How many social media analytics terminology do you know? Here is our top 40 most important:
Analytics: Process of searching, recognising and interpreting patterns and information from data. Social media analytics uses public social media content and conversations as data.
Audience: Group of people that you reach with the published content. Knowing your audience is one of the best assets in social media marketing and communication. With social listening you are able to gain information from your audience.
Benchmarking: Benchmarking is the process of comparing business attributes and performance between companies, channels or any other measurable topics. Social media benchmarking can include comparing, for example, sentiment scores, visibility and engagement.
Brand awareness: Measure that refers to the level of familiarity which an audience and consumers have with a brand. Brand awareness is one of the main goals of social media marketing, and it can be achieved with having efficient brand visibility and engaging content.
Brand health index: BHI. In the context of social media analytics, brand health index is a measure that reflects how the customers feel and interact with the brand. BHI includes brand awareness and sentiment score. It can also be used as a measure for threat level analysis.
Brand monitoring: Brand monitoring is the process in which social media conversations and channels are monitored in order to understand what people talk about a brand. It is not enough to analyse only the conversations on brand's own channels or their followers channels, because people talk about brands even they don't follow them in social media.
Brand visibility: Social media brand visibility refers to the amount of views that your content and brand receives. Brand awareness, on the other hand, takes into account also how the audience remembers and acknowledges the content and brand message. Social media brand visibility can be bought, but by choosing the correct channel and appropriate content the amount of visibility increases organically too.
Cleaning data: Data cleaning is the process of detecting irrelevant data and removing it. Social media is full of irrelevant data, for example, advertisements, bots and neutral meaningless content. Irrelevant data affects the analysis by making it unreliable. According to InsightsAtlas's research, as much as 60-80% of the social media data is irrelevant for the brand. InsightsAtlas analytics cleans all data, making the information and insights 100% accurate and unbiased.
Complex data: Data type that does not have a traditional structure (alpha, numeric, dates). For example, natural language, photos, audio and video are complex data. Social media if full of complex data, which can only be analysed accurately with a combination of human analysts and Artificial Intelligence.
Crisis management: Crisis management is the process, in which a brand or company deals with an immediate emergency situation. In case of a social media crisis, the emergency is happening fully or partly online. These kind of situations can be predicted and monitored in real time with InsightsAtlas’s service.
Demographic analysis: Method used to understand the age, sex, and location of a population. Demographic analysis can be utilised in marketing to target advertisement and content.
Engagement: Social media engagement is a measure of all the accountable activity within a shared content. These are, for example, likes, comments, shares, views for videos and retweets in Twitter.
Image analysis: Image and photo analysis is the process of extracting useful information from the source content. Currently, a major part of the social media text posts include also an image or photo. Accurate image analysis cannot be done by Artificial Intelligence alone, so real analysts are still needed. InsightsAtlas analytics service combines human skills with Artificial Intelligence in order to analyse imagen and photos with 100% accuracy.
Impression: In the context of social media, impression is an accountable view of a piece of content. Impression is also a view for a video, however, different social media platforms measure the accountable view differently.
Industry monitoring: Industry monitoring is the continuous process of observing and listening to the activities and news around a specific industry. Explicit social media industry monitoring will expose information and insights that help companies grow better. Similar to industry tracking and market monitoring.
KPI: Key Performance Indicators address the various measurements of performance. They are used in measuring, for example, social media performance, campaign performance and brand performance. KPIs are relevant insights for top management and marketing professionals as they represent the general view and are easily comparable.
Management insight: Management insights are customised advice and analyses for the top management in companies and organisations. InsightsAtlas management insights are based on data gathering from social media, data processing and cleaning, analysis, and interpretation. For example, competitor benchmarking, industry monitoring and trend tracking are management insights.
Market insight: Understanding or discovering something relevant to your business. Quality insights require comprehensive, subjective and accurate data analysis. Market insights help companies to meet their customers needs.
Market intelligence: All the market information that a company or organisation owns. For example, information about competitors, competitive advantage and current trends. Market intelligence can be formed from social media data as well.
Marketing analytics: Marketing analytics is the process of gathering, filtering and analysing social media data marketing performance to maximise its effectiveness and optimise return on investment (ROI). Understanding marketing analytics allows marketers to be more efficient at their jobs and minimise wasted web marketing dollars
NLP: Natural Language Processing is a tool for computers to analyse, understand, and synthesise human language in a smart and useful way. By utilising NLP, developers can structure, for example, natural language data in social media content into measurable data.
NLP algorithm: Natural language processing algorithms instruct computers to understand human language by simulating the human ability to understand language. With the algorithms, a technology is capable to interpret all the nuances, grammatical rules, contexts and natural expressions of the language.
Noise: Social media noise includes all irrelevant data, for example, ads, bot posts, posts not related to the topic, posts with no sentimental value, posts originally created by the brand. Noise can be filtered out to obtain better quality data for sentiment analysis.
Organic conversation: All the social media conversations and posts that are not paid, sponsored or produced by the brand.
Potential impressions: When the exact measure for visibility is not available, the content can be assessed with an estimated measure based on past statistics.
Potential media value: Potential media value or earned media value expresses how much the visibility of the content would cost when it is bought from the same channel.
Reach: Social media reach is a measure that refers to the number of individual users who have seen a particular content or campaign.
Real conversation: Social media activity that is meaningful for the brand. Real conversation can be also part of the photos and videos, or behind a link. In order to recognise and analyse all real conversations, a combination of human skills and Artificial Intelligence is needed.
ROI: Return On Investment is a performance measure for investments. ROI is calculated from the ratio between the net profit and amount of investment.
Sentiment analysis: Sentiment analysis is the process of researching an opinion or tone-of-voice about a given subject. Subject can be, for example, an individual piece of social media content, or all the content during one month. Traditional sentiment analysis is constructed from text, but InsightsAtlas sentiment analysis includes also the context of the content, links, natural language, photos, audio and videos.
Sentiment score: Sentiment score is the number that represents the positivity, neutrality or negativity of a given content. For example, the sentiment score for a photo can be 1, indicating that the photo is positive from the receivers point of view. Sentiment analysis is constructed of multiple sentiment scores.
Share-of-voice: Share-of-voice is the brand's social media exposure and engagement compared to the competitors. Share-of-voice is a percentage and can be used to represent the social media performance in comparison to other brands.
Social listening: Social listening is the process of monitoring social media channels and online data sources. Social listening is used in aggregating data for social media analysis, which helps companies and organisations to improve and develop their social media strategy, customer service and communications. Similar to social monitoring.
Social media alert: Automatic alerting service, which monitors social media channels and helps in spotting new threats. Social media alert is a crucial tool for brand protection.
Social media analysis: Social media analysis is the outcome from an analytical process, which includes gathering data, processing it and interpreting the information. Analysis includes valuable insights that a company or organisation can utilise in their strategy.
Social media monitoring: Social media monitoring is the process of continuous observing and listening of various social media channels for information and data. InsightsAtlas is the only service providing social media monitoring which includes the whole data: text, natural language, photos, audio and video.
SocialAI: InsightsAtlas SocialAI™ combines millions of in-market analysts with Artificial Intelligence, in order to provide unbiased and accurate analytics services in every language and market around the world.
Threat level analysis: In social media analytics, a threat level analysis is a continuous activity, in which the social media channels are monitored for possible risks and intimidating content. Threat level analysis is an efficient tool for brand protection and social media crisis management.
Trend tracking: Technique used to monitor the current and forthcoming trends, movements and changes of direction in the market. Quality trend tracking needs a lot of accurate data, and in case of InsightsAtlas, we analyse social media data including natural language, photos and videos. See also trend spotting.
Twitter sentiment analysis: Sentiment analysis, which is constructed for certain group of tweets, for example, all the tweets relating to a brand of a trend during one month. In order to have an accurate sentiment analysis, all the relevant data has to be included. This means not analysing only text with hashtags, but also natural language, photos, images and the context of the tweet.
Unstructured data: Unstructured data and unstructured information does not have a pre-defined data model or is not created in a pre-defined way. For example, natural language is unstructured information, because it includes slang, humour and illogical meaning from the computer's point of view.