabilities must improve in 90 days vs 6–12 months to protect profit?
              Explain
              Separate quick wins from longer build. Ask what can be fixed quickly and what requires structural investment.
            • What competitor moves are likely and how prepared are we to respond?
              Explain
              Create a response plan. Ask what price/service moves competitors may make and how we’d counter.

            ✅ Prescriptive: Capability roadmap

            • What should we build first to win (rental packages, service SLAs, refurbishment, financing partnerships)?
              Explain
              This becomes the roadmap. Prioritize initiatives with fastest time-to-value and strongest profit impact.
            • What systems/tools are needed (CRM, dispatch, inventory forecasting, service analytics)?
              Explain
              These enable scaling. Ask what data is missing today and what automation would reduce downtime.
            • What partnerships accelerate growth (warranty providers, finance partners, OEM alliances)?
              Explain
              Partners can speed up financing and guarantee programs. Ask which partnerships customers trust most.

            📋 Research Methodologies Deployed

            Blending historic research methods with modern analytics capabilities

            How to use this section

            The percentages are a live data-readiness / completion indicator (responses collected vs target) for each methodology. As you collect more surveys/interviews/focus groups, these bars update automatically—so you can see what to run next to strengthen confidence.

            Tip: If a method is low, create an invite link in Survey Management and send it to the right audience (buyers/prospects/internal).

            🎯 Starch Method (1920s)

            Brand Recall & Advertising Effectiveness

            Unaided/aided brand awareness surveys with 150+ mining decision-makers. Track message recall and positioning clarity.

            —

            📊 Gallup Method (1930s)

            Predictive Polling & Market Forecasting

            Time series analysis of equipment sales, economic indicators, and project timelines to forecast demand 12-24 months ahead.

            —

            🧠 Dichter Method (1950s)

            Motivational Research & Depth Psychology

            In-depth ethnographic interviews (30+) exploring subconscious motivations, fears, and unmet psychological needs.

            —

            📈 Green Method (1960s)

            Statistical Multivariate Modeling

            Regression analysis and conjoint analysis to quantify impact of each decision factor and customer segmentation.

            —

            💭 Howard & Fishbein (1960s)

            Multi-Attribute Attitude Analysis

            Integration of psychology, sociology, anthropology. Attitude modeling combining beliefs, emotions, and social factors.

            —

            👥 Focus Groups (1930s+)

            Qualitative Group Dynamics

            Structured group discussions with mining decision-makers to validate findings and understand peer influence effects.

            —

            💡 Unmet Needs Discovery

            Jobs-to-be-Done Analysis

            Identify what customers are trying to achieve and where existing solutions fall short. Design experience differentiation.

            —

            🌐 Global Information System

            Unilever Model - Centralized Intelligence

            Consolidated research repository accessible across regions. Regional intelligence hubs with centralized insights.

            —

            😊 Sentiment Analysis (AI)

            Real-Time Emotion & Tone Detection

            NLP-powered analysis of customer communications, social media, reviews for emotional intent and switching signals.

            —

            🏷️ Theme Extraction (AI)

            Pattern & Entity Recognition

            Automatic identification of key themes, entities, and relationship networks from unstructured data sources.

            —

            🔮 Predictive Modeling (ML)

            Behavior Forecasting & Churn Risk

            Machine learning models for customer churn prediction, purchase probability, market segment forecasting.

            —

            📡 Data Collection & Integration

            Comprehensive data sources and integration tracking

            Data Source Collection Method Frequency Status Insight Value
            Mining News & Industry Publications Web scraping, RSS feeds, manual curation Daily 90% Market trends, project announcements
            Social Media & LinkedIn API integration, keyword monitoring Real-time 80% Sentiment, industry discussions, competitor moves
            Customer Interviews & Ethnography Scheduled interviews, on-site visits Monthly 60% Deep motivations, unmet needs, decision processes
            Customer Surveys & Quantitative Online surveys, phone interviews Quarterly 70% Brand awareness, satisfaction, preferences
            Competitive Intelligence Website monitoring, price tracking, document analysis Monthly 75% Positioning, moves, vulnerabilities
            Internal Company Data CRM export, sales reports, service records Weekly 85% Sales performance, customer satisfaction, trends

            Regional Data Hubs

            🇧🇼 Botswana (Primary Hub)

            Focus: Diamond mining, copper expansion

            Major Clients: Debswana, Khoemacau, Sandfire
            Intelligence Lead: Country Manager

            🇿🇦 South Africa

            Focus: Regional equipment sourcing, remanufacturing

            Major Clients: Engineering firms, contractors
            Intelligence Lead: Regional Sales

            🇳🇦 Namibia

            Focus: Mining exploration, infrastructure

            Major Clients: Exploration companies
            Intelligence Lead: Territory Manager

            🇿🇲 Zambia & 🇿🇼 Zimbabwe

            Focus: Copper mining growth, recovery

            Major Clients: Mining operators
            Intelligence Lead: Regional Representatives

            📝 Survey Management

            Create New Invite Link

            🔗 Invite Links

            💡 Real-Time Insights Dashboard

            Auto-generated insights from collected survey and research data

            📊 Key Research Insights

            🎯 Copper Mining Growth

            Finding: Projected 35% CAGR expansion in copper mining segment

            Confidence: 90% | Source: Market analysis, project announcements

            Implication: Highest priority segment for growth investment

            📊 Service Differentiation

            Finding: 70% switching consideration reversed by 24/7 service experience

            Confidence: 88% | Source: Customer interviews, satisfaction surveys

            Implication: Service excellence is key competitive advantage

            👥 Brand Awareness Gap

            Finding: 45% vs Komatsu 78% brand awareness

            Confidence: 90% | Source: Brand awareness surveys

            Implication: Major opportunity for marketing investment

            💰 Unmet Need: Predictive Maintenance

            Finding: 78% of mining companies frustrated with reactive maintenance

            Confidence: 82% | Source: In-depth interviews, focus groups

            Implication: New service opportunity with premium pricing potential

            📈 Real-Time Analytics

            📄 Strategic Reports

            Executive Summary

            Key findings, confidence levels, strategic implications

            Market Analysis

            TAM sizing, competitive landscape, market drivers

            Customer Insights

            Segmentation, motivations, pain points, decision processes

            Strategic Recommendations

            Prioritized actions, expected impact, implementation timeline

            ⏱️ Research Execution Timeline

            Phased approach to comprehensive market research

            ⚙️ Configure Timeline Phases

            Set start and end dates for each phase. The timeline will automatically show status based on current date proximity to targets.

            🔌 Integration Connectors

            Connect external data sources to enrich your research insights

            🔒 Admin-Only Access: Integration API keys and configurations are stored securely and are only accessible through this admin dashboard. Public survey respondents cannot access or view any integration settings or data.

            Similarweb

            Website traffic, competitor analysis, market intelligence

            Not Configured

            SEMrush

            SEO, keyword research, competitor analysis

            Not Configured

            Ahrefs

            Backlink analysis, keyword research, content marketing

            Not Configured

            Owler

            Company intelligence, competitor tracking, news alerts

            Not Configured

            Earnest Analytics

            Consumer spending data, market trends

            Not Configured

            Google Analytics

            Website analytics, user behavior, conversion tracking

            Not Configured

            SurveyMonkey

            Survey data import, response management

            Not Configured

            Hootsuite

            Social media monitoring, sentiment analysis

            Not Configured

            Tableau

            Data visualization, advanced analytics

            Not Configured