The market is flooded with reputation monitoring solutions that often fall short in providing actionable insights for reputation management. Addressing this gap, a unique evaluation framework and methodology have been developed for precise reputation measurement. This approach identifies key sources, messages, and stakeholders, providing a roadmap for reputation enhancement.

Advanced statistics, modeling, and machine learning play a crucial role in customer research for retail chains. These advanced techniques help identify customer segments, predict demand, personalize offers, and improve the shopping experience, thus driving strategic decision-making to increase customer satisfaction and retail chain performance.

• Analysis of customer experience in physical stores from reviews on Google My Business.
• Competitive study of ecommerce websites and apps.
• Analysis of the online reputation of companies.
• ESG positioning.

We offer comprehensive place branding solutions, using reputation analysis in media and social networks, competitive diagnosis and investment opportunities, as well as the identification of influencers in key markets to attract companies, talent, and investments.

• Analysis of city reputations in the media and social networks.
• Competitive and opportunity diagnosis for attracting investment in strategic sectors.
• Identification of media and user influencers in markets and sectors where attracting companies, talent, and investments.

We provide cutting-edge services in tourism market research, using machine learning and big data to provide strategic insights.

• Analysis of traveler preferences and behaviors based on massive data.
• Advanced market segmentation to identify market niches and adapt marketing strategies.
• Demand forecasting and trend analysis to anticipate changes in the tourism industry.
• Personalization of offers and travel experiences based on advanced recommendation algorithms.
• Measurement of customer satisfaction and online reputation analysis through sentiment analysis and social media.

We provide banks with solutions based on advanced statistics, modeling, and machine learning to boost their performance and strategic decision-making. Through data analysis and the application of sophisticated algorithms, we provide financial institutions with accurate and relevant information to adapt to the changing banking landscape and gain a competitive edge.

• Customer segmentation, using modeling techniques and statistical analysis to identify groups of customers with similar characteristics.
• Advanced risk analysis, using machine learning techniques to assess and predict credit risks.
• Fraud detection models using machine learning algorithms.
• Sentiment analysis and online reputation analysis, using natural language processing techniques to assess customer perception and brand reputation on social media and other digital platforms.

We provide a summary of our value proposition and expertise in this sector and a few examples of types of studies for this sector.

• Tracking of digital indicators of emerging brands and models.
• Analysis of satisfaction, areas of improvement, and best practices in dealerships/agencies.
• Analysis of reputation at key touchpoints: Google searches, YouTube/TikTok videos, and media (motor sections of generalist media and specialized media).
• Studies of trends in mobility and micromobility.

We leverage AI techniques to understand consumer food preferences and provide valuable insights for new product development. Through the analysis of data from social media, reviews, and purchasing behaviors, we identify patterns and trends in food preferences.

• Social media tracking of health and nutrition professionals, including nutritionists, doctors, and pharmacists.
• Monitoring of ingredients and recipes in digital media.
• Analysis of food consumption trends.
• Identification of food world influencers.

Our expertise in combining the power of social media and AI provides a competitive edge by delivering precise, real-time insights into the pharmaceutical market’s interests and needs. This facilitates informed, strategic decision-making. The application of advanced AI techniques allows us to process large volumes of information in real-time, extract relevant insights, and generate actionable intelligence. This enables pharmaceutical laboratories to better understand their target audience, more effectively adapt marketing and communication strategies, and develop products and services that meet the specific demands of patients and healthcare professionals.

• Social media tracking of health professionals, including doctors, pharmacists, nurses, and nutritionists.
• Digital reputation analysis of laboratories among different types of stakeholders.
• Examination of the patient and caregiver voice.
• Identification of prescribers and influencers by specialty/pathology.
• Measurement of campaign and sponsorship results.

With nearly a decade of experience in consumer research across various beauty product categories (skincare, haircare, perfumes, and makeup) and segments (mass market, selective, etc.), we offer:

• Social media tracking of professionals and influencers within the beauty and cosmetics industry, including aesthetic doctors, dermatologists, beauticians, makeup artists, and hairdressers.
• Analysis of ingredient notoriety and prescription among both professionals and consumers.
• Examination of category and product trends.
• Assessment of brand positioning and customer experience.
• Evaluation of company reputation and ESG positioning.

The selection of influencers who align with a brand’s values and generate engagement directly influences the results of advocacy campaigns and can affect corporate reputation. Solutions have been developed to help select influencers that best connect with customers and brand values. A proprietary methodology is also used for analyzing the reputation and digital footprint of influencers, enabling the detection of potential future issues before collaboration begins.

AI and Machine Learning are used to measure the impact of advertising campaigns accurately. Models trained to recognize logos in images shared on social networks are used to analyze the impact of sponsorships at events and congresses. Advanced AI and Machine Learning techniques are also applied to analyze user-generated content on social networks, providing precise metrics about brand exposure.

The approach to detecting social and consumer trends has evolved over the past 15 years, with artificial intelligence (AI) and advanced statistics becoming fundamental pillars for trend prediction. AI allows for real-time information processing, relevant knowledge extraction, and accurate predictions about emerging trends. The combination of advanced statistical techniques and machine learning algorithms has overcome previous limitations, enabling the analysis of structured and unstructured data from various sources and offering a deeper understanding of changes in consumer behaviors.

Product reviews from online stores, like Amazon, provide deep insights into consumer tastes, preferences, and habits. Advanced NLP techniques and precision language models are utilized to analyze these reviews, revealing relevant category attributes, natural competitors, and brand positioning.

Traditional customer experience analysis techniques, such as surveys, are combined with online reviews to provide a comprehensive picture of the customer experience. Reviews, reflecting spontaneous and unsolicited customer experiences, are invaluable for training automatic sentiment classification models.

Traditional segmentation systems based on sociodemographic variables are enhanced with a tribe-based approach. Tribes, representing groups of individuals with shared interests, transcend traditional variables such as social class, gender, or age. This approach allows for a better understanding of the motivations and specific needs of these communities, enabling more effective adaptation of strategies and marketing messages.

A corporate purpose extends beyond profit-making, encapsulating the organization’s mission, core values, and its commitment to societal and environmental impact. Companies with a clear purpose gain a competitive edge, attracting loyal customers and committed employees, and fostering strong stakeholder relationships. Consumer research is leveraged to define and adjust this purpose, aligning it with societal demands and fostering open dialogue and trust with customers.

Ensuring that an ESG strategy is recognized by stakeholders is a significant challenge for sustainability departments. To meet this challenge, a portfolio of specialized solutions has been developed to optimize the ESG strategy. These solutions ensure the strategy is distinctive, relevant, and responsive to stakeholder needs and expectations, avoiding greenwashing.