Unlocking Local Growth Data Driven Neighborhood Targeting

For small to medium businesses (SMBs), growth often hinges on dominating their local market. Casting a wide net in marketing can be costly and inefficient. Data-driven neighborhood targeting offers a smarter approach, focusing resources where they yield the highest return. This guide provides actionable steps to implement this strategy, even with limited resources.

Understanding Neighborhood Targeting Fundamentals

Neighborhood targeting is about concentrating marketing efforts on specific geographic areas where your ideal customers live and work. Instead of broadly advertising across an entire city, you pinpoint neighborhoods with demographics, lifestyles, and needs that align with your business offerings. This focused approach maximizes marketing impact while minimizing wasted ad spend.

Data-driven neighborhood targeting enables SMBs to concentrate marketing efforts on specific geographic areas with high customer potential, optimizing resource allocation and maximizing ROI.

Why Neighborhood Focus Matters for SMBs

SMBs often operate with tighter budgets than large corporations. Therefore, every marketing dollar must count. Neighborhood targeting allows for:

• Increased Relevance ● Messaging can be tailored to the specific needs and interests of neighborhood residents.
• Higher Conversion Rates ● Targeting receptive audiences naturally leads to better engagement and sales.
• Cost Efficiency ● Reduced ad spend on uninterested audiences translates to significant savings.
• Stronger Community Ties ● Focusing on the local community builds brand loyalty and word-of-mouth referrals.
• Competitive Advantage ● Outsmarting larger competitors by hyper-localizing marketing efforts.

Essential First Steps Defining Your Ideal Neighborhood

Before diving into data, clarify who your ideal customer is. Consider:

• Demographics ● Age, income, education, family status.
• Lifestyle ● Interests, hobbies, values, online behavior.
• Needs and Pain Points ● What problems does your business solve for customers?
• Location ● Where do your current best customers live?

Once you have a clear customer profile, you can start identifying neighborhoods that match. This involves both online and offline research.

Leveraging Basic Tools for Neighborhood Insights

Several free or low-cost tools can provide valuable neighborhood-level data:

1. Google My Business (GMB) ● Your GMB profile itself is a neighborhood targeting tool. Ensure it’s fully optimized with local keywords, accurate address, and neighborhood descriptions. Google provides insights into search queries used to find your business, often revealing neighborhood names.
2. Google Maps ● Explore neighborhoods visually. See the types of businesses, amenities, and housing. Read local reviews to understand community sentiment and needs.
3. Facebook Audience Insights ● Even with privacy changes, Facebook still offers demographic and interest data at a local level. Explore audience segments within your service area.
4. Local Data Platforms (e.g., City-Data.com, Niche.com) ● These platforms aggregate public data on neighborhoods, including demographics, schools, crime rates, and resident reviews.
5. U.S. Census Bureau ● Provides detailed demographic data at various geographic levels, including census tracts and neighborhoods. While detailed data might require some navigation, summary tables are readily accessible.

Avoiding Common Pitfalls in Early Targeting

SMBs new to data-driven targeting sometimes make easily avoidable mistakes:

• Overlooking Offline Data ● Don’t solely rely on online tools. Observe your physical surroundings, talk to local residents, and attend community events to gain qualitative insights.
• Generic Messaging ● Failing to tailor your message to the specific neighborhood. A one-size-fits-all approach diminishes impact.
• Ignoring Local Competition ● Analyze what your competitors are doing in specific neighborhoods. Identify underserved areas or niches.
• Data Paralysis ● Getting overwhelmed by data and failing to take action. Start with basic data and iterate.
• Lack of Tracking ● Not monitoring results to see what’s working and what’s not. Basic tracking is essential for optimization.

Quick Wins Initial Neighborhood Targeting Actions

Start with these immediately actionable steps:

1. Optimize Google My Business ● Ensure your GMB profile is complete, accurate, and uses local keywords relevant to your target neighborhoods. Add posts and photos showcasing your business’s local connection.
2. Localize Website Content ● Create neighborhood-specific landing pages on your website. Mention neighborhood names and landmarks in your website copy.
3. Run Geo-Targeted Social Media Ads ● Use platforms like Facebook and Instagram to run ads targeting specific neighborhoods. Experiment with different ad creatives tailored to each area.
4. Participate in Local Online Groups ● Engage in relevant Facebook groups, Nextdoor, and other online communities specific to your target neighborhoods. Offer helpful advice and subtly promote your business where appropriate.
5. Sponsor Local Events ● Support neighborhood events like farmers’ markets, festivals, and school fundraisers. This builds local visibility and goodwill.

Example Restaurant Neighborhood Targeting

Consider a pizza restaurant aiming to increase local deliveries. Using basic tools, they can identify target neighborhoods:

1. GMB Insights ● Analyze search queries to see which neighborhoods are searching for “pizza delivery near me.”
2. Google Maps ● Identify neighborhoods near the restaurant with a high density of apartments or families.
3. Local Data Platforms ● Check neighborhood demographics for areas with a high percentage of their target age group (e.g., 25-45 year olds) and income level.

Based on this data, they might target two neighborhoods ● “Oakwood” and “Maplewood.” Their initial actions could include:

• Creating GMB posts specifically mentioning “Pizza Delivery in Oakwood and Maplewood.”
• Running Facebook ads targeting residents of Oakwood and Maplewood with a special “Neighborhood Discount.”
• Partnering with the Oakwood community center for a pizza night fundraiser.

By focusing on these two neighborhoods, the pizza restaurant can significantly increase its delivery orders and build a loyal local customer base.

Starting with these fundamental steps and readily available tools empowers SMBs to begin leveraging data-driven neighborhood targeting for immediate and measurable growth. The key is to start small, focus on actionable insights, and continuously refine your approach based on results.

Refining Targeting Advanced Data and Techniques

Building upon the fundamentals, the intermediate stage of data-driven neighborhood targeting involves employing more sophisticated tools and techniques to deepen customer understanding and optimize marketing campaigns. This phase focuses on leveraging richer datasets, implementing targeted advertising strategies, and measuring campaign performance with greater precision.

Expanding Data Sources Deeper Neighborhood Insights

Moving beyond basic tools requires exploring more granular data sources to build a comprehensive picture of target neighborhoods:

Advanced Demographic and Psychographic Data

While census data provides a broad overview, specialized data providers offer more nuanced insights:

• Experian, Nielsen, Acxiom ● These companies offer marketing data services providing detailed demographic, psychographic, and consumer behavior data at the neighborhood level. This includes information on lifestyle segmentation, purchasing habits, media consumption, and more. While often requiring a subscription, the depth of data justifies the investment for businesses scaling their targeting efforts.
• Local Market Research Firms ● Engaging local research firms can provide customized neighborhood-level studies tailored to your specific business needs. They can conduct surveys, focus groups, and analyze local market trends to deliver highly relevant insights.
• Publicly Available City Data Portals ● Many cities and municipalities now offer open data portals with information on permits, licenses, zoning, infrastructure projects, and more. This data can reveal neighborhood development trends and business opportunities.

Location-Based Mobile Data

Mobile data provides real-time insights into consumer movement and behavior within neighborhoods:

• Mobile Advertising Platforms (e.g., Foursquare, Groundtruth) ● These platforms utilize location data from mobile devices to enable highly targeted advertising based on real-world behavior. You can target users who frequently visit specific types of businesses or locations within your target neighborhoods.
• Geofencing Technology ● Geofencing allows you to create virtual boundaries around neighborhoods and trigger actions when users enter or exit these areas. This can be used for targeted mobile ads, notifications, and data collection.
• Aggregated Mobile Movement Data (Anonymized) ● Data providers offer anonymized and aggregated mobile movement data showing foot traffic patterns, popular routes, and dwell times within neighborhoods. This can inform decisions about optimal business locations, outdoor advertising placement, and event planning.

Social Listening and Sentiment Analysis

Monitoring social media conversations provides valuable qualitative data about neighborhood sentiment and trends:

• Social Listening Tools (e.g., Brandwatch, Sprout Social) ● These tools track social media mentions, hashtags, and keywords related to your business and target neighborhoods. They can identify trending topics, customer opinions, and potential brand advocates within specific localities.
• Sentiment Analysis ● Advanced social listening Meaning ● Social Listening is strategic monitoring & analysis of online conversations for SMB growth. tools incorporate sentiment analysis, automatically gauging the positive, negative, or neutral tone of online conversations. This helps understand neighborhood perceptions of your brand and identify areas for improvement.
• Neighborhood-Specific Social Groups ● Actively monitoring and engaging in neighborhood-specific Facebook groups, Nextdoor communities, and local forums provides direct insights into resident concerns, needs, and preferences.

Intermediate data-driven neighborhood targeting leverages advanced demographic, mobile, and social data to create a richer understanding of local customer segments and preferences.

Implementing Targeted Advertising Strategies

With deeper neighborhood insights, SMBs can implement more refined advertising strategies:

Hyperlocal Digital Advertising

Beyond basic geo-targeting, hyperlocal advertising focuses on reaching customers within very specific micro-geographic areas:

• Radius Targeting Refinement ● Instead of targeting entire zip codes, narrow your radius targeting to specific blocks or streets within high-potential neighborhoods.
• Addressable Geofencing ● Target advertising to individual households or businesses within a neighborhood based on address-level data. This is particularly effective for direct mail integration or highly personalized offers.
• Contextual Geo-Targeting ● Target users based on their real-time location and context. For example, a coffee shop can target users near their location during morning commute hours.
• IP Address Targeting ● Target households based on their IP address, allowing for precise delivery of online ads to specific residential areas.

Neighborhood-Specific Content Marketing

Tailor content marketing Meaning ● Content Marketing, in the context of Small and Medium-sized Businesses (SMBs), represents a strategic business approach centered around creating and distributing valuable, relevant, and consistent content to attract and retain a defined audience — ultimately, to drive profitable customer action. efforts to resonate with the unique interests and needs of each target neighborhood:

• Localized Blog Posts and Articles ● Create blog content or articles addressing topics relevant to specific neighborhoods. For example, a gardening store could write a blog post on “Best Plants for Oakwood Gardens” highlighting local soil conditions and climate.
• Neighborhood-Focused Social Media Content ● Develop social media posts showcasing your business’s involvement in specific neighborhoods, featuring local events, customer stories, or neighborhood landmarks.
• Community Newsletters and Emails ● Create email newsletters segmented by neighborhood, delivering localized promotions, event announcements, and community news.
• Partnerships with Local Influencers ● Collaborate with social media influencers who are popular within specific neighborhoods to promote your business to their local followers.

Direct Mail and Print Advertising Optimization

Even in the digital age, direct mail and print advertising can be highly effective when hyper-localized:

• Targeted Direct Mail Campaigns ● Use demographic and address-level data to send highly targeted direct mail pieces to households within your ideal neighborhoods. Personalize offers based on neighborhood characteristics.
• Local Print Media Advertising ● Advertise in neighborhood newspapers, community magazines, and local directories to reach residents who consume local print media.
• Door-To-Door Marketing ● For certain businesses, door-to-door marketing (flyers, coupons, samples) can be effective in densely populated target neighborhoods, especially when combined with online follow-up.
• Integration of Online and Offline ● Combine direct mail or print advertising with online retargeting. For example, send a direct mail piece with a QR code that leads to a neighborhood-specific landing page for online follow-up.

Case Study Local Bookstore Targeted Campaign

A local bookstore wants to promote its new children’s book section. They identify two target neighborhoods ● “Literary Heights” (high income, families with young children, known for book clubs) and “Scholarsville” (university-adjacent, students and academics, diverse interests).

Their intermediate-level targeting strategy includes:

1. Data Enrichment ● They purchase data from a marketing data provider to identify households in “Literary Heights” with children under 10 and an interest in reading. For “Scholarsville,” they focus on households near the university and those expressing interest in literature and education on social media.
2. Hyperlocal Digital Ads ● They run addressable geofencing campaigns targeting homes in “Literary Heights” with ads featuring children’s books and family reading events. For “Scholarsville,” they use contextual geo-targeting to reach users near the university campus during lunch and evening hours with ads highlighting diverse literary genres and academic books.
3. Neighborhood-Specific Content ● They create blog posts titled “Top 5 Children’s Books for Literary Heights Families” and “Scholarsville’s Guide to Contemporary Literature.” They also create neighborhood-specific Facebook events for children’s story time in “Literary Heights” and author talks in “Scholarsville.”
4. Direct Mail Optimization ● They send personalized postcards to homes in “Literary Heights” with a family reading promotion and to homes in “Scholarsville” with a student discount offer.

By tailoring their marketing message and channels to each neighborhood’s unique characteristics, the bookstore significantly increases engagement and sales for their new children’s book section.

Measuring and Optimizing Intermediate Campaigns

Intermediate targeting requires more sophisticated measurement to assess ROI and optimize campaigns:

Advanced Web Analytics and Tracking

Beyond basic website traffic, track neighborhood-specific website behavior:

• Geographic Segmentation in Analytics ● Use Google Analytics or similar platforms to segment website traffic and conversions by geographic location (neighborhood, city, region).
• Landing Page Performance by Neighborhood ● Track the performance of neighborhood-specific landing pages, measuring conversion rates, bounce rates, and time on page for each neighborhood segment.
• Call Tracking with Geographic Data ● Implement call tracking to attribute phone calls to specific marketing campaigns Meaning ● Marketing campaigns, in the context of SMB growth, represent structured sets of business activities designed to achieve specific marketing objectives, frequently leveraged to increase brand awareness, drive lead generation, or boost sales. and geographic areas. This provides offline conversion data linked to neighborhood targeting efforts.
• Customer Relationship Management (CRM) Integration ● Integrate your CRM system with your marketing analytics to track customer acquisition costs, lifetime value, and customer behavior segmented by neighborhood.

Attribution Modeling for Multi-Channel Campaigns

When using multiple channels (digital ads, social media, direct mail), use attribution modeling Meaning ● Attribution modeling, vital for SMB growth, refers to the analytical framework used to determine which marketing touchpoints receive credit for a conversion, sale, or desired business outcome. to understand the contribution of each channel to conversions within target neighborhoods:

• Multi-Touch Attribution Models ● Explore attribution models beyond last-click, such as linear, time-decay, or U-shaped models, to get a more holistic view of channel contributions across the customer journey within each neighborhood.
• Marketing Mix Modeling (MMM) ● For larger SMBs with significant marketing budgets, consider marketing mix modeling Meaning ● Marketing Mix Modeling (MMM) is a statistical analysis technique utilized by SMBs to quantify the impact of various marketing investments on sales and revenue. to analyze the overall impact of different marketing channels on sales across various neighborhoods.
• A/B Testing of Neighborhood-Specific Campaigns ● Conduct A/B tests comparing different marketing messages, channels, and offers within specific neighborhoods to identify the most effective combinations.

Return on Investment (ROI) Analysis by Neighborhood

Calculate ROI at the neighborhood level to identify the most profitable target areas:

• Revenue Tracking by Neighborhood ● Implement systems to track revenue generated from customers in each target neighborhood. This can involve point-of-sale (POS) integration, CRM data, or customer surveys.
• Marketing Cost Allocation by Neighborhood ● Accurately allocate marketing expenses to each target neighborhood to calculate neighborhood-specific ROI.
• Profitability Analysis ● Analyze profitability by neighborhood, considering both revenue and marketing costs. Identify high-ROI neighborhoods for increased investment and low-ROI neighborhoods for optimization or re-evaluation.

By embracing these intermediate strategies, SMBs can move beyond basic targeting and achieve significantly improved campaign performance, customer acquisition, and ROI from their neighborhood-focused marketing efforts. Continuous measurement and optimization are paramount to maximizing success at this level.

AI Powered Hyperlocal Strategies Competitive Edge

For SMBs seeking to truly dominate their local market and gain a sustainable competitive advantage, advanced data-driven neighborhood targeting leverages the power of Artificial Intelligence (AI) and sophisticated automation. This level focuses on predictive analytics, personalized customer experiences at scale, and optimizing every facet of hyperlocal marketing Meaning ● Hyperlocal marketing: Targeted strategies for SMBs to connect with nearby customers, fostering local growth and community ties. with cutting-edge technologies.

Harnessing AI for Predictive Neighborhood Insights

AI algorithms can analyze vast datasets to uncover patterns and predict future trends at the neighborhood level, providing a significant strategic advantage:

Predictive Analytics for Demand Forecasting

AI-powered predictive analytics Meaning ● Strategic foresight through data for SMB success. can forecast demand for your products or services in specific neighborhoods:

• Time Series Analysis with Machine Learning ● Utilize machine learning algorithms to analyze historical sales data, seasonal trends, local events calendars, and demographic shifts to predict future demand fluctuations in each neighborhood. Tools like Prophet (by Facebook) or ARIMA models in Python can be employed.
• External Data Integration for Demand Prediction ● Integrate external datasets such as weather forecasts, local economic indicators (unemployment rates, housing market data), traffic patterns, and social media trends into predictive models to enhance forecast accuracy.
• Neighborhood-Level Demand Heat Maps ● Visualize predicted demand on neighborhood heat maps, identifying high-demand zones and optimal times for targeted marketing campaigns or staffing adjustments.
• AI-Driven Inventory Management ● Optimize inventory levels based on predicted neighborhood-level demand, ensuring product availability in high-demand areas while minimizing waste in lower-demand zones.

AI-Powered Customer Segmentation and Persona Development

Go beyond basic demographics and create hyper-personalized customer segments using AI:

• Clustering Algorithms for Micro-Segmentation ● Employ clustering algorithms (e.g., K-Means, DBSCAN) to segment customers into micro-segments based on a combination of demographic, psychographic, behavioral, and location data. This reveals nuanced customer groups within neighborhoods.
• AI-Driven Persona Generation ● Automate the creation of detailed customer personas for each micro-segment using AI. These personas go beyond basic demographics to include motivations, values, pain points, media consumption habits, and even preferred communication styles.
• Natural Language Processing (NLP) for Sentiment-Based Segmentation ● Utilize NLP to analyze customer reviews, social media posts, and survey responses to segment customers based on their expressed sentiment and opinions related to your brand and local market.
• Personalized Marketing Journeys Per Persona ● Design unique marketing journeys tailored to each AI-generated persona, delivering highly relevant content, offers, and experiences across all touchpoints.

Anomaly Detection for Emerging Neighborhood Trends

AI can identify anomalies and outliers in neighborhood data, signaling emerging trends or potential disruptions:

• Statistical Anomaly Detection Meaning ● Anomaly Detection, within the framework of SMB growth strategies, is the identification of deviations from established operational baselines, signaling potential risks or opportunities. Algorithms ● Implement statistical anomaly detection algorithms (e.g., Z-score, Isolation Forest) to identify unusual patterns in neighborhood data, such as sudden spikes in social media mentions, shifts in demographic trends, or unexpected changes in foot traffic.
• Real-Time Data Monitoring with AI Alerts ● Set up real-time data monitoring dashboards with AI-powered alerts that notify you of significant anomalies in neighborhood data, enabling proactive responses to emerging trends or potential crises.
• Early Adopter Identification ● Use anomaly detection to identify “early adopter” neighborhoods that are exhibiting trends before they become mainstream. Focus marketing efforts on these neighborhoods to gain a first-mover advantage.
• Competitive Intelligence and Threat Detection ● Monitor competitor activity and customer sentiment in target neighborhoods using AI-powered anomaly detection to identify potential competitive threats or shifts in market share.

Advanced AI-powered neighborhood targeting utilizes predictive analytics, AI-driven segmentation, and anomaly detection to anticipate market changes and proactively optimize hyperlocal strategies.

Advanced Automation for Hyperlocal Marketing Execution

Automate marketing processes with AI to deliver personalized experiences at scale and maximize efficiency:

AI-Powered Content Personalization and Dynamic Creative Optimization (DCO)

Automate the creation of personalized content and ad creatives tailored to each neighborhood and customer segment:

• AI Content Generation for Hyperlocal Messaging ● Utilize AI content Meaning ● AI Content, in the SMB (Small and Medium-sized Businesses) context, refers to digital material—text, images, video, or audio—generated, enhanced, or optimized by artificial intelligence, specifically to support SMB growth strategies. generation tools (e.g., GPT-3 powered platforms) to automatically create neighborhood-specific ad copy, social media posts, email newsletters, and website content.
• Dynamic Creative Optimization (DCO) for Ad Personalization ● Implement DCO platforms that dynamically adjust ad creatives (images, headlines, calls-to-action) in real-time based on user location, demographics, interests, and browsing behavior within target neighborhoods.
• Personalized Landing Pages with AI Content ● Automate the creation of personalized landing pages Meaning ● Personalized Landing Pages, in the context of SMB growth, represent unique web pages designed to address the specific needs and interests of individual visitors or audience segments. for each neighborhood segment, dynamically displaying relevant content, offers, and testimonials based on user location and persona.
• AI-Driven Email Personalization at Scale ● Utilize AI to personalize email marketing campaigns with neighborhood-specific content, product recommendations, and offers, automatically tailoring email elements based on recipient location and preferences.

Automated Hyperlocal Campaign Management and Optimization

Automate campaign management tasks and optimize performance in real-time with AI:

• AI-Powered Bidding and Budget Allocation ● Employ AI-driven bidding algorithms and budget allocation tools to automatically optimize ad spend across different neighborhoods and platforms, maximizing ROI based on real-time performance data.
• Automated A/B Testing Meaning ● A/B testing for SMBs: strategic experimentation to learn, adapt, and grow, not just optimize metrics. and Experimentation ● Utilize AI to automate A/B testing of different ad creatives, landing pages, and offers within target neighborhoods, continuously identifying and implementing the most effective combinations.
• Real-Time Campaign Performance Monitoring and Alerts ● Set up AI-powered campaign monitoring dashboards with real-time performance alerts, automatically notifying you of underperforming campaigns or opportunities for optimization within specific neighborhoods.
• Predictive Campaign Optimization ● Leverage AI to predict future campaign performance in different neighborhoods and proactively adjust campaign parameters (bids, targeting, creatives) to optimize results before performance declines.

AI-Driven Customer Service and Engagement Automation

Enhance customer service Meaning ● Customer service, within the context of SMB growth, involves providing assistance and support to customers before, during, and after a purchase, a vital function for business survival. and engagement with AI-powered automation tailored to neighborhood preferences:

• AI Chatbots for Hyperlocal Customer Support ● Implement AI chatbots Meaning ● AI Chatbots: Intelligent conversational agents automating SMB interactions, enhancing efficiency, and driving growth through data-driven insights. on your website and social media channels to provide instant customer support tailored to neighborhood-specific inquiries, local store information, and community events.
• Personalized Customer Service Interactions with AI ● Utilize AI to personalize customer service interactions based on customer location, purchase history, and neighborhood preferences, delivering more relevant and efficient support.
• Automated Feedback Collection and Sentiment Analysis ● Automate the collection of customer feedback through surveys, reviews, and social media monitoring, using AI sentiment analysis Meaning ● Sentiment Analysis, for small and medium-sized businesses (SMBs), is a crucial business tool for understanding customer perception of their brand, products, or services. to identify neighborhood-specific customer satisfaction trends and areas for improvement.
• Proactive Customer Engagement with AI-Driven Recommendations ● Employ AI to proactively engage customers with personalized product recommendations, neighborhood-specific offers, and event invitations based on their past behavior and location.

Case Study AI Powered Restaurant Chain Expansion

A regional restaurant chain wants to expand into new neighborhoods using AI-powered hyperlocal targeting.

Their advanced strategy includes:

1. Predictive Analytics for Site Selection ● They use AI to analyze neighborhood demographics, competitor density, foot traffic data, and social media sentiment to predict the most profitable locations for new restaurants. AI models identify underserved neighborhoods with high demand for their cuisine.
2. AI-Driven Personalized Marketing Pre-Launch ● Before opening a new restaurant, they launch AI-powered hyperlocal marketing campaigns targeting residents in the surrounding neighborhoods. Personalized ads and social media content showcase menu items tailored to local preferences (identified through social listening and demographic data).
3. Dynamic Creative Optimization for Grand Opening Ads ● For grand opening promotions, they use DCO to dynamically adjust ad creatives based on neighborhood demographics and real-time weather conditions. Ads shown in family-oriented neighborhoods feature family meal deals, while ads in younger neighborhoods highlight happy hour specials.
4. AI Chatbots for Local Customer Service ● After opening, they implement AI chatbots on their website and mobile app to handle local customer inquiries, reservations, and delivery orders. Chatbots are trained to provide neighborhood-specific information, such as local parking availability and community event tie-ins.

By leveraging AI across site selection, marketing, and customer service, the restaurant chain achieves rapid and profitable expansion, outperforming competitors with less sophisticated hyperlocal strategies.

Adopting these advanced AI-powered strategies empowers SMBs to operate at the forefront of hyperlocal marketing. By embracing predictive insights and automation, businesses can achieve unprecedented levels of personalization, efficiency, and competitive dominance in their target neighborhoods, securing sustainable long-term growth.

References

• Kotler, Philip; Armstrong, Gary (2021). Principles of Marketing. Pearson Education.
• Levitt, Theodore (2006). Marketing Myopia. Harvard Business Review Press.
• Ries, Al; Trout, Jack (2006). Positioning ● The Battle for Your Mind. McGraw-Hill.