Table of Contents
What Is Competitive Intelligence (CI)?
Competitive Intelligence is a systematic process for gathering and analyzing publicly-available information about an external business environment – competitors, customers, market trends, and macro factors – in order to inform decisions.
Key Features:
- Uses only publicly accessible information (web, reports, foot traffic, social media, etc.) – no secret or proprietary spying.
- Turns raw data into actionable insights.
- Supports both strategic and tactical decision-making: long-term planning and immediate business moves.
Why CI Matters – The Strategic Value
- Early Warning & Proactive Positioning: Detect market shifts, competitor moves, or consumer behavior changes ahead of time, enabling business adaptation before risks materialize or opportunities vanish.
- Data-Driven Decision Making: Moves choices from intuition to evidence, reducing risk, minimizing guesswork, and improving the odds of success.
- Competitive Benchmarking & Differentiation: By understanding what competitors are doing well (and where they struggle), businesses can carve out differentiators, whether through product selection, pricing, customer experience, or location strategy.
- Adaptive Responsiveness: When CI is embedded in ongoing operations (not as a one-time study), businesses maintain agility, responding proactively to market changes in near-real time rather than after they hit full force.
Types of Competitive Intelligence
Professionals commonly distinguish between two different types of competitive intelligence: Strategic intelligence and tactical intelligence.
| Type | Description | Typical Use Cases |
|---|---|---|
| Strategic Intelligence | Macro-level view of market dynamics: shifts in industry, emergent competitors, consumer behavior trends, regulatory or macroeconomic changes. | Long-term planning, positioning, investment decisions, expansion strategy. |
| Tactical Intelligence | Micro-level, near-term data: competitor store openings/closures, local demand shifts, pricing changes, consumer foot-traffic patterns. | Short-term decisions: store placement, marketing/promotions, assortment selection, pricing strategy. |
Sources & Methods for Gathering Competitive Intelligence
- Public data & documents: websites, press releases, filings, news articles, reviews, social media, market reports.
- On-the-ground observations: field visits and customer or shopper surveys.
- Third-party data sources: location analytics and demographic/psychographic overlays.
- Hybrid approach: combining multiple data sources (public + observational + analytics) tends to produce richer, more accurate insight.
Analytical Frameworks & Converting Data into Insight
Frameworks help structure thinking and draw actionable conclusions from the gathered data. They include:
- SWOT Analysis (Strengths, Weaknesses, Opportunities, Threats): Compare internal capabilities vs external environment; identify gaps and competitive edges.
- PESTLE Analysis (Political, Economic, Social, Technological, Legal, Environmental): Useful for assessing macro-environmental factors that could impact business over time.
- Porter’s Five Forces: Helps evaluate the industry’s structure in terms of barriers to entry, competitors, suppliers, customers, and substitute products.
SWOT Analysis in Practice: Using Competitive Intelligence to Guide Retail Strategy
This section walks through how a retailer can apply competitive intelligence in a real-world scenario using a SWOT framework powered by location analytics. The example centers on a 50-unit sporting goods chain evaluating expansion opportunities.
Strengths:
- Store-level performance: Sales data shows that 30 stores posted meaningful revenue gains over the past year. Foot traffic trends reinforce this momentum, with visits rising 8.0%–12.3% across these locations.
- Fleet-wide visit growth: Total chain visits increased 11.0% in Q3 compared to the previous year. Some of the growth reflects the opening of five new stores, but average visits per location also climbed 5.0% YoY, supporting the impact of the broader growth strategy.
- Improving customer loyalty: The share of customers visiting more than once in Q3 reached 15.0%, up from 7.0% the previous year, indicating rising loyalty and stronger engagement.
- Diversifying customer base: Foot traffic data combined with demographic and psychographic data points to a broader audience mix. Average-income shoppers increased by 7.0% in captured markets over four years. Stores that expanded high-end yoga assortments saw parallel growth in the share of yoga enthusiasts.
Weaknesses:
- Underperforming locations: Fifteen venues show sales data below expectations: eight with stalled growth and seven with significant YoY declines. Location analytics show that only four of the seven stores with declining sales experienced foot-traffic dips; the remaining three actually saw visit gains – suggesting conversion challenges rather than exposure or demand issues.
- Weekend softness & shorter dwell times: A smaller share of customers are visiting on weekends, and average in-store dwell time is falling – hinting at friction in the experience or changes in shopper mission.
- Promotion fatigue: Recent promotional campaigns are delivering diminishing foot traffic lifts. The latest basketball event drove a 107.4% spike in visits compared to 220.4% for the same promotion last year – signaling diminishing returns and potential oversaturation.
Opportunities:
- Cycling-focused markets: Trade area analysis paired with demographic datasets highlights twenty locations with above-average concentrations of cyclists. Strengthening biking assortments could unlock incremental demand.
- Cross-shopping synergies: Cross-shopping data reveals that an increasing share of shoppers to the sporting goods chain visit local gyms and coffee chains – making these nearby businesses ideal partners for promotions.
- Void analysis and site selection insights: Vacancies in several regional malls reflect visitor profiles aligned with the sporting goods chain’s existing customer base. These centers show untapped sporting goods demand – making them promising candidates for new locations.
Threats:
- Competitor momentum: A competing chain is experiencing a 33.0% YoY increase in visits, along with gains in loyalty and dwell time – suggesting operational or merchandising advantages that may pressure future share.
- Demographic exposure: Trade area comparisons show competitors outperforming in Gen Z engagement. With younger residents increasing in many of the chain’s markets, this gap poses a risk to long-term positioning.
A comprehensive SWOT analysis weaves together the data signals to form a grounded view of a company’s competitive posture. Location analytics provides clarity to questions of performance, evolving consumer preferences, expanding audience cohorts, and where competitors hold an edge. This structured perspective helps retailers refine strategies and build more resilient growth plans.
How Placer.ai Optimises Competitive Intelligence Gathering and Analysis
Using a location intelligence platform like Placer.ai enables businesses to analyze market, industry, and consumer trends with greater precision. Placer.ai leverages a panel of tens of millions of devices and utilizes machine learning to make accurate estimations for foot traffic across the country, from specific POIs, to chains, markets, and regions. Visitation data is enhanced with Placer Marketplace 3rd party datasets that further describe businesses, audiences, and markets.
Insights into how audiences and places interact are presented via an intuitive UI, data feeds, or the Placer API. Placer.ai’s dedicated support professionals and best-in-class research team are also available to deliver expert analysis and strategic guidance.
Whether you’re gathering competitive intelligence to benchmark against the competition, understand your consumer, or stay ahead of macroeconomic trends, Placer.ai provides the data and insights to strengthen your strategy.
Key Takeaways
- CI transforms publicly available information into strategic value: helping organizations understand competitors, customers, and market dynamics without relying on proprietary data.
- Location intelligence’s role in CI assessments: providing visibility into visits, loyalty, cross-shopping, trade area composition, and competitor performance that may not surface through traditional sources.
- Richer CI comes from a multi-source approach: public documents, field observations, and location intelligence collectively deliver a fuller picture of competitive realities.
