Ebook
This ebook explores the evolving discipline of social listening, its many names, and the key questions organizations should ask before getting started. If you are new to social mediamonitoring or don’t have theanswers to these questions, readon...
Ebook Highlights:
1. See how web listening provides a unique consumer portal at a time when response rates for research projects are dropping and it’s getting harder to reach your key customers;
2. Understand why It is now more vital than ever for organizations to understand what is being said about them, so that they can effectively manage their brands and their reputation online;
3. Learn how findings from web listening can improve business performance, whether it’s communication, targeting or product development or using the findings to enhance data from existing sources.
Ideal for:
1. Any organisation, brand manager and employees within the marketing department who specialise in the discipline of social media.
2. Market research agencies who want to learn about social media monitoring or web listening.
P.S. Have questions about the ebook? Contact us at: info@listening247.com. We're happy to help!
listening247 In the Press
The future of Customer Experience Management (CXM) is set to be transformed by the ability to analyze all customer interactions, regardless of their source or language. This shift is not speculative but rather a natural progression of existing technology. With AI-driven tools becoming increasingly capable of processing vast amounts of customer data, the industry is moving towards a universal approach that captures every customer opinion, whether solicited or unsolicited. As CXM professionals adapt to this new reality, they will face both challenges and opportunities in harnessing the full potential of this comprehensive analysis.
The future of Customer Experience Management (CXM) will be significantly impacted by the ability to access and analyze all customer opinions, particularly in tracking multiple relevant KPIs. While many companies currently rely on the Net Promoter Score (NPS) to gauge customer loyalty and satisfaction, this single KPI may not capture the full complexity and nuance that new technology offers by analyzing every customer interaction.
As CXM evolves, we can expect a shift towards using multiple, composite KPIs that synthesize data from various customer interaction sources, such as sentiment, purchase intent, and social media engagement. While these findings may still be presented in a simplified score, like DMR’s Net Sentiment Score (NSS) or Social Presence Score (SPS), the measurement of market performance will need to reflect the sophistication and depth of the available data.
Access to comprehensive customer interaction data will not only enhance market position insights but also revolutionize how companies address pain points. With all customer feedback at their disposal, businesses will be able to prioritize and address issues more effectively, both proactively and reactively. Reactive measures may involve refining call center protocols and complaints handling, while proactive solutions could focus on real-time operational fixes to mitigate issues before they escalate.
These advancements are already feasible with current technology and specialist expertise, enabling companies to convert customer opinions into actionable strategies. By tackling pain points and optimizing customer retention, businesses can significantly reduce churn. Future discussions will shift towards leveraging customer strengths and gain points to further improve CX.
The growing reliance on advanced technology for Customer Experience Management (CXM) will introduce new challenges, particularly regarding the accuracy of AI-driven annotations for sentiment and purchase intent. Ensuring precise analysis of millions of interactions across various languages is crucial for effective CXM. As the industry adapts to these technologies, a virtuous cycle may emerge: enhanced annotation accuracy leads to better analysis, which in turn improves CXM capabilities, promising robust business growth and a more satisfying customer experience.
In conclusion, the integration of advanced AI technologies in Customer Experience Management (CXM) holds the promise of transforming how businesses understand and respond to customer interactions. By leveraging precise, language-agnostic data analysis, companies can move beyond traditional KPIs and gain a deeper, more nuanced view of customer sentiment and behavior. This shift enables proactive and reactive solutions to pain points, ultimately enhancing customer satisfaction and retention. As the industry embraces these innovations, the emphasis on accurate data annotation and comprehensive analysis will drive significant growth and elevate the overall customer experience.
Origal Source: Finance Digest
listening247 In the Press
London, UK – 01/10/2024 – listening247, a leading provider of data-driven marketing solutions, is proud to announce the launch of DataVinci, a Generative AI (Gen AI) solution that is set to transform how businesses gather, analyse, and act on data. DataVinci adds value to listening247’s Intelligent data as a Service (IdaaS) offering, delivering actionable insights and helping brands unlock the full potential of their marketing strategies.
DataVinci sits in the middle of listening247’s suite of solutions, including listening247 for social listening and analytics, engaging247 for social media management, and communities247 for direct customer engagement through private online customer communities. Together, these solutions provide businesses with a comprehensive, end-to-end data intelligence platform that empowers them to stay ahead of their competition.
“DataVinci is a significant leap forward in the way we approach data and content creation,” said Michalis A. Michael, CEO at listening247. “We have developed a solution that not only identifies trends and insights but also turns those insights into action. DataVinci delivers fully automated recommendations, and what truly sets it apart is its ability to create ready-to-use content, complete with post copy and image briefs, helping businesses connect with their audiences more efficiently than ever.”
DataVinci: Powering Intelligent data as a Service (IdaaS)
At the heart of DataVinci’s innovation is its ability to turn raw data into precise, actionable recommendations. By integrating with listening247’s social listening and analytics solution, DataVinci analyses both structured and unstructured data from across digital channels to offer a 360-degree view of consumer sentiment and brand performance. It not only identifies emerging trends, customer emotions, and key purchase drivers but also generates content—from engaging copy to image descriptions—tailored to your brand’s voice.
“DataVinci is not just about reports; it’s about taking meaningful action in a very efficient way,” added Michalis A. Michael. “With DataVinci, businesses no longer need to struggle with interpreting complex data or creating content from scratch. Our AI-driven solution automates these processes, allowing teams to focus on what truly matters—engaging with their customers and driving growth.”
Enhancing Social Media and Customer Engagement
DataVinci works alongside engaging247, listening247’s social media management platform, to help brands manage their social presence with ease. While DataVinci creates high-quality, actionable content, engaging247 streamlines the posting and scheduling process, allowing businesses to maintain a consistent and impactful online presence.
Meanwhile, communities247 enables brands to gather solicited feedback directly from private, branded customer communities, offering deep insights into customer behaviour and preferences. With DataVinci, these insights are automatically analysed, and businesses receive clear, data-driven recommendations to enhance customer engagement and drive loyalty.
Industry Leaders Impressed by DataVinci
Since its introduction, CEOs who have experienced DataVinci in action have been thoroughly impressed. DataVinci’s ability to streamline data analysis and content creation has resonated strongly with decision-makers looking for smarter, more efficient ways to engage with their audience.
“After seeing what DataVinci can do, all CEOs who were involved in our “lean start-up” approach for customer-centric development were eager to sign up and get it implemented to support their teams,” Michael continued. “They appreciate how DataVinci simplifies the process of data analysis and automatically produces reports, actionable recommendations, and even content that’s ready to go. It’s not just about saving time—it’s about ensuring that the actions taken are always based on intelligent, data-backed insights.”
A Bright Future for Data-Driven Marketing
As more businesses turn to AI to gain a competitive edge, DataVinci stands out as a solution that combines innovation, authenticity, and ease of use. Its ability to deliver insights, automate content creation, and empower businesses with actionable recommendations sets a new standard for how brands can leverage the power of data.
“Our mission has always been to help brands better understand their customers and act on those insights,” said Michael. “With DataVinci, we’re delivering on that promise in a way that is more intuitive, more powerful, and more cost-effective than ever before.”
*Original Source: Global Tech Reporter
Ebook
This ebook aims to demonstrate how integrating Social Listening and Analytics data with survey data, and other traditional research methods, can help companies uncover some of the most accurate insights possible. A case study revolving around Health & Wellness, as discussed online in Arabic, was selected as an example to illustrate the untapped power of social listening analytics.
Ebook Highlights:
1. Find out how to uncover and synthesize accurate insights by integrating data from various sources;
2. Discover the untapped power of social listening analytics;
3. Understand why traditional methods are no longer sufficient or fully representative;
4. Learn about trends and ideas related to Health & Wellness in the MENA region.
Ideal for:
1. Any organisation within the health & wellness sector who want to enhance their market research activities to uncover some of the most accurate insights possible.
2. Market research agencies who want to learn about the importance of accuracy when it comes to social insights about trends and ideas related to health and wellness in the MENA region.
P.S. Have questions about the ebook? Contact us at: info@listening247.com. We're happy to help!
Case Study
A global company needed to enhance product perception and performance without increasing costs, as traditional market research methods were too slow and expensive. listening247 responded with a private online community platform that allowed real-time consumer interactions and feedback, offering a cost-effective and timely solution for strategic insights and marketing decisions.
A global company faced the dual challenge of improving product perception and performance without increasing expenditure. Tasked by the CEO to deliver actionable insights, the Marketing Director needed a solution that was both quick and cost-effective, as traditional market research methods were proving too slow and expensive for the dynamic market landscape.
To address these challenges, listening247 introduced an innovative solution: a private online community platform designed to serve as an advisory board comprising consumers. This platform facilitated real-time interactions and allowed the marketing team to conduct various activities like polls, asynchronous discussions, and video diary sessions.
1. Accelerated Decision-Making: The client rapidly acquired preliminary consumer feedback that informed critical marketing decisions, keeping them ahead in a competitive market.
2. Economic Strategy Refinement: The online community platform reduced overall market research costs while providing valuable insights, maximising ROI on marketing spend.
3. Real-Time Consumer Feedback: listening247 introduced a private online community platform that acted as a consumer advisory board, enabling the marketing team to gather immediate insights through polls, discussions, and video diaries.
4. Cost-Efficient Engagement: This virtual platform significantly cut costs associated with traditional research methods by eliminating the need for physical focus groups and reducing logistical expenses.
5. Privacy-Centric Interaction: Maintaining consumer privacy, the platform encouraged genuine feedback, ensuring that the insights gathered were both authentic and actionable.
Case Study
A leading luxury watch manufacturer sought to deepen their understanding of market dynamics and consumer perceptions but faced challenges with a limited volume of social media interactions. listening247® technology was deployed to analyse over 41,794 posts, refining the data to 4,423 relevant commercial interactions, which provided actionable insights and enhanced brand perception and engagement.
A leading luxury watch manufacturer needed to enhance their understanding of market dynamics and consumer perceptions. The challenge was to derive actionable insights from a limited volume of social media interactions using methods beyond traditional analytics.
listening247 implemented their proprietary technology to meticulously analyse social media data associated with the luxury watch market. The approach was comprehensive: beginning with the harvesting of over 41,794 posts and undergoing multiple rounds of noise elimination to refine the data to the most relevant 4,423 commercial posts.
1. Enhanced Brand Perception: Insights revealed the brand as 'elegant' and 'good value for money', crucial for refining marketing strategies and consumer communication.
2. Direct Consumer Engagement: The identification of leads facilitated direct interactions with potential buyers, boosting conversion opportunities and enhancing customer relationship management. Identifying key influencers and approximately 513,000 potential customer leads, listening247 enabled the brand to strategically connect with both market movers and potential buyers.
Case Study
Carlsberg’s YouTube campaign faced challenges with a noisy dataset of 22,448 posts, plagued by duplicates and irrelevant content. listening247 employed a three-step noise elimination strategy, refining the data to 177 relevant posts, leading to more accurate insights, cost efficiency, and improved campaign performance.
Carlsberg’s “Standing up for a friend” YouTube campaign initially struggled with a noisy dataset of 22,448 posts, predominantly filled with duplicates and irrelevant content. Traditional tools inaccurately processed this noise, risking flawed campaign evaluations.
listening247 approached the problem with a structured three-step noise elimination strategy, utilising their proprietary solution, listening247. The first step involved the removal of 3,354 duplicate posts, instantly refining the dataset. Subsequently, a taxonomy of noise terms was created with the assistance of specially trained human curators, which facilitated the identification and removal of 18,890 irrelevant posts. By the end of the process, the dataset was distilled to 177 relevant posts, ensuring a high level of data purity.
Using engaging247, the brand enhanced its social media management with features like the smart compose for scheduling posts, a unified inbox for tracking and responding to comments, and easy access to comprehensive reports. The seamless integration between listening247 and engaging247 allowed the brand to target the right audiences with the content and offers that they were expecting.
1. Informed Decision-Making: With purified data, Carlsberg gained accurate insights into audience engagement, enhancing decision-making and strategic planning.
2. Cost and Time Efficiency: The precise analytics saved significant time and resources otherwise wasted on sifting through irrelevant data, boosting operational efficiency.
3. Enhanced Campaign Performance: The insights derived from high-quality data enabled Carlsberg to optimise its marketing efforts, leading to improved campaign efficacy and a stronger market presence.
4. Precision Analytics: listening247's proprietary solution, was pivotal, filtering out 99% of the noise and isolating 177 pertinent posts, starkly contrasting with the results from other tools and solutions.
Case Study
A global FMCG company sought to identify emerging trends in Vietnam's market using digital data. listening247 provided a solution by applying advanced AI models to analyse extensive online content, enabling the client to enhance marketing strategies, adapt swiftly to market changes, and make informed decisions through detailed insights and interactive reporting tools.
A global FMCG company needed to uncover emerging consumer trends in Vietnam’s dynamic market. They required a solution to interpret vast digital data—from blogs to social media—without direct consumer interaction.
To address these challenges, listening247 implemented a comprehensive social intelligence strategy using advanced AI models. The approach involved collecting data from a wide range of digital platforms using 60 generic keywords categorised into areas such as 'lifestyle', 'appearance', and 'career'. This data was meticulously annotated with information about brands, sentiments, and topical discussions.
1. Enhanced Marketing Strategy: The insights gained enabled the FMCG company to refine their marketing strategies, ensuring alignment with real-time consumer trends.
2. Agile Market Response: Access to the listening247 platform allowed the client to monitor changes and adapt quickly, maintaining a competitive edge.
3. Informed Decision-Making: The strategic insights led to better decision-making, driving effective consumer engagement and increasing market penetration in Vietnam.
4. Interactive Reporting Tools: listening247 provided an intuitive dashboard and detailed reports via a partner agency, facilitating seamless insight dissemination to the client.
Case Study
In a collaborative project with a telecom client, listening247 faced the challenge of integrating social listening analytics with existing consumer surveys amidst managing over 620,000 social media posts and aligning diverse Net Promoter Scores (NPS™) and Net Satisfaction Scores (NSS™). The project demanded advanced analytical techniques to sift through noise, categorise data effectively, and correlate consumer sentiment with market events.
The collaborative project between listening247 and a Telecom client sought to integrate social listening analytics with existing consumer surveys. A significant challenge was managing over 620,605 social media posts, with about two-thirds rendered irrelevant due to noise issues. Aligning the monthly NPS™ with variable NSS™ scores also presented complexities, necessitating an advanced analytical approach to synthesise these diverse data streams.
listening247 addressed these challenges by involving extensive social media listening over a six-month period and the deployment of sophisticated data curation techniques. This included the creation of a detailed hierarchical taxonomy to categorise the data effectively and the use of refined search term combinations to improve the relevance of the data collected. listening247's solution also involved superimposing NPS™ and NSS™ data over a calendar of market events thereby providing a dynamic analysis that captures the pulse of consumer sentiment and its impact on brand perception.
1. Enhanced Strategic Decision-Making: The integration of NPS™ and NSS™ allowed telecom client to gain a dual perspective on customer loyalty and social sentiment, offering a holistic view of brand health and consumer satisfaction.
2. Improved Customer Insights: The project uncovered specific consumer sentiments not captured in traditional surveys, enabling telecom client to tailor their customer engagement and service strategies more effectively.
3. Informed Operational Adjustments: The insights provided led to better-informed operational decisions, enhancing brand’s responsiveness to market changes and customer needs, ultimately strengthening their market position.
4. Dynamic Data Analysis: By overlaying NPS™ and NSS™ data with a calendar of market events, listening247 provided a nuanced analysis that captured real-time consumer sentiment fluctuations and their impacts on brand perception.
Case Study
A leading fashion brand in South Africa faced the challenge of understanding true consumer sentiment despite widespread online mentions. Traditional analytics fell short, prompting the brand to partner with listening247, which used advanced image analytics and deep learning to decode the visual narrative of the brand’s online presence.
A leading fashion brand in South Africa found itself facing a perplexing conundrum. Despite being mentioned across various online platforms, deciphering the true sentiment and perception surrounding its brand proved to be an uphill battle. Traditional text analytics fell short in capturing the richness and depth of consumer engagement, leaving the brand grappling with a fragmented understanding of its online presence.
Recognising the imperative to adapt to the evolving landscape of social media, the fashion brand turned to listening247 for a transformative solution. Leveraging listening247's cutting-edge image analytics capabilities, the brand embarked on a journey to unravel the visual narrative surrounding its products and brand identity. Through the deployment of advanced deep learning machine technology, listening247 provided the brand with the tools to decode the complexities of consumer-generated content, including images, videos, and other unstructured data.
1. Holistic Brand Perception: By harnessing image analytics, the fashion brand gained unparalleled insights into how consumers perceive and interact with its products online. From identifying key brand elements within visual content to discerning emerging trends, the brand now possesses a comprehensive understanding of its online image.
2. Strategic Agility: Armed with a newfound understanding of consumer sentiment, the fashion brand seamlessly integrated image analytics into its strategies. This strategic pivot not only unlocked new revenue streams but also positioned the brand at the forefront of innovation within the fashion industry.
3. Rapid Insights Generation: With listening247's image analytics solution, the fashion brand can now decode vast amounts of unstructured data in mere minutes. Whether it's analysing video clips, social media posts, or online community chatter, the brand gains actionable insights at an unprecedented speed, enabling agile decision-making and strategic planning.
4. Emotion Intelligence: listening247's proprietary AI models go beyond surface-level analysis, delving deep into the intricacies of consumer emotions. By dissecting both positive and negative sentiments expressed in visual content, the fashion brand gains a nuanced understanding of consumer sentiment, driving enhanced engagement and brand loyalty.
5. Intelligent Consumer Insights: With listening247's advanced machine learning models, the fashion brand gained unparalleled access to consumer behaviours, requirements, and preferences. Armed with this knowledge, the brand can tailor its marketing strategies and product offerings to resonate more deeply with its target audience.
Case Study
A leading beverage manufacturer faced the challenge of analyzing consumer discussions about dining out in Morocco amidst multiple languages and diverse data sources. Their objective was to uncover trends to strengthen their market presence.
A leading beverage manufacturer needed to decode consumer discussions about dining out in Morocco, navigating the dual challenges of multiple languages and varied data sources. Their goal was to understand trends that could enhance their market presence.
listening247’s strategy ensured a comprehensive capture and interpretation of consumer behaviour and preferences across different platforms. This annotated data was systematically organised into Excel tables, facilitating a seamless transfer of processed information to the client’s market research agency.
1. Strategic Insights: The client received a PowerPoint report filled with actionable insights, enabling them to tailor their strategy effectively.
2. Market Alignment: The insights provided allowed the client to align their offerings with consumer preferences, enhancing customer engagement.
3. Competitive Advantage: Armed with deep market understanding, the client could better position themselves in Morocco’s competitive dining sector, potentially increasing their market share.
4. Effective Collaboration: By collaborating closely with the client’s market research partner, listening247 ensured the insights were precisely aligned with the client’s strategic needs.
Case Study
A leading knitwear brand struggled with a low share of voice and ineffective social media strategies, despite having a positive brand sentiment. Challenges included identifying key influencers, managing sentiment, and distinguishing itself in a competitive market.
A leading knitwear clothing brand faced significant challenges in maintaining its competitive edge in the crowded knitwear market. Despite having a positive brand sentiment, the brand's share of voice was notably low, commanding only 4% of the industry's conversation. The company also struggled to identify key influencers, manage sentiment across various platforms, and differentiate itself from competitors. Furthermore, there were gaps in their social media strategy, particularly in content creation and resource allocation.
To address these challenges, the knitwear brand began with listening247 for brand health tracking and competitor benchmarking. This provided them with valuable insights into the social media landscape, identifying conversation drivers and gaps in the brand's strategies. The integration of DataVinci 3.0, a generative AI, offered deeper analysis and actionable suggestions, such as identifying key influencers and pinpointing negative conversation drivers of competitors that the brand could capitalise on.
Using engaging247, the brand enhanced its social media management with features like the smart compose for scheduling posts, a unified inbox for tracking and responding to comments, and easy access to comprehensive reports. The seamless integration between listening247 and engaging247 allowed the brand to target the right audiences with the content and offers that they were expecting.
The implementation of listening247 and engaging247 yielded significant benefits for the knitwear brand. The insights provided by listening247 enabled the brand to refine its social media strategy by focusing on the most impactful conversation drivers such as materials, sustainability, and size. The company identified key influencers to collaborate with, which amplified their reach and engagement on platforms like Instagram, their most active channel.
engaging247's unified inbox streamlined the brand's social media management, allowing for efficient tracking and response to follower interactions. The smart compose tool simplified content creation and ensured optimal post sizes across all channels, saving time and resources. Furthermore, the easy-to-access reports facilitated informed decision-making and strategy adjustments by the social media team.
Overall, the integration of these solutions helped the knitwear brand increase its visibility and engagement, resulting in improved competitive positioning and a stronger social media presence. The brand's ability to differentiate itself in the knitwear market was significantly enhanced, leveraging data-driven insights to drive strategic social media initiatives.
By utilising engaging247 and listening247, the knitwear brand transformed its social media strategy, achieving a comprehensive understanding of its brand health and competitive landscape, which ultimately led to increased brand loyalty and market share.
The festive season is upon us, and Christmas 2024 promises a celebration that blends cherished traditions with fresh, modern interpretations. Using listening247’s Social Listening and Analytics, we analysed over 50,117 posts from Twitter, TikTok, and Instagram between 5th October and 8th December. Keywords such as Christmas Gifts, Secret Santa, Christmas 2024, Holiday Season 2024, Gift Ideas, Holiday Shopping, Christmas Shopping, Festive Gifts, and Holiday Gifts were used to categorise posts.
These posts shed light on the key conversation drivers and trends that brands can leverage to create unforgettable holiday experiences.
Holiday cheer dominates online discussions, with a significant 68% (34,358 posts) expressing positive sentiment. Neutral conversations accounted for 29% (14,384 posts), while negative posts were low at 3% (1,375 posts). This overwhelming positivity prompts brands to connect with customers through festive messaging.
With 36,816 mentions, occasions emerged as the leading theme this holiday season. Consumers prefer shared experiences over material gifts, marking a cultural shift towards valuing time spent with loved ones.
This trend highlights the importance of framing campaigns around moments that matter for brands. Think event-driven promotions, experiential pop-ups, or even hosting holiday workshops to tap into the emotional core of Christmas. By aligning products and services with these experiences, brands can foster a deeper connection with their audience.
The allure of winter wonderlands - complete with sparkling lights, frosty landscapes, and cosy settings - is pulling audiences. This theme reflects a universal desire for escapism, nostalgia, and the joy of immersive holiday environments.
Brands can capitalise on this by transforming store displays into magical winter settings or curating themed collections inspired by the festive season. Even digital spaces can incorporate "winter wonderland" shopping experiences using AR-powered (augmented reality) winter effects.
Christmas carols with traditional melodies are being offered in interactive formats like virtual sing-alongs, community carol events, and life performances. Carols act as a unifying force, bringing families and communities together during the holidays.
Brands can harness this trend by sponsoring carolling events, incorporating carol-themed marketing campaigns, or creating playlists to complement the shopping experience.
In 2024, exceptional customer experiences are the ultimate differentiator. Shoppers seek seamless, personalised interactions at every touchpoint, from festive packaging to in-store ambience and online convenience.
This was never about selling products but building an emotional connection with the customer. Brands should focus on creating memorable experiences, such as personalised gifting services, festive loyalty rewards, or interactive in-store events that leave a lasting impression.
Sustainability continues to shape consumer behaviour. From eco-friendly holiday decor to gifts with purpose, shoppers are drawn to brands that reflect their values. Many are engaging in charitable giving, seeking ways to give back through donations and community drives.
Brands can respond by offering sustainable products, recyclable packaging, and charity collaborations. Highlighting eco-conscious initiatives in holiday campaigns resonates with consumers and strengthens brand loyalty.
The season is no longer confined to a single location. Many are opting for unique travel experiences, whether snow-covered retreats or tropical getaways. At its heart, this trend revolves around the desire to connect with loved ones, bridging geographical gaps to create cherished memories.
This opens up opportunities for brands to market travel-friendly products, such as compact gifts, travel kits, or digital gifting options. Partnering with travel companies or creating holiday content tailored to travelling audiences can further amplify relevance.
Christmas 2024 is a season of connection, creativity and purpose. Consumers are looking for experiences that resonate emotionally, whether through the carols, the escapism of winter wonderlands, or the shared joy of meaningful occasions.
The message is clear for brands: adapt to these evolving preferences by focusing on experiences, sustainability, and personalisation. With data-driven decisions, brands can create memorable and meaningful campaigns - ensuring Christmas 2024 is one to remember for customers and brands alike.
As Black Friday 2024 draws closer, retailers worldwide are gearing up for one of the busiest shopping days of the year. With billions spent in a single day, it’s an unmissable opportunity to connect with consumers, boost sales, and build brand loyalty. Thanks to listening247’s Social Listening and Analytics, we’ve uncovered the key trends and conversation drivers shaping this year’s Black Friday, helping retailers align with consumer behaviour and stand out in a crowded market.
Over 15,719 social media posts in English from platforms like Twitter, TikTok, and Instagram between 20 September and 15 November were analysed, to provide a wealth of data on what shoppers are saying, what they want, and how they feel about Black Friday 2024. Keywords such as Black Friday, Black Friday 2024, online shopping, in-store shopping, gift shopping, and Christmas shopping were used to track and categorise posts.
The buzz around Black Friday remains overwhelmingly positive:
Shoppers are excited, and motivated by the promise of unbeatable deals and the chance to save on holiday purchases. Positive sentiment is around tech deals, personalised promotions, and early access discounts, while negative sentiment is minimal, often tied to delivery delays or website crashes.
Using listening247, we identified the dominant topics shaping consumer conversations:
1. Technology – 12,881 posts: Tech products remain the crown jewel of Black Friday, accounting for nearly half of purchases. Televisions, laptops, gaming consoles, and smartwatches are the most wanted items. Major retailers like Amazon and Best Buy are expected to lead the charge with deep discounts, making this a key category for shoppers and brands.
2. Price – 9,313 posts: Pricing is a decisive factor in consumer decision-making. With financial pressures rising, shoppers are thoroughly comparing deals, looking for the best value, and waiting for Black Friday to make high-ticket purchases.
3. Discount Deal Promotions – 9,224 posts: Shoppers are actively seeking pre-Black Friday sales and exclusive member rewards. Brands offering early access or time-limited offers are seeing increased engagement, highlighting the effectiveness of targeted, exclusive promotions.
4. Gift Ideas – 7,116 posts: Black Friday is a prime moment for gift shopping. Consumers are turning to curated gift guides and social media for inspiration, with jewellery, apparel, and tech products topping the list of preferred gifts.
5. Shopping Platform – 2,094 posts: More than half of shoppers prefer online platforms to avoid crowds and enjoy convenience. Social media-driven e-commerce is particularly popular with Gen Z and Millennials, who rely on mobile-first shopping experiences.
1. Tech-Takeover: Electronics are projected to dominate Black Friday spending, driven by promotions from retailers like Walmart and Target. Smart home devices, gaming consoles, and high-end TVs are leading the wish lists. The influence of younger shoppers, particularly Gen Z and Millennials, is steering purchases online, where seamless digital experiences win the day.
2. The Power of Price: Pricing remains king. Consumers have set aside budgets specifically for Black Friday, emphasising its role as a cornerstone shopping event. The focus isn’t just on discounts but on true value, with shoppers scrutinising every deal to ensure it’s worth the spend.
3. Discount-Driven Decisions: Early-bird promotions and tiered discounts are becoming standard. Successful brands are going beyond basic sales by offering “spend-and-earn” rewards or bundling discounts to entice shoppers. This maximises short-term revenue and builds customer loyalty for future events.
4. Gifts Variety: Black Friday is the ultimate inspiration hub for gift-givers. Retailers curating well-targeted gift guides see higher engagement and conversions, as consumers look for meaningful yet budget-friendly options.
Black Friday 2024 provides a golden opportunity for retailers to connect with their audience through strategic pricing, tailored promotions, and a strong digital presence. Here’s how to capitalise on these insights:
Black Friday 2024 is more than just a sales event—it’s a cultural moment that reflects shifting consumer priorities and behaviours. By understanding what shoppers want, why they’re excited, and how they plan to spend, brands can tailor their strategies to exceed expectations. Thanks to listening247’s powerful analytics, retailers have the insights they need to navigate this high-stakes season and come out on top.
Let’s make this Black Friday a win for your business and your customers.
“Pan metron ariston” (παν μέτρον άριστον) is a quote in ancient Greek which was coined by Kleovoulos o Lindios in the 6th century B.C. and means “everything in moderation”. Some believe that the original quote was “Metron Ariston” which means “moderation is best”. Whatever the quote, ancient Greeks believed that you should live your life choosing the mean and avoid the extremes on either side, as much as possible.
Talking about extremes, I have always been fascinated by continua, I think it’s because of the order they bring to chaos and complexity. Almost every ideology or idea that matters in life, can be expressed on a continuum. A continuum has two extremes - let’s think of them as black and white with many shades of grey in between.
Here are two more official continuum definitions which are quite similar:
I do not consider myself qualified to improve on wisdom that transcended centuries (26 centuries since Lindios said “everything in moderation”) but I do have an opinion about quotes that include the words “everything” or “nothing”, “always” or “never”; incidentally these two pairs of opposite words can be the extremes of two continua; very few things are absolute, this is why the quote “everything in moderation... even moderation” may be just short of genius.
There is no doubt that being an extremist has mainly negative connotations: a fascist, a racist, a sexist, a religious fanatic, a communist… There are also some other examples like “feminist” or “atheist” that would create a debate with certain groups - as to whether they have negative connotations - that I am cowardly avoiding to mention at this time (see how I did this :)?).
Let’s first review a few random continua to familiarise ourselves on what they could look like, and after that we will go ahead and discuss the usefulness of looking at an issue through the lens of a continuum. Take the eating continuum below for example, isn’t it amazing how many types of diets there are? It has an impressive 13 elements in addition to the 2 extremes; a total of 15 elements. Kangatarian (I bet you can guess what these people eat :)) is the one that cracks me up with cannibal being a close second! I am also intrigued by how vegetarians managed to be the mean nowadays, they have come quite far from being an extreme in the not too distant past. And in case you are not familiar with ahimsa fruitarians, they only eat fruit that falls off a tree and they call pulling a carrot from the earth murder!
The God continuum with probabilities on God’s existence is not as harmless as the eating one; it is one that has been the basis for so many debates, civilised and uncivilised - and when I say uncivilised I mean the killing type if you think of the Crusaders (even though in their case it was more of a “my God is better than yours” rather than about its existence).
The selfishness continuum comes straight out of the Vedanta Treatise, a Hindu approach to life.
The colour coding means red is bad and green is good for most people.
Disclaimer: this does not always represent the author’s opinion. We will discuss more the groupings or segments of continua in the next chapter.
The continuum below communicates a thesis of mine that most people disagree with. I believe that being a patriot is the beginning of a proverbial “slippery slope”. It could progressively lead to someone becoming a nationalist and then a jingoist which is what you have to be to vote for Brexit or for someone like Trump.
The nationalism continuum can be integrated with the selfishness one at the point of loves all humans which is another way to say world citizen. One can then make interesting connections and draw conclusions about love and nationalism.
Those of you who have read other articles of mine may be wondering what all this has to do with market research, social intelligence, customer insights etc. Well the nice thing about continua is that you can conjure one out of nothing about almost anything. Case in point, digital transformation is something closer to home for a company with a name like ours; listening247. It was a sensible name 10 years ago to communicate specialism in digital market research; today however, when almost everything is digital, a name like this loses its meaning. It’s like calling a car a horseless carriage when in this day and age it is quite obvious that a car does not need horses to move (unlike the 1920s when Ford T1 was launched). But I digress... if you replace physical with ‘brick & mortar’ then this continuum becomes about retail, and if you replace it with ‘analogue’ it could be about equipment.
For market research, physical could mean in-person or telephone interviews, whilst digital means online surveys or unsolicited opinions found on social media using social listening tools.
Nothing easier than creating a 5 point continuum. The one below is about ways of gathering the opinions of customers and other stakeholders. Asking questions refers to surveys and focus group discussions whilst listening refers to unsolicited posts of people online. The discipline of harvesting these posts and analysing them is what we call social intelligence and it is mainly based on machine learning models that annotate posts for topics and sentiment in an automated way.
When you take some time to absorb the 6 examples shared above, you will realise that not all continua are created equal.
Here are some ways to differentiate them:
1. both extremes are bad (ahimsa fruitarian AND cannibal)
2. both extremes are acceptable (asking AND listening)
3. One extreme is really bad the other is really good (fascist Vs world citizen)
4. The mean is a combination of the extremes (asking & listening)
5. The mean is just a standalone option that has nothing to do with the extremes (vegetarian)
So what are they good for? They are philosophical tools that can help organise thought, clear the fog, visualise relationships, pinpoint and explain movements and trends.
Ancient Greeks believed that you should live your life choosing the mean and avoid the extremes on either side, as much as possible. Is this a good principle to follow though? If we consider the various types of continua described in the previous chapter sometimes the best choice is to adopt one of the extremes, sometimes it is indeed the mean like our ancient progenitors preached.
Thinking about moderation, can one be too much of a world citizen or too loving for all creatures?
When a continuum describes progress over time it is more likely that the most recent extreme is the best place to be. Even so, living it in moderation is probably a sound piece of advice.
I do subscribe to the notion that life is not black or white, it is mostly grey. Most of our lives are lived in the grey, only very few of us live on the extremes - sometimes by choice, but mostly not. Extremists must always be on edge, in contrast to leading a happy life, laid back, going with the flow, accepting the things they cannot control. Do let me know how you feel about continua and “pan metron ariston” @listening247_CEO or via email.
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‘How does market research rank on usefulness for human life’
In an increasingly digital world, social media platforms have transformed the way individuals connect, share information, and express opinions. Banks can leverage the power of social media listening to manage loan default risks effectively. By gathering and analysing online posts about the companies to which they have extended loans, banks can conduct continuous commercial due diligence and identify early warning signals when debtors encounter financial difficulties. This post explores how banks can utilize social media listening as a strategic tool to proactively manage loan default risks and enhance their risk management practices.
Social Listening & Analytics involves monitoring and analysing online conversations, mentions, comments, and reviews across various social media platforms. It allows banks to extract valuable insights and gain real-time information about the financial health, market reputation, and business activities of the companies they have extended loans to. By employing machine learning for natural language processing techniques, banks can effectively identify potential red flags indicating financial difficulties and anticipate loan defaults.
A. Proactive Risk Assessment:
Traditional due diligence processes primarily focus on pre-loan assessment, often failing to capture evolving risks that borrowers may face after obtaining the loan. By incorporating social media listening into their risk management framework, banks can conduct continuous commercial monitoring in addition to their due diligence during the loan underwriting or credit extension phase. This enables them to monitor ongoing developments, industry trends, and financial indicators related to their borrowers, providing a more comprehensive risk assessment. These non-traditional indicators of credit quality and borrower’s abilities to service their debts and obligations give a much fuller picture than simple financial statements which are backward looking and often don’t provide the full story. This alternative data can also be a better predictor of borrower behaviour than historical financial statements.
B. Real-Time Insights:
Social media platforms act as virtual marketplaces where individuals freely share their experiences, opinions, and concerns. By monitoring online posts about borrower companies, banks can gain real-time insights into their operations, financial stability, customer sentiment, and market perception. Any notable shifts, negative sentiments, or concerning patterns identified through social media listening can serve as red flags, prompting banks to investigate further and take necessary actions. As we have seen recently with the collapse of Silicon Valley Bank and First Republic Bank in the US, depositor sentiment played a striking role in their demise. Due to adverse online sentiment that spread very rapidly, customers and depositors caused a digital run on the bank that had never been seen or experienced before. In the case of Silicon Valley Bank, deposits were leaving at the rate of $1 million per second for 10 hours (or $41 billion).
A. Detecting Financial Difficulties:
Social media listening allows banks to identify early warning signals of potential financial difficulties faced by their borrowers. By analysing online conversations, comments, and reviews, banks can detect signs of operational challenges, supply chain disruptions, declining customer satisfaction, or negative market perception. These signals can help banks proactively engage with borrowers, assess their financial health, and take appropriate measures to prevent loan defaults.
B. Amplifying Existing Risk Indicators:
Social media listening augments traditional risk indicators with additional insights derived from user-generated content. For example, a decline in positive sentiment towards a borrower company may coincide with a decrease in revenue, an increase in customer complaints, or a deteriorating market position. By integrating social media listening into their risk management framework, banks can enhance their ability to identify and act upon early warning signals, thereby mitigating loan default risks.
“Effective Early Warning Systems (EWS) reduce loan loss provisions by 10%-20% and required regulatory capital by 10%”
Galytix paper in association with PWC
A. Leveraging Advanced Tools:
To effectively analyse vast amounts of online data, banks can employ machine learning and sentiment analysis tools. These tools enable banks to filter and categorize information, identify patterns and trends, and extract meaningful insights. By leveraging sentiment analysis, banks can assess the overall market sentiment towards borrowers and gauge the impact of external factors on their financial health.
B. Enhancing Risk Models:
Integrating social media listening insights into risk models can strengthen banks' loan default risk assessments. By combining traditional financial indicators with sentiment analysis and social media data, banks can improve the accuracy and predictive power of their risk models. This holistic approach allows for a more comprehensive evaluation of borrower creditworthiness and provides a deeper understanding of the potential risks associated with loan defaults.
A. Privacy and Data Protection:
As banks engage in social media listening, it is crucial to prioritize data privacy and protection. Banks must ensure compliance with relevant data protection regulations and implement robust security measures to safeguard the information collected. Respecting user privacy, obtaining consent, and anonymizing data if necessary are essential steps to maintain ethical practices. This is of particular importance when used for due diligence and for the monitoring of individuals and their transactions, as is required of banks by Know-Your-Customer rules and regulations imposed upon them by the authorities.
B. Noise and Information Overload:
The sheer volume of online information can pose challenges in effectively filtering and interpreting relevant data. Banks can employ sophisticated filtering techniques and analytical tools to address information overload. Machine learning algorithms and natural language processing can help identify key topics or themes, prioritize relevant content, and provide actionable insights to manage loan default risks efficiently.
By harnessing the power of social media listening, banks can conduct continuous commercial due diligence and effectively manage loan default risks. Monitoring online posts about borrower companies enables banks to gather real-time information, detect early warning signals, and anticipate financial difficulties. However, banks must navigate ethical considerations, prioritize data privacy, and address information overload challenges. When implemented strategically, social media listening empowers banks to proactively manage loan default risks, enhance risk management practices, and ensure more informed lending decisions.
“Banks that fail to improve their EWS will also face significant regulatory pressures. The European Central Bank (ECB) has highlighted the huge variation in the quality of early warning systems and how credit assessment at a micro as well as macro level is core to risk management and processing.”
Galytix paper in association with PWC.
In today's fiercely competitive business landscape, companies are constantly seeking ways to gain an edge over their rivals. Among the various capabilities that contribute to success, unstructured data analytics capability stands out as indispensable for survival in the face of intense competition. This post explores the significance of text and image analytics specifically and argues that no company can thrive without harnessing the power of these capabilities. There is of course also audio and video analytics to consider but once the tech is available to analyse text and images the rest can be handled with voice-to-text and image-to-text technology. More details on this below.
1. Uncovering Insights: Text and image analytics enable companies to extract valuable insights from vast amounts of textual and visual data. By employing sophisticated algorithms and machine learning techniques, businesses can analyse customer feedback, reviews, social media posts, and other textual data sources. This allows them to identify emerging trends, preferences, and sentiment patterns, leading to informed decision-making and strategic planning. Similarly, image analytics empowers companies to understand visual content, enabling them to recognize brand logos, product placements, and consumer behaviour from images shared on social media platforms. The ability to uncover such insights provides a competitive advantage by allowing businesses to stay ahead of the curve.
2. Enhancing Customer Experience (CX): Text and image analytics play a crucial role in enhancing the customer experience, which is a key differentiator in today's market. By leveraging these capabilities, companies can gain a deep understanding of customer needs, preferences, and pain points. Through sentiment analysis of calls, chats, emails and social media posts, businesses can assess customer satisfaction and promptly address any concerns, improving overall customer experience and loyalty. Furthermore, image analytics can identify visual cues and sentiment from images shared by customers, helping companies gain insights into how customers engage with their products or services. By proactively addressing customer needs, businesses can establish a stronger foothold in the market and build long-lasting relationships.
3. Competitive Intelligence: Text and image analytics applied on publicly available information online also serve as powerful tools for competitive intelligence. Companies can monitor competitor activities, track mentions, and analyse customer sentiment related to competitors through textual data. This information provides valuable insights into competitor strategies, product offerings, and market positioning. Similarly, image analytics can help identify visual elements associated with competitors, such as logos or brand imagery, aiding in assessing market share and brand perception. Armed with this knowledge, businesses can adjust their own strategies, differentiate their offerings, and better position themselves to gain a competitive edge.
4. Operational Efficiency and Risk Mitigation: Text and image analytics contribute to operational efficiency by automating processes that would otherwise be time-consuming and error prone. For instance, text analytics can automate the categorization and tagging of large volumes of textual data, reducing manual effort, and improving data accuracy. Similarly, image analytics can automate the identification and classification of visual content, streamlining tasks such as quality control or identifying counterfeit products. By improving operational efficiency, companies can reduce costs, optimize resource allocation, and respond quickly to market demands, ensuring survival in a competitive environment.
At listening247, we leverage voice-to-text and image-to-text technology to efficiently process all forms of unstructured data through our social listening and analytics platform platform. This enables us to label the data with custom machine learning models, ensuring the highest possible accuracy, regardless of the original language. In contrast, some vendors offering multilingual text labelling solutions rely on translating everything to English before labelling, which is not an optimal or accurate approach.
Lately, many individuals have inquired about how the listening247 sentiment and topic labelling approach compares to GPT-4 or Bard. The answer is: the listening247 approach is unequivocally better. For a less biased and more objective perspective, I encourage you to refer to this paper. Here is an excerpt from the paper summary:
“The preliminary study shows that ChatGPT and GPT-4 struggle on tasks such as financial named entity recognition (NER) and sentiment analysis, where domain-specific knowledge is required, while they excel in numerical reasoning tasks.”
This subject deserves its own article with a proper gap analysis between LLMs and the proprietary and custom ML models that listening247 creates.
Text, voice and image analytics have become indispensable capabilities for any company striving to survive and thrive amidst fierce competition. The ability to extract insights, enhance the customer experience, gain competitive intelligence, and improve operational efficiency makes these capabilities vital for success. Companies that neglect to harness the power of unstructured data analytics will find themselves at a significant disadvantage, missing out on crucial insights, falling behind competitors, and failing to meet evolving customer expectations. Therefore, to remain competitive in the modern business landscape, organizations must prioritize the adoption and utilization of text, audio and image analytics to secure their long-term survival.
This statement, which I have shared numerous times in previous articles, encapsulates the essence:
“Over 90% of all human knowledge recorded throughout history exists in the form of unstructured data. If your company solely focuses on analyzing and comprehending structured data, it implies that you are utilizing less than 10% of the available data to inform your decision-making processes.”
What exactly is AI?
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For the first time, listening247 unveils a breakthrough in automated targeting and social media content creation, powered by Gen AI for agencies.
Join Michalis A. Michael, CEO of listening247, and Marcus Harding, Founder of Deviceful as they discuss how Gen AI shortens the marketing content creation cycle from weeks to minutes at scale!- revolutionising the way agencies create and publish content.
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listening247 is proud to collaborate with ESOMAR, the global professional association for market research and analytics community, to bring an online course addressing the evolving market research sector.
Offered through the ESOMAR Academy, this course, "Unstructured Data: Unsolicited Customer Opinion – How Social Media Listening and Gen AI is Changing the Market Research Landscape," is now available on-demand to ESOMAR members and non-members, respectively.
The course explores the application of generative AI for automated content creation, precise online micro-audience targeting, and the effective integration of unsolicited customer opinion with established research methodologies.
This course is ideal for insights professionals from market research agencies and client-side organisations, marketing professionals seeking deeper customer understanding, and business development professionals looking to offer these solutions.
Join us to master:
The course is structured across three sessions:
Our speakers:
The participants will receive in-depth content, direct trainer contact for support, and a certificate upon completion. This training is available on-demand for 12 months, offering flexibility.
Register now on the ESMOAR website and start anytime: link here.
Register Now: Click Here
Struggling to keep up with content demands? Feeling invisible in crowded feeds?
It’s time to leave behind manual campaign creation and switch to smart, AI-powered brand visibility.
Join listening247’s CEO, Michalis A. Michael, and a soon-to-be-announced guest speaker in this exclusive webinar to discover how automated targeting and content creation are transforming how B2C brands appear online.
This webinar is made for brand leaders, marketing directors, social media managers, and digital teams working within consumer-facing businesses across retail, beauty, tech, FMCG, fashion, hospitality, and more. If your job is to grow your brand’s sales, voice, relevance, engagement and visibility in a noisy market, this session is built for you.
Rather than replacing creative or marketing roles, this AI-driven approach becomes a force multiplier, freeing up your team’s time, removing production bottlenecks, and accelerating execution. You’ll be able to launch high-quality, targeted campaigns in seconds, not weeks. Your message lands right where conversations are happening, with the right visuals and copy, automatically tailored for people already engaging with your brand or actively searching for products like yours.
In just 45 minutes, we’ll show you how Gen AI can:
Whether you're building a challenger brand or scaling a household name, this is your edge: Faster campaigns. More visibility. Deeper engagement. More sales.
And if you work with agencies, you'll be pleased to know: The same automation agencies use to drive efficiency, profitability, and scale is now available directly to you.
Date: 29/05/2025
Time: 1:30 PM BST
Speakers: CEO of listening247 + Guest Expert (TBA)
What You’ll Get: Expert insights, live demo, real use cases
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listening247 In the Press
London, UK – 24/03/2025 – Which luxury brands are setting the internet on fire, and which are fading into the background? The listening247-Glion Luxury Brand Index (LBI) is here to answer just that. This cutting-edge index unveils how the world’s top luxury brands rank based on online conversations, engagement, and consumer sentiment—offering an unprecedented look at a digital brand equity equivalent in the luxury space.
This is a very different approach to other attempts to rank luxury brands using financials, fundamentals or survey questions to consumers.
The l247-Glion LBI is best described as the difference between the balance sheet value of a brand and its market capitalisation.
Over a nine-month period (29th March 2023 – 1st January 2024), unsolicited online posts and their metadata were collected globally in English. These posts spanned Instagram, TikTok, X, news sites, forums, blogs, and YouTube, capturing organic brand mentions, consumer sentiment, and engagement metrics. Additionally, Google search trends for each brand were analysed to gauge public interest. Advanced Natural Language Processing (NLP) and AI-driven analytics filtered and refined the data to eliminate noise and ensure only relevant, high-value insights shaped the index.
To quantify brand strength, the index examined key variables such as post volume, engagement (likes, shares, comments), Net Sentiment Score™ (NSS), conversation topics, brand reach, and search frequency. The findings reveal not just popularity but also how deeply brands connect with audiences and drive conversations that matter. The LBI was validated using daily stock prices of the brands included for the same period as the posts collected.
After meticulous analysis, the top luxury brands ranked by the listening247-Glion LBI are:
Notably, Dior emerges as the digital powerhouse, boasting the strongest engagement, brand advocacy, and consumer sentiment. Meanwhile, heritage brands like Louis Vuitton and Hermès, though dominant in sales, rank lower in online engagement compared to more trend-driven brands like Balenciaga and Givenchy.
The listening247-Glion Luxury Brand Index doesn’t just measure popularity—it predicts future success. In an era where digital presence defines brand strength, luxury houses must prioritise online engagement, consumer sentiment, and cultural relevance to stay ahead.
As the index evolves with continuous data updates, it will serve as the definitive barometer for luxury brand health, offering brands, investors, and industry leaders a strategic tool to navigate the digital-first luxury market.
Want to know how your brand stacks up? Contact us for a deep dive into your brand’s performance and learn how to leverage these insights for competitive advantage.
Original Source: UK Herald Tribune
listening247 In the Press
London, UK – 26/02/2025 – Luxury brands, historically measured by traditional benchmarks, are now entering a new era that demands evolving metrics. In collaboration with the esteemed Glion Institute of Higher Education, listening247 has developed the listening247-Glion Luxury Brand Index (LBI) that brings a fresh perspective to online brand performance measurement in the luxury market.
This innovative index is built on unsolicited customer opinions and behaviour collected from public online data, offering a timely, authentic reflection of consumer sentiment. This method ensures a dynamic, data-driven approach to luxury brand analysis, setting it apart from existing indices.
Unlike traditional metrics focusing on financial performance or surveys, this composite index uses advanced mathematical and statistical methodologies to select digital media metrics based on millions of online posts and assign their respective weights. The result is a balanced, evidence-based framework that evaluates brand equity and performance.
The luxury goods market—including apparel, accessories, watches, jewellery, and eyewear—has experienced consistent growth over the past decade. Yet, many existing indices fail to capture the full scope of brand influence. While indices like the S&P Global Luxury Index focus on financial metrics, others like the Altagamma Social Luxury Index incorporate non-financial factors such as limited scope social presence, reach and engagement, gaps remain in providing a holistic understanding of brand desirability.
The listening247-Glion Luxury Brand Index fills these gaps by leveraging nearly all available unsolicited consumer data to track brand trends, preferences, and sentiment. This index is valuable for all brand stakeholders—investors, analysts, policymakers, vendors, and customers—by delivering precise, current, and actionable insights.
Data was gathered across platforms, including Instagram, TikTok, X, news articles, forums, blogs, and video comments from 29th March 2023 to 1st January 2024 in the English language
The index includes 20 of the world’s leading luxury brands, selected based on their prominence in reputable rankings - they are shown in alphabetical order:
The listening247-Glion LBI offers a new approach to understanding the luxury landscape. By focusing on online consumer conversations and behaviour, it offers a time bound reflection of brand desirability and cultural relevance. This methodology provides all stakeholders the tools to evaluate opportunities, manage risks, and make informed decisions in an evolving market.
The rankings of the 20 luxury brands included in the listening247-Glion LBI will be revealed soon. This ranking will shed light on the latest trends and performance metrics in the luxury industry.
Original Source: UK Daily News Online
Michalis A. Michael, CEO of listening247 and Dr. Antonina Santalova, GIHE Academic Dean will be attending the prestigious Monaco Symposium on Luxury 2025, where they will present groundbreaking research on luxury brand valuation. Held from April 1-3, 2025, this elite international event bridges academic expertise and industry leadership in the luxury sector, fostering high-level discussions and knowledge-sharing.
On April 3rd, at the International University of Monaco (IUM), Michalis and Antonina will present Session 15: Bridging Brand Value Perspectives: A Novel Approach to Measuring Luxury Brand Intangible Value Through Unsolicited Consumer Data. (Michalis A. Michael, Paul Hounnaklang, Antonina Santalova, Nicos Rossides, Jelena Krsman.)
At the symposium, Michalis and Antonina will introduce the listening247-Glion Luxury Brand Index (LBI)—an innovative benchmark co-developed with the Glion Institute of Higher Education to transform how luxury brand performance is measured.
Unlike traditional luxury brand rankings that rely on financial data, surveys, or expert opinions, the LBI harnesses timely unsolicited consumer conversations from across the digital landscape. By leveraging AI-powered analytics and advanced statistical methodologies, the index brings a fresh perspective to online brand performance measurement in the luxury market.
The luxury sector has long struggled with quantifying brand desirability beyond sales figures. Existing indices offer partial insights but fail to capture the holistic impact of consumer sentiment. The LBI fills this gap by aggregating millions of data points from platforms like Instagram, TikTok, X (Twitter), news articles, blogs, and online forums.
The LBI ranks the world’s top luxury brands based on their digital footprint and online consumer sentiment. The latest rankings reveal some interesting insights:
The findings suggest that while heritage brands retain value, trend-driven brands that engage effectively with digital audiences are shaping the future of luxury. The LBI is validated through its correlation with stock price fluctuations, reinforcing the impact of brand sentiment on market success.
As luxury brands navigate an increasingly digital-first market, the listening247-Glion Luxury Brand Index offers a crucial strategic tool for brand executives, investors, and analysts. This timely data-backed insights into brand desirability and influence, helps stakeholders anticipate trends, mitigate risks, and drive informed decision-making.
Register Now: Link to register
Discover how to leverage Social Listening & Analytics for Customer Insights through three illuminating case studies from Latin American projects. Unlock the transformative potential of 'A Journey to Artificial Intelligence' ebook, learning to decipher accurate information across languages and harness untapped capabilities in social listening analytics. Explore the limitations of conventional methodologies and the critical importance of precision in social insights. Download now to embark on a journey revolutionizing your understanding of artificial intelligence.
Ebook Highlights:
1. Find out how to uncover accurate insights in any language;
2. Discover the untapped power of social listening analytics;
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5. See the three case studies on the use of Social Listening in LATAM.
Ideal for:
1. Any market deparment and organisations who want to enhance their market research activities by introducing an additional source of data.
2. Market research agencies who want to learn about the importance of accuracy when it comes to social insights in LATAM.
P.S. Have questions about the ebook? Contact us at: info@listening247.com. We're happy to help!
listening247 In the Press
listening247 has been recognized by Welp Magazine as one of the Top Predictive Analytics Companies and Startups in the UK. This prestigious list highlights listening247’s excellence in the field of predictive analytics, placing it among other influential and innovative companies such as Cazana, OAG Aviation, Swift ERM, and Streetbees. This acknowledgment underscores DigitalMR’s significant contributions and advancements in the industry.
Welp Magazine, an esteemed online publication, focuses on profiling companies and startups across various sectors including technology, innovation, software, design, and management. By covering these dynamic fields, Welp Magazine provides valuable insights into emerging trends and leading players, helping readers stay informed about the latest developments and breakthroughs in the industry.
Original Source: Welp Magazine
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listening247 In the Press
listening247 recently published a report revealing that, over the last quarter, the Countess of Wessex, Princess Anne, and Camilla were the most positively talked about Royals in the UK, while (unsurprisingly to some) Prime Minister Boris Johnson was one of the UK’s most unpopular politicians – and his cabinet was in the doghouse as well! How do you interpret the results and what insights do they give us into the mindset of the British public?
First of all, it’s worth quickly noting the main KPIs used to rank the subjects of this research:
1. Share of Voice (SoV) – which is calculated based on the total volume of posts for each subject. The total number of posts within a category was used as the base to calculate the shares.
2. Net Sentiment Score (NSS) a metric coined and trademarked by listening247, simply calculated as follows: share of positive sentiment minus share of negative sentiment.
Under many circumstances, a high SoV is great news – but not for Boris Johnson, whose Net Sentiment Score (NSS) rests at -5%. This means, as the graph below indicates, that more online posts about Johnson were driven by negative sentiment than by positive, giving a strong indication of the public’s mood towards their Prime Minister.
Fig 1. NSS Politicians Dec-Mar
Johnson isn’t alone in his negative NSS status. In fact, of all current Cabinet members, only Steve Barclay has a positive score – albeit with a low volume of only 22,000 posts when compared with Johnson’s princely 10 million.
As for the rest, the numbers speak for themselves. Sajid Javid continues to have the worst NSS, with -26% up from -34% during the previous 3-month period. Rishi Sunak sunk from one of only 4 politicians with positive NSS during the last period to the 2nd from bottom with -19% NSS. Priti Patel improved her position from second to last and -24% to an impressive 21 percentage points increase to -3% (still negative, though).
What kind of conclusions might we draw from these results?
For one thing, this analysis of sentiment might give an indication of who may (or may not) be in the running for any prospective Tory leadership battles. Liz Truss is often named as a possible leadership hopeful, for example, but our analysis shows that Truss is perceived twice as negatively as Johnson, suggesting that she’s not currently an optimal candidate.
Setting our sights a little higher, it’s also worth noting that this data was gathered before the local elections – and I think it’s no coincidence that this largely negative perception of the leading Tories was swiftly followed by a loss of around 400 council seats.
In other words: analysis that involves every data source has a great deal of predictive potential.
In terms of SoV, Prince Andrew overtook Meghan Markle and the Queen who had the highest SoV during the last period – mainly, no doubt, due to the court settlement. Megan is now 3rd with the Queen having surpassed her by 10 percentage points. Now the world makes more sense!
Sophie (+59%) Anne (+56%), and Camilla (+47%) continue to have a higher NSS than the Queen; added to the list of royals with better NSS than the Monarch are Kate, Meghan, Charles, Harry and William in this order. These results might challenge our assumptions that the Queen is the be-all and end-all of Royal discussion – in fact, the Queen’s NSS dropped from 55% to 27% in this period.
Fig 2. NSS Royals Dec-Mar
Unlike traditional polls and surveys, which rely on small sample sizes and can be prone to inaccuracies, listening247's report uses social intelligence technology to gather and analyze unstructured data from a wide range of online sources. By collecting posts from platforms like Twitter, Facebook, blogs, and forums, as well as internal data from clients, the analysis captures unsolicited, honest opinions from the public. This comprehensive approach offers a more accurate reflection of public sentiment, free from the biases and limitations of conventional polling methods.
Sentiment analysis only sprang into existence at the beginning of the last decade.
From a place of obscurity twelve years ago, however, its rise has been meteoric. Sentiment analysis has truly jumped into the light in this decade – and it’s unquestionably here to stay.
The process is best known for its application in a social media context, but it can be equally useful when applied to other customer feedback sources such as call centres, private messages, emails, answers to open ended questions in surveys, and many more sources besides.
In fact, any source of unstructured data can be considered grist to the mill of sentiment analysis – especially when it’s backed by robust artificial intelligence (AI).
With this AI capability, CXM professionals working for brands can now know with certainty what each and every customer interaction with their brand means and represents.
Frankly, because we haven’t had the technology.
Today, however, machine learning and AI has become more mainstream and accessible. Without AI, the only way to understand unstructured data was to read, listen to, or view every single piece of data – which is an impossible task, of course, when you reflect on the millions of posts, calls, chats, and other data needed to gain a truly universal and comprehensive view of customer opinion.
In a word: no.
For one thing, UK personal data protection laws are fairly robust – as anybody who undertakes GDPR compliance training can attest.
Besides, the strength of our analyses is that the opinions we find and work with are volunteered by their posters. This doesn’t just have good implications for the reliability of the data – it also means that this is data that people don’t mind being publicly available.
Of course, we should all take responsibility and think carefully about what we post in public online spaces – but this is just good general advice which would apply irrespective of any advances in social intelligence technology.
There are many use cases whereby machine learning and AI is applied in order to decipher big unstructured data. When it comes to companies like Bloomberg, they see an application for social intelligence as a means of factoring alternative data into trading and investment decisions for their hedge fund clients. Agencies, on the other hand, use social intelligence in order to discover insights based on unsolicited customer opinion for the brands of their big corporate clients. More broadly, of course, literally all companies want to optimise their customer experience by discovering and fixing customer pain points early and efficiently by listening in to all the customer interaction in calls and chats.
In the next couple of decades there are at least two areas where we will see wonders:
Tracking net sentiment scores for public figures, like politicians and royals, on a frequent basis is crucial. As technology continues to evolve, traditional polls may become obsolete, replaced by more accurate and comprehensive methods of gauging public sentiment. For businesses, tools like the listening247's social presence score offer valuable insights, enabling brands to benchmark against competitors and identify the most impactful elements of their campaigns. This approach ensures a clearer understanding of what resonates with the audience and what falls short. Origal Source: Global Banking & Finance Review
listening247 In the Press
Text analytics is a transformative tool for businesses, offering the ability to capture and analyze customer opinions across multiple languages. As British executives become more aware of the vast amounts of unstructured data surrounding their businesses, the language-agnostic capabilities of AI in text analytics emerge as a critical, yet often overlooked, component. Unstructured data, which makes up the majority of available information, provides invaluable insights into customer experiences. Leveraging AI for multilingual text analytics enables companies to access and understand customer feedback from diverse sources, ensuring a comprehensive view of customer sentiment and priorities.
The basis for AI-powered text analytics is a combination of machine learning (ML) and natural language processing (NLP).
ML is the way to produce AI designed to mimic human learning. While conventional programming requires the implementation of rules created by humans, ML uses data analysis to learn hugely complex patterns that can be used to infer – making ML powerfully adept at solving problems and performing complex tasks.
NLP, meanwhile, pertains to processing language – in fact, it can be understood as one of the complex tasks that ML supports.
The uses for NLP in this context are many and varied. It can be used for simpler goals, like working out how often a given term or word appears in a text. Alternatively, it can take on the tougher challenge of determining the sentiment – or even emotion – of a given piece of text.
Obviously, both the former and the latter have great utility for businesses who want a detailed understanding of all available customer opinion.
These uses of NLP allow companies to assess enormous quantities of data to discover how often their brand is being talked about online or offline – and whether it’s being perceived positively, negatively, or in relation to a range of more nuanced sentiments.
Crucially, as mentioned above, the power of this approach rests in its capacity to encompass all customer opinion – text analytics work with every opinion, rather than a sample or selection.
In order to realise this goal, however, you can’t limit the language in which a given opinion is expressed – you need your AI to be entirely language agnostic, especially if you are a multinational organisation.
We achieve this by using both unsupervised and supervised ML. Supervised ML means that the algorithms involved are ‘trained’ by human beings who annotate training data, allowing the AI to do a much better job than humans when it comes to narrow tasks involving large quantities of data – also known as Big Data.
To ensure that all languages are catered for, we make use of a network of some 300 native speakers of various languages who read, understand, and manually annotate unstructured data – establishing, for example, whether a given Tweet is positive or negative, its topic, the presence of sarcasm, or even the customer journey stage implied by the content of an email or chat message thread.
Once an AI has been trained in the native language (without translating into English and using an ML model for English) to very accurately achieve its goals – whether to establish sentiment or identify the presence of a topic – the results can be easily visualised in English, unlocking the accumulated opinions of all customers for CX professionals, retention managers, and so on in a language they can understand.
On top of this, AI precision can continuously increase. Precision can be measured when a small sample of tweets, for example, are annotated by a human with a certain sentiment. We’re seeing 80-90 percent or more match the algorithm, irrespective of the language in which the tweets were written.
Bearing in mind the subjective nature of expressing sentiment, this demonstrates just how formidable these AI techniques have become.
I began this piece by pointing out that UD is everywhere, and that it represents an opportunity to get a sense of all customer opinion – as opposed to polls and surveys which, by definition, can only provide customer opinion based on a sample.
In order to truly achieve this unlimited degree of access into consumer opinion, however, multinational companies don’t just need to engage AI experts and their tech for the English language – they also need to make sure their AI is trained on data across all pertinent languages with the same high precision as for English.
In so doing, text analytics become not only source agnostic, but language agnostic too – allowing business leaders to confidently assert that their understanding of their customers’ views, pain points, and gain points is detailed, precise, and unprecedentedly comprehensive.
In conclusion, to fully leverage the power of text analytics, businesses must recognize the importance of language-agnostic AI. By embracing multilingual AI capabilities, companies can accurately capture and analyze customer opinions across all languages, ensuring a comprehensive understanding of customer sentiment. This approach not only enhances customer experience insights but also provides a competitive edge in an increasingly globalized market. As AI technology continues to advance, the ability to process unstructured data in any language will become essential for businesses aiming to stay ahead.
Original Source: Global Banking & Finance Review
listening247 In the Press
Michalis A. Michael, CEO of listening247, a leading tech company in AI-driven customer experience, insights, and analytics, understands the concerns surrounding artificial intelligence but emphasizes that not all AI is the same.
As the head of London-based listening247, Michael has extensive experience working with AI. One of listening247’s key services is its social listening platform, a competitive intelligence tool that enables brands and organizations to monitor online discussions about them. As AI gains widespread adoption, Michael recognizes both the vast opportunities it presents and the common misconceptions that accompany it.
'We are working with a team of data scientists on a very detailed gap analysis of what we produce ourselves and what ChatGPT can deliver. The question is whether it can also label millions of documents, like we do in seconds. And whether it will have over 80 percent accuracy in every language, like we do. We don't know yet. ChatGPT was mainly created to generate language. And it is generalistic. If our customer is Heineken and the subject is 'beer', we train a model to understand the sentiment for beer in Dutch. That is then 80 to 90 percent accurate.'
'Our approach is supervised machine learning. We pay five students to read 5,000 to 20,000 posts about beer in Dutch. They have to have common sense and good judgment. They will interpret sentiments in posts differently, because there is often ambiguity. It all depends on the training data. This is not about algorithms, it is about people.'
'I don't see that in market research yet. Some research managers use SPSS to process survey results and create tables for powerpoints. When measuring the unsolicited opinions of consumers, you sometimes have to process 10 million posts. If you have the technology to label that and identify the cross-connections, you can use the data for powerpoints or to provide input for dashboards. But you always need people to discover the insights. The machine doesn't do that. At least, not with limited AI. With strong AI, this can indeed become a reality.'
'It's not free. There is a price tag attached, but it's very vague. Who knows what it means when GPT-4 charges six cents per 1000 prompt tokens ? What is a token? It can be a word, a document, a message... You'll probably pay less for lower accuracy. There
We have been dealing with as an industry for about ten years. But those thousands of social media monitoring tools are not market researchers. There are PR people behind them, they are not there to question data quality. That alone creates a difference in accuracy. If ChatGPT delivers 60 or 70 percent accuracy, I am not worried. But if it delivers 80 to 85 percent accuracy in every language. Then we have to create something different or better very quickly.'
As AI, particularly ChatGPT, advances, its impact on services like those offered by listening247 is still uncertain. While ChatGPT excels at generating language, it remains to be seen whether it can match the precision of listening247's specialized models, which achieve over 80% accuracy in sentiment analysis across various languages. listening247's approach relies on supervised machine learning, combining human judgment with advanced algorithms to interpret complex data. While AI may streamline certain tasks, the nuanced insights derived from human interpretation remain crucial, at least until stronger AI becomes a reality.
Original Source: Daily Data Bytes & Data Insights Network
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