Absolutely. We are mindful of various special requests from our Clients to ensure the best experience. To customize products, contact us at nuance@d-tag.com.

Based on detailed analysis we can predict changes in trends with high probability. Market reports today are hardly interpretable without context, so we place them on trend lines built on historical databases to create scalable and verifiable forecasts.

Our NLP (Natural Language Processing) algorithms can process data across more than 30 languages. The number of available languages depends upon your specific solution and service pack of choice. For more information, visit platform-languages and see the full list of supported languages and features.

You’ll know more underlying factors of the decisions made by your customers, brand, competitors, audience, content, and much more. You can discover new leads, identify the top influencers in your industry, and keep track of your competitors’ progress - what works for them and what doesn’t. Online content is no longer just an accessory to your marketing plan, it is part of the customer experience. Use our solutions to create better content, campaigns, and products as well as overall better business decisions.

Our NLP is able to learn new languages and phrases used within any given industry, so that it can identify the topic and emotional charge of a comment. D-TAG only releases a new language once it can identify emotional charge with at least an 85% accuracy rate compared to human understanding.

It strongly depends on the scope of your project, including the number of objects,
channels, languages, and the covered time period. If your project is extensive, it can easily be over a million per day.

We collect data from public blogs, websites, news sites, forums, message boards (excluding those with firewall or paywall protection), and all major social media platforms, including Facebook, Instagram, YouTube, Twitter, Reddit, Vkontakte, and Tencent.

D-TAG will only provide ethical solutions and only uses publicly available data and complies with all government regulations. Ethical competitor analysis is a common practice. Your competitors are probably already using some sort of Social Media Analytics to track key players. The only w­ay you can get ahead of them is by diving deeper into the available data.

If you need to analyze your own private data, those private messages may be used if you choose. However, listening in on private conversations is neither available nor legal.

D-TAG can be used to enhance existing data, frameworks, and toolsets. By integrating it into your current SMA toolkit you can maximize the potential of your marketing strategy without losing your previous results.

We totally understand that you may need to retain private data within your existing data storage solution. For such cases we deploy a completely closed, on-premise version of the Deep Nuance Platform which can be run on your servers, behind your own firewall.

D-TAG is ready to be linked with a professional voice-to-text converter to be able to process hundreds of hours of audio content according to your preferences.

Marketing: When you start planning the marketing strategy, you need to have a clear and detailed picture of your industry. Social Media Analytics will answer your questions.
Analytics: Once your marketing campaign is running, you need to identify your audience’s communication channels and figure out how you can reach them.
Public relations: Monitor trends, find the best entry points, track the competition, and measure the effectiveness of your campaigns.
Product development: Before you spend anything towards a new product, you and your management would love to see validation based on accurate and reliable results.

Whether you follow them or not, people are talking about your product, brand, or organization online. They share their thoughts on your latest campaign, react to your posts, and retweet news about you, offering you valuable insights into how people see you. Industries have recognized the importance of listening to what is said online. Social listening is much more than simply monitoring communications. It means you dive deeper into what’s being said, find the root causes, and continuously improve based on the latest feedback.

NLP (Natural Language Processing) is a subfield of linguistics, computer science, and artificial intelligence which allows for quick, scalable, repeatable analysis of text. NLP recognizes the contents of documents, including the contextual nuances of the language. The technology can then accurately extract information and insights contained in the documents as well as categorize the documents themselves.
In other words, D-TAG understands candid, unstructured conversations and in more than 30 languages.

Once you have access to social media channels and other online sources, you get unfiltered data streams. To exclude irrelevant data, you need a high-quality query, which acts as a filter, to create a data collection that is relevant to your topic.

There’s way more to telling how people feel about your brand than determining whether their reactions are positive or negative. Emotions are not binary – people may have mixed feelings about something and as such we can place that feeling on a scale of -5 to +5 by analyzing the language they use. This is what we call sentiment score.
Once you have a timeline and different scores to compare, you can easily track how certain events or changes have affected the perception of your product, brand, or organization in the online space and adjust your strategy accordingly.

ROI from SMA tools can be realized in cost savings, market penetration, and risk avoidance among other things. The actual ROI depends on your market, industry, and product. However, in general, it is estimated that if a B2C company spent 4-10% of their yearly marketing budget on SMA, a return of over 100% could be anticipated.

This is exactly why it’s not enough to determine the sentiment score of a document.
Let’s say we have an overall positive comment, but the brand itself is mentioned in a subtle negative tone. Document-level detection would yield a positive sentiment score for the comment, and the negative light in which the brand is mentioned would go unnoticed.
To address this issue, we use object-level sentiment detection, which allows us to take a closer look at the phrases surrounding the object (in this case the brand) and calculate a more accurate sentiment score. The same goes for multiple objects mentioned in one document. If one of them tips the scale, we’ll know.
In sum, if you and your competitor are mentioned in the same comment, we can tell you the sentiment of you and your competitor separately.

D-TAG can provide professional services to support you. We offer training, analytics teams that help you set up your analytics platform. If you need help, don’t hesitate to contact us.