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
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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
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
listening247 In the Press
LONDON, UNITED KINGDOM, August 30, 2023/EINPresswire.com/ -- listening247 presents a brand-new innovative feature that promises to reshape the way businesses glean insights from social listening: the revolutionary theme identification tool on their social listening platform.
According to Jonathan Sands: "This feature cements listening247's place as a pioneer in Natural Language Processing using custom proprietary machine learning models. I am extremely proud of our Data Science team.”
In an era where information moves at lightning speed, keeping up with emerging themes and trends can be a challenge. This is where listening247's new feature steps in, leveraging state-of-the-art machine learning algorithms to sift through the data deluge and extract the underlying patterns as they emerge over time.
By harnessing the power of state-of-the-art machine learning algorithms, you're not just listening to what your customers are saying; you're predicting what they'll say next. Stay ahead, stay relevant.
The benefits and competitive advantage that the new theme identification feature brings to the table are immense. By analysing the collective chatter of a myriad of online users, this tool can identify hot topics and emerging themes with unparalleled accuracy giving the company Strategic Agility, Early Brand Engagement, Relevance Enhancement and Risk Mitigation.
listening247 uses a proprietary social intelligence platform to extract value from vast quantities of unstructured data using advanced AI and machine learning techniques. The revolutionary theme identification tool of the listening247's platform, which is the most recent of many inventive developments, works by using Data Aggregation, Natural Language Processing (NLP), Machine Learning, and Real-time Insights. Since 2012 listening247 developed more than 100 custom and proprietary AI models and used millions of online posts, verbatims and other documents as training data in over 30 languages.
listening247's the flagship platform developed has already established itself as a game-changer in the realm of social listening. By tapping into the vast ocean of conversations happening across social media, forums, news outlets, and other online platforms, listening247 empowers businesses with real-time insights into customer sentiments, preferences, and trends. A recent accuracy analysis between GPT-3.5 Turbo and DMR’s proprietary AI, performed by its Data Science team, shows a gap of over 25 percentage points in listening247’s favour.
Ensure your success with listening247. The future of insights is here.
Origial Source: EINPresswire
Fig 1. Detect exponential daily post growth before a theme goes mainstream.
Despite the strong pro-Palestinian sentiment seen on social media, properly weighted opinion polls indicate that support for Israel is more prevalent than online posts suggest. This contrast highlights the need to consider multiple sources when assessing public opinion on the conflict.
Fig 1. Social-media posts in October 2023, % of sample
Scrolling through a typical X (formerly Twitter) feed might give the impression that sympathy for Israel has waned since last month’s attacks, as pro-Palestinian voices dominate both the streets and social media. One user, for instance, wrote, “At first, I was angry at Hamas and Palestine for the attacks, but now after seeing more of what’s going on, I cannot support such a regime in Israel. #FreePalestine.”
But do these views reflect broader public opinion? At our request, listening247, an AI-technology firm, analyzed 1 million posts from Instagram, X, and YouTube between October 7th and 23rd. They used a machine-learning model to classify posts as pro-Israel, pro-Palestine, or neutral. Initially, support was evenly split, but by October 19th, pro-Palestinian posts were nearly four times more common than pro-Israeli ones.
However, Israel's online perception contrasts sharply with overall public opinion. A YouGov poll of Americans on October 20th found three supporters of Israel for every one backing Palestine, even though that day’s social media posts in the U.S. were predominantly pro-Palestinian. Similarly, in Britain, while YouGov found equal support for both sides, social media was overwhelmingly pro-Palestinian by a six-to-one margin.
Fig 2. Which side of the Israeli-Palestinian conflict do you sympathise with more?
One reason for this disparity is age. Social-media users tend to be younger, and this demographic is notably more pro-Palestinian. Additionally, listening247’s analysis did not include Facebook, a platform with an older user base that is likely more pro-Israel. Polls in Denmark, France, Spain, and Sweden show that Israel garners more overall sympathy, but younger participants' views align closely with social-media trends. However, in the U.S. and Britain, social-media sentiment is even more pro-Palestinian than among young poll respondents. Israel’s supporters appear less enthusiastic about engaging in online debates.
In summary, while social media reflects a strong pro-Palestinian sentiment, particularly among younger users, this does not fully align with broader public opinion, which tends to be more balanced or even pro-Israel. The divergence highlights the influence of platform demographics and the varying levels of online engagement among different age groups. This gap between social media perceptions and overall public sentiment underscores the complexity of gauging true public opinion in the digital age.
This article appeared in the International section of the print edition under the headline “The social skew”
Chart sources: listening247; YouGov; The Economist
Original Source: The Economist
listening247 In the Press
Analysis of about 1.9 million social media posts reveals significant language-based differences in opinions on the Israel-Hamas conflict. English- and French-speaking users generally show pro-Palestine sentiments, while German-speaking users tend to support Israel. These online opinion disparities could influence public opinion across different regions and countries.
There are many pro-Palestinian posts in languages other than German.
Fig 1. Analysis of over a million social media posts in various languages to see how many are Pro-Palestine, Pro-Israel or Neutral
The analysis covered about 1.9 million posts across Twitter, Instagram, YouTube, and blogs from October 7 to November 8, discussing the Gaza conflict. Using machine learning, listening247 classified posts in 130 languages as pro-Palestine, pro-Israel, or neutral based on language, hashtags, and emojis. The trends were then analyzed by the Nihon Keizai Shimbun.
English had the highest number of posts, totalling 1.1 million, with 38% pro-Palestine and 20% pro-Israel. French and Spanish also showed higher pro-Palestine sentiment, at 24% and 34%, respectively. Japanese posts have decreased since November, but overall, support for Palestine remains strong. In Arab countries, where anti-Israel sentiment is rising, Arabic posts are over 60% pro-Palestine.
Fig 2. A post to X written in English expressing sympathy for the Palestinian people (some images have been edited)
Support for Palestine is prevalent on Western social media, but pro-Israel sentiment in German posts significantly exceeds pro-Palestine support, with 27% compared to 11%. Due to its historical context and stance since World War II, Germany has consistently supported Israel. In early November, Germany banned pro-Palestinian groups from operating in the country. Chancellor Scholz reaffirmed the government’s position on November 17, declaring that "solidarity with Israel is beyond doubt."
Fig 3. A post by X in German condemning the Hamas attacks (some images have been edited)
Fig. 4 Percentage of opinions by country: (Top 7 countries with the most posts)
Regional analysis of social media posts revealed that India had the highest volume of posts globally, with over 70% in English. Among these, 24% were pro-Israel, significantly higher than in France and the UK. Given that about 80% of India's population is Hindu, support for Palestine was relatively low. In contrast, neighbouring Pakistan, an Islamic country, had nearly 60% pro-Palestine posts. Among English-speaking countries, the US, with its pro-Israel government stance, had 10 percentage points more pro-Israel sentiment than the UK.
Fig 5. Proportion of opinions by SNS
There was a notable difference in opinion on Instagram, where 48% of posts were pro-Palestinian and 31% were pro-Israel, with only 22% being neutral, the lowest among social media platforms. Instagram's user base, primarily young people, saw a clear divergence in opinions following clashes and explosions at various locations. On X, neutral posts accounted for 46%, while YouTube and other video platforms had 80% neutral posts. Overall, pro-Palestinian posts outnumbered pro-Israel posts by 5 to 20 percentage points across all platforms.
The analysis of social media sentiment reveals distinct regional and platform-based differences in opinions about the Gaza conflict. While Western social media, particularly Instagram, shows a strong pro-Palestinian stance, platforms like X and YouTube have higher proportions of neutral posts. In contrast, countries like Germany and India exhibit significant pro-Israel sentiment, with India's Hindu majority reflecting lower support for Palestine compared to Pakistan. These varied perspectives underscore the complexity of global sentiment on this issue and highlight the need for nuanced understanding and engagement in international discourse.
Origal Source: NIKKEI
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listening247 In the Press
IMD’s Peter Nathanial and INSEAD’s Ludo Van der Heyden, examine in their article, how the fallout after the Credit Suisse collapse impacted Switzerland's image as a country. The article is based on listening247's social intelligence collected, tagged and analysed by its proprietary social listening platform.
On March 19, Swiss authorities facilitated the takeover of Credit Suisse by UBS to protect the Swiss economy, a move that surprised many despite prior assurances of Credit Suisse's liquidity. This intervention highlighted longstanding governance issues that had been inadequately addressed, raising concerns about the effectiveness of Swiss governance in managing financial stability. The takeover not only marked a sad end for Credit Suisse but also questioned the strength of governance in maintaining the Swiss Financial Centre's stability. These concerns were acknowledged in the Expert Group on Banking Stability’s 2023 report, issued by the Federal Department of Finance.
In early June, the Swiss Parliament announced a Parliamentary Inquiry Committee to investigate the government's and regulatory authorities' handling of the Credit Suisse crisis, marking only the fifth such inquiry in the country’s history. This investigation underscores that the crisis is far from over, highlighting the ongoing unpredictability of financial markets. Despite Credit Suisse avoiding bailouts during the 2007-08 Global Financial Crisis, its sudden collapse suggests that the Swiss Financial Centre has not fully learned the necessary lessons, particularly regarding the need for more systematic oversight. The Expert Group on Banking Stability’s 2023 report calls for increased government involvement and stronger regulatory oversight in response.
Fig 1. An analysis of stakeholder sentiment in Switzerland and around the world confirms that the Swiss Financial Centre has not benefitted from the Credit Suisse crisis, to say the least
Switzerland's decision to consolidate financial power into UBS, whose assets now equal 2.5 times the nation's GDP, heightens the "too big to fail" risk and creates significant moral hazard. This move also raises concerns about UBS's past misconduct, including involvement in tax evasion schemes and fraud, which could further jeopardize the Swiss economy and its global reputation.
Swiss authorities and citizens need reassurance that UBS will abandon its past misconduct, given the dominant position it now holds in Switzerland. This situation raises concerns about the independence and trustworthiness of Swiss authorities, questioning whether the interests of Swiss citizens were compromised in favor of UBS, especially given the lack of significant taxpayer protections and the minimal cost of the Credit Suisse takeover.
In a recent address to the Zurich Bankers Association, the new CEO of the Swiss Banking Association (SBA) acknowledged, "there is still a lot we do not know, which is why a thorough investigation into what happened at Credit Suisse is essential." The Parliamentary Inquiry Commission (PIC) will likely seek to answer these questions over the next 12-15 months. However, the pressing question remains: will the global community allow the Swiss Financial Centre (SFC) the time it needs to restore or preserve its reputation?
Swiss banking history is unfolding before our eyes, making it crucial to grasp the impact of sentiment—both in Switzerland and internationally—on the reputation of the country’s financial sector in light of the Credit Suisse events.
To begin understanding how these events have impacted the image and goodwill towards Switzerland, the Swiss Financial Centre, and the banks involved, we have partnered with listening247, a research organization specializing in machine learning and AI. They will scan social media for unsolicited stakeholder opinions on Switzerland, using keywords like trust, stability, and competence to gauge sentiment on these themes. This type of sentiment analysis is increasingly becoming a standard tool for early problem detection and crisis management for major brands and institutions.
" Switzerland has now taken a huge risk and is doubling down on the 'too big to fail' doctrine emanating from the GFC advocates creating even more moral hazard."
Net Sentiment Scores (NSS™) for the Swiss Financial Centre (SFC) shifted from fully positive before March 19 to slightly negative afterward, indicating newfound vulnerability. While the Swiss National Bank (SNB) slightly improved its sentiment and the government saw a small decline, sentiment toward FINMA turned negative. These changes suggest emerging concerns about Swiss market authorities, an issue the Expert Group has recognized and begun addressing. Tracking sentiment moving forward will be important.
Not all banks were negatively impacted by the Credit Suisse crisis. Raiffeisen gained favor, and sentiment toward Julius Baer remained steady. Most Swiss banks, apart from Credit Suisse and UBS, maintained or improved their positions, reassuring stakeholders that they were distanced from the crisis, with CS, UBS, and Swiss authorities as the main players. The NSS™ dynamics of Credit Suisse and UBS reveal some notable insights.
Unfortunately, sentiment among both Swiss and international observers is negative. The NSS™ methodology indicates this reflects a risk factor and potential vulnerability moving forward.
Swiss and international sentiments have diverged in their negativity. Credit Suisse entered the crisis with already negative ratings, which worsened but slightly improved after its absorption into UBS. In contrast, UBS, which had a negative sentiment in Switzerland before the crisis, initially saw some improvement due to its role in rescuing Credit Suisse. However, this positive sentiment faded within six months, and UBS's standing in Switzerland has returned to where it was a year ago, possibly due to its tough negotiating stance or perceived reluctance to rescue Credit Suisse.
The sentiment abroad has become as negative as in Switzerland, with UBS now fully absorbing the negative sentiment once directed at Credit Suisse. UBS faces increased risk due to its larger size and negative NSS™, a known risk predictor. The UBS CEO's recent claim that cantonal banks pose a greater systemic risk than UBS is illogical, as these banks are well-guaranteed, operate locally, and have minimal concentration risk. The NSS™ analysis also explains why deposits are flowing to cantonal banks, a trend that the Credit Suisse takeover and the CEO's remarks are unlikely to reverse, especially given the SNB Chairman's call for customer mobility in seeking competitive bank offers.
The review of Swiss authorities' handling of the Credit Suisse crisis raises key questions. What was the plan behind their intervention, and why weren't more assertive actions taken earlier despite their limited powers? Interventions at the board level, such as changing the Chairman, could have been quick, yet the actions seemed timid or absent. For instance, why did Swiss authorities allow Credit Suisse to hire a CEO from the insurance sector, while the company's top leaders lacked banking expertise, and why didn’t they demand changes to CS’s business model or create a toolkit for such crises?
Fig 2. The exceptional financial concentration into UBS puts the entire Swiss economy at risk since total UBS assets now equal 2.5 times Swiss GDP
listening247 is set to further enhance its algorithmic precision and broaden its application across various demographic and linguistic landscapes. The success in the UK elections serves as a testament to the potential of AI solutions to transform electoral strategies and deepen our understanding of voter behaviours.
If interventions were so hesitant, what does this reveal about the Swiss authorities' supervisory capabilities? Was Credit Suisse in worse shape than initially reported during its government-led rescue? Why weren’t healthier segments like wealth management and Swiss retail spun off to benefit the Swiss Financial Centre and its reputation? Why are Swiss authorities permitting the concentration of financial risk in UBS, allowing it to build a monopoly while leaving taxpayers bearing the downside?
These questions cast doubt on the effectiveness of the Swiss regulatory framework. How will Swiss authorities supervise UBS, especially with concerns about the "revolving door" where former executives might oversee their previous employer? Should Switzerland consider closer cooperation with the EU’s Single Supervisory Mechanism (SSM), which has stronger supervisory capabilities? FINMA could lead by adopting transparent standards similar to those of the SSM, such as avoiding former UBS or Credit Suisse executives on its board, to prevent perceived bias and enhance its supervisory role. Additionally, Swiss authorities should consider rebranding and empowering their agencies to better oversee financial institutions.
A key issue remains the ongoing uncertainty surrounding Credit Suisse, Swiss banking, and the Swiss Financial Centre, which will likely persist until the Parliamentary Inquiry Committee’s evaluation in about 12 months. The lack of a clear plan delays the restoration of Switzerland’s brand and image. This situation parallels the UK's Brexit, which stemmed from unresolved economic model debates post-GFC. The lack of a strategic discussion on the UK’s future led to Brexit as a superficial solution, highlighting the need for proactive national governance and long-term planning, which was missing after the 2008/09 crisis.
Fig 3. Evolution of Net Sentiment Scoring of CS and UBS over the period April 2022 – August 2023, with information on the volume of items identified in the search
The critical question is why key issues in the Credit Suisse crisis were not addressed sooner or were answered unexpectedly. If progress is being made, the direction needs clarity; if not, it’s better to acknowledge this early and discuss new strategies. The PIC report, while taking over a year, may be seen as overly bureaucratic in the fast-paced global financial world, suggesting a lack of urgency. The Expert Group on Banking Stability 2023 contradicts the notion that everything is under control, and both Swiss and international stakeholders expect prompt action. Switzerland’s traditionally slow and cautious approach may not align with the rapid pace of today’s world, highlighting the risk of underestimating global sentiment and the need for immediate measures.
Our analysis confirms that the Swiss Financial Centre has not benefitted from the Credit Suisse crisis, and this situation requires ongoing monitoring. UBS, despite its financial gain and near-monopolistic position in Switzerland, fares poorly in sentiment analysis. Previously, both UBS and Credit Suisse offered unique banking services under Swiss bank secrecy to international clients. Without this secrecy, UBS's competitiveness now hinges on providing superior banking services, supported by a skilled workforce and a stable legal and political environment, with Switzerland managing 25% of cross-border assets according to the Swiss government.
The Swiss Financial Centre faces two major governance challenges: can FINMA recover from its perceived inaction during the Credit Suisse crisis, and how will it demonstrate improved capability to anticipate and intervene in future crises? Failure to address these issues effectively could have severe consequences for Switzerland and the global financial system.
Origal Source: IMD
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listening247 In the Press
listening247, an innovative leader in the technology sector specialising in AI-driven insights, is thrilled to announce the addition of nine talented professionals. LONDON, UNITED KINGDOM, April 12, 2024 /EINPresswire.com/ -- listening247, an innovative leader in the technology sector specialising in AI-driven customer insights, is thrilled to announce a significant expansion of its team, with the addition of nine highly talented professionals.
Following a successful first institutional funding round at the end of 2023, listening247 is poised for accelerated growth and innovation in the Intelligent Data as a Service (IdaaS) space. This strategic expansion includes the introduction of brand new Marketing and Sales departments, further enhancing listening247's capabilities to serve its global client base.
listening247 is at the forefront of transforming unstructured data into precise, actionable intelligence. With over 100 proprietary AI models, used on listening247, which delivers exceptional, data-driven insights across various sectors, empowering clients to make informed decisions that drive marketing, sales, and operational efficiencies.
Michalis A. Michael, Chief Executive Officer at listening247, shared his enthusiasm about the expansion, "We are embarking on an exciting phase of growth and innovation at listening247. The new team members bring a dynamic mix of skills and expertise that are crucial for our continued success. We continue to be a remote-first company hiring the best talent in whichever country we find it. Their addition is a testament to our commitment to excellence and our mission to revolutionise by creating the new IdaaS sector with AI-driven solutions. We are more prepared than ever to deliver unparalleled insights and services to our clients."
This team expansion underscores listening247's unwavering commitment to leveraging the power of AI for transformative customer insights. By enhancing its capabilities across departments, listening247 continues to deliver actionable insights and drive success for its clients in the ever-evolving landscape of data-driven research. Stay tuned for some really exciting innovations about to be announced soon.
Original Source: TECHNOLOGY TODAY
Fig.1: Graphic of new listening247 starters & successful funding round.
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listening247 In The Press
LONDON, UNITED KINGDOM, June 18, 2024 /EINPresswire.com/ -- Social media platforms serve not only as spaces for networking but also as arenas for political discussion and voter engagement, the recent South African elections on 29 May 2024 have underscored the transformative role of digital analytics. Developed by listening247's platform which has emerged as a crucial solution in decoding voter sentiments and forecasting election results, marking a significant evolution in how political campaigns and analysts understand voter interactions. This project was carried out in partnership with Rich Rewards.
Utilising more than 100 custom machine learning models, listening247 processes unstructured data from diverse sources including social media, forums, blogs, and news outlets. During the run-up to the South African elections, from February to May 2024, listening247 meticulously analysed posts from platforms such as X, Facebook, YouTube, Instagram, news and forums focusing on six major political parties and numerous political issues.
The standout feature of listening247 is its accuracy in relevance, sentiment analysis and conversation drivers. listening247 successfully predicted the ranking of the six political parties based on social media engagement and sentiment. This was achieved despite only analysing English-language data, which speaks volumes about its sophisticated algorithmic capabilities.
Data revealed the African National Congress (ANC) as the winning party in both the volume of social media posts and positive sentiment, closely followed by the Democratic Alliance (DA) and MK. Notably, MK clinched third place due to its significant following and engagement on social media, challenging traditional poll predictions. EFF, Action SA and Rise occupied the 4th, 5th and 6th positions of the six parties included. This outcome was accurately predicted by ranking the six parties using the total volume of positive sentiment posts.
Fig 1.
Key issues that resonated with voters included infrastructure, corruption, employment, education and crime, reflecting the electorate's core concerns. Interestingly, all six parties analysed exhibited a negative net sentiment score on these pivotal issues, yet listening247's detailed analysis allowed for a deeper understanding of voter concerns and party strengths.
The methodology behind listening247 is a testament to listening247’s commitment to innovation and precision. listening247 is capable of analysing data across any language, enhancing its versatility. For the South African elections, the focus was on English-language data due to its prevalent use and status as a lingua franca among the diverse linguistic groups in South Africa.
Despite not including other major local languages such as Zulu, Xhosa, and Afrikaans, listening247 accurately predicted the political parties' rankings. This achievement highlights its ability to effectively interpret key trends and sentiments from the English-speaking segments of the population, showcasing its robust algorithmic design.
listening247’s AI technology is engineered to handle data from any language with high accuracy, ensuring that listening247 can be adapted for a broader linguistic analysis in future projects. This potential for expansion promises even more detailed insights into voter sentiment across different linguistic demographics.
*With 45 million internet users and 26 million social media users in South Africa, platforms like X, Facebook, Instagram and YouTube have become integral to political campaigning. The analysis demonstrated that the ANC, DA, and MK had the most substantial online presence and engagement, correlating with their top rankings in both social media discussions and predicted electoral outcomes.
As listening247 continues to refine its social listening platform, the focus remains on enhancing its predictive accuracy and expanding the scope of data analytics in political forecasting. The success seen in the 2024 South African elections serves as a powerful example of the potential of AI-driven analytics to revolutionise political campaigns and the understanding of voter dynamics.
The South African elections have illustrated a significant shift towards digital analytics in the political sphere. Solutions like listening247 are becoming indispensable in deciphering the complex landscape of voter behaviour and sentiment. As technology progresses, the convergence of AI, data analytics, and political science is set to offer deeper insights, potentially altering the traditional approaches to political engagement worldwide.
The journey of enhancing these predictive models continues, aiming to provide increasingly precise and actionable insights into voter sentiments and electoral outcomes. With its spirit of innovation, authenticity, and empowerment, listening247 is committed to providing invaluable solutions that empower analysts around the globe.
*Source: Stats SA figures allow one to estimate that there were 37.8 million people aged 18 years and older living in South Africa in mid-year 2018.
Original Source: United Kingdom Political Times
listening247 In the Press
In the bustling arena of UK politics, the recent general elections revealed a significant evolution towards technology-driven electoral analysis. listening247 proprietary solution showcased its ability by not only analysing but also dabbling in predicting election outcomes, drawing from its earlier success in the South African elections.
During a critical two-week period – from June 17 to July 2 - leading up to the UK elections, listening247 processed an extensive dataset comprising 704,413 online posts mentioning the participating parties across key platforms such as X, Facebook, YouTube, Instagram, TikTok, and various news outlets, blogs and fora. This robust analysis provided a deep dive into the unsolicited opinions of UK voters, offering a rich layer of insight that augmented traditional polling methods which are based on the solicited voter opinion.
listening247 highlighted a notable trend: despite its lower profile in conventional polls (projected at 16% Fig. 1), Reform UK demonstrated significant influence on social media topping the rankings with number of positive sentiment posts overall (39% share Fig. 1) and number of posts that show preference in voting for a party (61% share for Reform UK but dropping to 32% Fig. 1). This anomaly may be a critical data point, especially considering the hesitation among some voters to declare their support for a far-right party in polls, hinting at a potential electoral surprise. Of course on July 1st and 2nd something changed in this respect and Reform UK lost the advantage to the extend we saw on June 28th. This is going to be a learning moment for our predictive capability.
Labour has the most followers on social media, followed by the Conservatives and Reform UK. Yet, when it came to engagement and positive sentiment, Reform UK again unexpectedly led the charge. This discrepancy underscored the unique ability of listening247 to detect detailed voter sentiments and engagement, beyond mere follower counts.
Fig. 1
Key electoral issues such as taxation, Brexit, and immigration dominated online conversations, resonating deeply with the electorate. All parties recorded negative sentiments on these critical issues, a trend consistent with broader European sentiments, yet listening247 effectively dissected these complex dialogues to forecast electoral leanings.
listening247 employs a sophisticated blend of data collection, sentiment analysis, and noise filtration, specifically tailored to navigate the multifaceted political landscape of the UK. This methodological rigour enabled it to make some predictions for the election results, building on the successful prediction models used in South Africa.
Despite the UK's diverse political environment, listening247 demonstrated its robust capability to deliver precise and actionable insights, affirming its role as a critical solution in contemporary political strategy.
With an *83% penetration rate among eligible voters, social media is now indispensable in UK political campaigns. listening247’s analysis revealed that while Labour enjoyed the highest number of overall posts, Reform UK captured the lead in positive engagements, pointing to evolving strategies in political communication.
listening247 is set to further enhance its algorithmic precision and broaden its application across various demographic and linguistic landscapes. The success in the UK elections serves as a testament to the potential of AI solutions to transform electoral strategies and deepen our understanding of voter behaviours.
The UK elections have highlighted the indispensable role of advanced digital analytics in deciphering complex voter behaviours and effectively predicting election outcomes. As AI technology continues to evolve, the synergy between polls and unsolicited voter opinion expressed online is poised to offer more accurate predictions, fundamentally changing the landscape of political engagement.
Embracing the innovative spirit, authenticity, and empowerment that define listening247 at the forefront of redefining political analysis, providing campaign teams and analysts with the tools needed to navigate the complexities of voter interactions with unmatched precision and insight.
* There are approx. 45 million voters registered in the UK. The social media penetration is 83% which basically covers everyone who is of voting age. Election turnout in 2019 was 67%.
Origal Source: UK Daily Ledger
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listening247 In the Press
LONDON, UNITED KINGDOM, September 4, 2024 /EINPresswire.com/ -- DMR Unveils Exciting Rebrand to "listening247" – Pioneering Intelligent data as a Service (IdaaS) Sector
DigitalMR Ltd., a leading provider of intelligent data solutions, proudly announces its rebranding to "listening247". This strategic move underscores the company's commitment to innovation and its vision to revolutionise the digital landscape. As part of this rebrand, DigitalMR (DMR) will be doing business as (dba) listening247, alongside its solutions DataVinci, engaging247 and communities247.
CEO and Founder Michalis A. Michael expressed his enthusiasm about the rebrand, stating, "We are thrilled to unveil our new identity as listening247. This rebrand reflects our evolution as a company and our dedication to pioneering the Intelligent data as a Service (IdaaS) sector. listening247 represents our commitment to innovation in the space of AI-driven insights that empower businesses to thrive in today's rapidly changing environment."
At the heart of listening247 lies a commitment to transforming unsolicited and raw data into actionable insights. Leveraging more than 100 proprietary AI models, listening247 extracts valuable insights from unstructured data streams, like social media, blogs, forums, news, review sites, customer calls, chats, emails and survey responses enabling businesses to make informed decisions and stay ahead of the competition.
"listening247 is not just another analytics solution – it's a game-changer," remarked Michael. "In today's data-driven world, businesses need more than just numbers; they need actions and execution. That's where listening247 comes in – we're pioneering a new era of Intelligent data as a Service."
The rebranding to listening247 aligns seamlessly with the company's integrated approach to data solutions. By combining listening247 with DataVinci, engaging247 and communities247, we empower users to harness the full potential of unsolicited and solicited customer opinions.
"DataVinci, engaging247 and communities247 complement listening247 perfectly," explained Michael. "While listening247 provides intelligent data from unsolicited opinion, DataVinci produces the recommended actions and not only that, it also produces copy and images for social media posts. engaging247 then makes it easy to schedule these posts and connect with their customer communities. Meanwhile, communities247 facilitates the gathering of solicited opinion from private and branded customer communities and provides a true 360-degree view of the customer."
As businesses navigate an increasingly complex digital landscape, and as unstructured data grows exponentially the need to find a needle in a haystack has never been greater. With listening247, businesses can unlock the full potential of their data, gaining the competitive edge needed to succeed in today's fast-paced environment.
"We live in an era where data is king, but “ready-to-eat” actionable insights are the crown jewels," said Michael. "With listening247, businesses small and large can uncover hidden opportunities, spot market trends early, and make data-driven decisions with confidence. Our rebranding to listening247 reaffirms our commitment to driving innovation and empowering businesses to thrive."
For more information about listening247 and its suite of intelligent data solutions, please visit the listening247.com website.
Original Source: TECHNOLOGY TODAY
Fig.1: Graphic of rebrand
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
