The Traps of Big Data

With all the buzz around big data nowadays, it is easy to get carried away with collecting as much data as possible. People think to themselves that with more data they will be able to better improve their business making decisions. This is true… but to an extent and with caveats. Over at Semeon, we pride ourselves in our ability to make use of data for the companies we work with. This has been our mission, and since our inception, we have been able to help brands such as P&G, Honda, Toyota, Pepsi, Sephora and many more leverage their data for actionable insights.

Along our journey, we have encountered a countless number of firms who have fallen into some of the traps of big data. Some of the major pitfalls we see are as follows:

1. Vanity Metrics

This is the number one problem we see with companies today: they focus on data that doesn’t matter. It takes time, but it is important to determine what data matters to your company. What data is going to help increase user retention? What data is going to help you better understand the needs of the customer? What data is measurable and consistent? Focus on quality over quantity. Too many companies love the idea of having data that they forget what the purpose is for. The purpose is to create insights that allow you to make better, more informed decisions.

2. Un-Actionable Insights

This leads right into our next point: actionable insights. This problem is deeply correlated with vanity metrics but requires its own mention due to its importance. Many companies we have interacted with collect data for data’s sake. Perhaps this data can be analyzed ex-post but it is much more effective to know why it is being collected, ex-ante. If you can’t summarize what the data is being used for in a few lines, it is time to reconsider whether or not it is providing any use to the company.

3. Lack of Statistical Significance

Insights can’t help you if your results aren’t valid. When you find trends and interpret data there is the question of whether your results are statistically significant. This can be figured out with little knowledge of statistical analysis and is necessary to confirm trends. Using data sets that are small in size can lead to a misalignment of strategic priorities based on information that isn’t true.   

4. Not Leveraging it enough

I’m sure we don’t have to explain to you the importance of data. Chances are, if you are in the workforce, you have either dealt with analyzing data firsthand or at least contributed to data entry. Economist Intelligence Unit reported that 60% of the professionals they quizzed feel that data is generating revenue within their organizations and 83% say it is making existing services and products more profitable. The uses of it are seemingly limitless and continue to be improved upon, yet still, there are copious amounts of companies not leveraging it to their full capabilities. As the famous manager, Peter Drucker says, “What gets measured, gets managed”. Our suggestions to companies that use data is to evaluate what else they could be measuring. Is there anything in the company that needs to be improved upon? If so, is it measurable? Will measuring it interfere with workflow? These are just some of the questions companies should be asking themselves on a regular basis.

5. Misinterpreting it

“It is much easier to maintain and bolster views that we currently hold than it is to create and develop new ones” – Daniel Kahneman.

Confirmation bias is one of the biggest dangers to big data. It is a cognitive bias in which one possesses a hypothesis and actively seeks out data to support it – ignoring the data that reject it. The worst part is that people do it unconsciously. Over at Semeon, we have been able to statistically show some companies that their firmly held assumption were false.

We have also seen a decent amount of firms mistake correlation for causation. Just because data suggests two events are interconnected, it doesn’t mean that one definitively caused the other, even if it makes logical sense.

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We hope you enjoyed the article! If you are interested in receiving a free consultation call on how to improve your company’s use of data, we are more than willing to assist and offer insight. Contact us by requesting a demo on our main page.

Utilizing AI to Understand your Customers

Noam Chomsky, a central figure in the study of linguistics from the late 1950’s, said that language “is a process of free creation; its laws and principles are fixed, but the manner in which the principles of generation are used is free and infinitely varied. Even the interpretation and use of words involves a process of free creation.”

Clearly then, language is complex. By Chomsky’s logic, conjuring and deciphering language is seemingly infinite. In linguistics, semantic analysis is the study of the structure and meaning of speech. It’s the job of semantic analysis to understand language from the point of view of the encoder. This eliminates the process of ‘free creation’ that comes from interpretation. It does this by relating syntactic structures from the level of phrases, clauses, sentences, and paragraphs to the level of the writing as a whole. This involves removing features specific to cultural contexts  and deciphering key elements from idioms, and figurative speech.

For many brands nowadays, the complexity of language is proving to be an obstacle. The fact that there are so many ways to encode and decode messages makes understanding the customer difficult. Online content is rife with spelling mistakes, acronyms, initialisms, and emoticons. In addition, the mechanics of tracking exactly when and how people are interacting with one another is non-trivial (for example, are they in a series of threads in a forum, are they retweeting or replying to one another on Twitter?). Also, once the boundaries of people’s conversations are well understood, the correct interpretation of the meaning behind words is handled very poorly. Most analytics companies’ attempts to interpret conversations are based largely on frequency driven metrics. As a result, we often see that interpreting meaning is based on the number of times any given word is mentioned in online posts being analyzed. This misinterpretation can lead to a misunderstanding of customer sentiment and cause a multitude of problems. A study from IBM and eConsultancy found that 81 percent of companies say they have a holistic view of their customers. And yet, only 37 percent of customers agree that their favorite retailer understands them. This is a huge discrepancy and highlights the challenges associated with language.

But despite the complexities, it is not impossible to understand your customers. Like Chomsky said, there are basic laws and principles that need to be followed. These rules make it possible. Over at Semeon, we have made it our mission to understand the meaning underlying what the customer is saying. It started with the realization that customer and brand alignment is essential to maximizing ROI. So, using artificial intelligence, we have created a software that figures out the context behind the consumer’s speech instead of identifying keywords. This allows us to provide proper analysis and gives brands the capabilities to be in the 37 percent companies that truly know their customers.

I hope this article provided some insight into the complexities of language and the problem is poses for brands. Furthermore, I hope that if you represent a brand that it makes you stop and think about how you are evaluating what your customers are saying.

The Call to Action

At the least, stop with the glorified post counters. We need to start focusing on the metrics that really matter: the customer sentiment. What are your customers actually saying about your brand? Are they content? Do multiple customers have the same problem?  

At the most, check out what we have to offer over at Semeon! We are here to help you and make your lives easier. Our software can help take your brand to the next level.

Let’s Skip The Small Talk Within Big Data!

As the world is moving into a symbiotic state with technology, specifically with their handheld devices, there is much buzz around ‘Big Data’ as a means to understanding societies and individuals. However, there is an important hurdle, algorithms must face in order to begin decoding our condition – the complexities of the human language.

Originating across the globe, our language constantly evolves to carry culture, tradition, sentiment and overall sentiment at a given time. The traditional analysis uses simple word clouds that divide text content through elementary rubrics such as positive/negative words, frequency tags. Nonetheless, in a society where sarcastic memes surf large waves of the internet, it is crucial for big data analysis tool to stop comprehending like a detached machine and view text like a human would.

So, where do we go from here…

The Birth of NLP (Natural Language Processing)

Natural language processing (NLP), a component of artificial intelligence, is the ability of a computer program to understand human speech as it is spoken.

The development of NLP applications takes on bigger challenges as computers traditionally require humans to “speak” to them in a programming language that is precise, unambiguous and highly structured or, perhaps through a limited number of clearly enunciated voice commands. In contrast, Human speech is not always precise — it is often ambiguous and the linguistic structure can depend on many complex variables, including slang, regional dialects, and social context.

Hm, only if there was an example of how this can be used in business…

Leveraging of the Concept Cloud for an Influencer

The excerpt below is a Concept cloud that has been plucked from a report created for Sugar Sammy, a Canadian comedian, actor, writer and producer from Montreal who conducts his routines through a mixture of fluent English, French, Punjabi, and Hindi.

This analysis poised Sugar Sammy in a better position to pick his events, content material and the correct means to connect with his fans, as it provided him insights on how his fans were reacting to his performances.

Fans are engaged and want to praise Sugar Sammy online and the death threats seem to drive negative sentiment. Moreover, there is a connection made with Montreal Canadiens that has had a significant impact on Sugar Sammy’s brand identity as well.

A legitimate data-driven approach, that surpasses the human linguistic complexities, allows brands, be it large consumer product goods organizations or individual influencers, to understand the real conversations that their audience are having. This allows them to connect directly to their audience while reducing inefficient decision making on the content/project roll out, thus helping their overall return on investment.

An extremely small cohort of companies, such as Semeon Analytics, focus all its efforts on research and development of the NLP technology through its product and services. Please feel free to comment below, or reach out if any of this work interests you!

 

Source:

http://searchcontentmanagement.techtarget.com/definition/natural-language-processing-NLP

Fuel your Business Decisions with Dynamics 365 Data

Dynamics 355 - Leverage DataWhat is the main business tool that Sales and Marketers both use on a daily basis? CRM, the business platform that collects and houses an immense amount of your customer’s data. Third-party applications make CRM tools more powerful, and increase the amount of data being fed into the system. Add-ons such as Marketing Automation Software allow for automated email campaigns from the CRM system while collecting user data from email responses. How are you optimizing your sales and marketing efforts without first listening and understanding your customers? Effective campaigns are customer-driven, and what better to use than the data already at your team’s disposal.

Semeon Insights platform employs the power of Artificial Intelligence to sift through all of your customer data to create insights that fuel better business decisions. The Holy Grail is aligning your campaigns with the wants and needs of your customers. Market leaders can respond to customer issues quickly if they are listening to all their channels, and proactively adjust their latest communication strategies by gauging public opinion. Consumers are overexposed to content coming from brands, and this leads to less effective messaging compared to reviews coming from the industry Influencers. Leveraging your Brand influencers provides your consumers with product updates and incentive to purchase from the highest respected opinions in the industry. If you are listening to all your communication channels effectively, your teams will optimize brand influencers with the concepts and ideas that mold public opinion the most.

To get there you need to analyze and understand data coming in from multiple sources, such as Social Media data, Blogs, comment sections, and to combine this with your CRM data to create a 360-degree view of your customers. Combining data from your CRM and your social channels, the interactions between customers and between the customers and your company, allows you to stay ahead of your competition with Actionable Insights.

The type of data Semeon can analyze from CRM includes; sales notes, email responses, customer service interactions, competitor information, basically text that is either structured or unstructured. Semeon Analytics allows you and your teams to quickly understand public opinion, to drive higher engagement and close more deals. Semeon handles any type of textual data, whether it be structured (in forms) or unstructured (free-form such as blogs) and transforms this wealth of data into Actionable Insights you and your teams can use everyday. If you are ready to optimize your sales and marketing efforts contact us today for a free consultation today!

About Semeon: Based in Montreal, Canada, Semeon combines the best semantic, sentiment, intent and statistical analysis. Thanks to its 100 person-years of experience with natural language processing systems, our team of experts has developed a unique platform that affords Semeon’s customers the ability to track what is being said about their brands, products, customers, competitors and helps them do so more rapidly and efficiently than with competing products.

Social Media Analytics Trends in 2017

Social Media Analytics Trends 2017Welcome Marketing Professionals and anyone else realizing the power of analytics. There are many exciting aspects of the market to look forward to, and trends to follow that will lead your business to an effective Marketing strategy. Semeon Analytics has been in the Text Analytics space since before 2012 and have seen all the high’s and low’s, all the passing fads and the features that truly benefit their clients. To give you a sense of where this market is going, the worldwide Social Media Analytics Market is set to grow to $5.40 Billion by 2020, at a Compound Annual Growth Rate of 27.6%. (http://www.prnewswire.com/news-releases/social-media-analytics-market-to-rise-at-276-cagr-to-2020-568584751.html)

There is no surprise that with the maturation of the market, the features are becoming infinitely more effective, while the tools in general have become more intuitive and user-friendly. Truth be told, many of the products just a few years ago were either light on the analytics, or far too complex for the non-Data Analysts. Today, tools like Machine Learning are quickly becoming an essential piece to the Analytics puzzle, allowing platforms to continuously learn while refining their results. Similarly, how Machine Learning is helping Siri answer your questions, it is also helping Analytics tools provide better answers to Marketing teams. Another emerging trend is integrating Text Analytics tools with CRM databases, this can be extremely effective if performed properly. Combining Data Silos such as CRM data and Social Media data, you are creating a 360-degree view of your customers and sales cycle which will provide your teams the insights to drive more sales online and off. In 2017 Influencer Marketing is going to continue to grow. As Brands and companies overload News Feeds and Social Feeds, consumers are becoming weary and fatigued from all this content, leading to lower engagement and decrease in brand trust. Consumers are looking elsewhere to receive their product reviews and information; Industry Influencers have popped up everywhere and have become an essential piece to online branding. More than 75% of consumers identify word-of-mouth as a KEY influencer in their purchasing decision (https://www.getambassador.com/blog/word-of-mouth-marketing-statistics).

With the new Influencer analytics features within the market, brands and marketing teams can keep track and leverage their key industry influencers! Creating strong relationships with these top influencers will lead to stronger social engagement, positive brand perception, and trusted advisors within the industry as your Brand ambassadors, not to mention the free advertisement whenever they post about your products. Content creators can benefit immensely from the influential topics and ideas that some high-end tools provide. Imagine being able to create blogs that resonate with your audience, every time. This is what’s possible when you are analyzing the most influential topics within your industry or surrounding your products and services, providing your team with the tools to grow engagement and sales. 2017 is the year to stay clear of advertising on Social Media channels, people will see right through your efforts and it will only hurt your engagement. Social Media channels are a place to engage your followers, keep them up to date with thought leadership, and nurture your relationship between your customers and your brand. As millennials grow their purchasing power, brands will need to communicate to them anywhere and everywhere. With chat bots and integrated chat features with Instagram and Facebook, personalized customer service will become more essential to any consumer products or services. A strong analytics strategy will provide teams with the insights needed to engage with their consumers intelligently.

Social Media Analytics is a massive ocean of products and services, getting deeper by the day, if you have any questions feel free to ask the experts at Semeon Analytics. Semeon Analytics is a leader in Text Analytics solutions and can provide organizations with Actionable Insights, straight from the consumer, leading to better business decisions. Contact us at marketing@Semeon.com to learn more about how we can optimize your digital marketing strategies.

About Semeon: Based in Montreal, Canada, Semeon combines the best semantic, sentiment, intent and statistical analysis. Thanks to its 100 person-years of experience with natural language processing systems, our team of experts has developed a unique platform that affords Semeon’s customers the ability to track what is being said about their brands, products, customers, competitors and helps them do so more rapidly and efficiently than with competing products. Semeon Analytics

Branding Technique 101: Leveraging your Brand Influencers

Branding Techniques 101Communicating effectively with your audience is no small feat for Brands in today’s Digital Landscape. Social Media networks have become an essential channel to get your message to the right consumers in a timely manner. There is no longer a need for statistics about making purchase decisions online, it is common knowledge heading into 2017 that without an online presence Brands will become ghosts along with the VHS and Pokémon GO.

Successful Brands engage with their consumers on review sites, Facebook and Instagram and provide reinforcement to motivate these consumers to spread their appreciation for the products or services. A key to any successful Brand is leveraging your Brand Influencers. Engaging with your top influencers leads to a stronger relationship with your audience, added value through social proof, and improved brand positioning in the market. Building trust stems from consumers speaking highly of your products and this arises from your Brand Influencers.

When creating content, Brands should focus on creating content with value, motivating your Brand Influencers to share and engage with your content which leads to an increase in your target audience. Get to know your audience, your Brand Influencers are great places to start. What are their interests, do they love the outdoors, are they “Foodies”, this information will fuel your communication strategies and strengthen your relationship with your audiences and boost your Return on Engagement.

Finding and utilizing your Brand Influencers is the tricky part. Many Analytics tools use a Klout Score, which references frequency of posts and is not the complete picture. Brands must consider the influencers’ audience, and expertise when choosing whom best to engage with. Semeon Analytics utilizes a unique Influencer Network to find the most influential people within your industry.

Brand Influencers, trusted advisors for industries online, have become more important today than ever before. With consumers resorting to Ad Blockers, Brands need to find new ways to effectively engage with their audiences that does not involve Interruption Marketing or advertisements that follow you around from site to site.

If you would like to learn about more ways to create effective and dynamics marketing strategies, contact Semeon Analytics for free Brand Consultation.

About Semeon: Based in Montreal, Canada, Semeon combines the best semantic, sentiment, intent and statistical analysis. Thanks to its 100 person-years of experience with natural language processing systems, our team of experts has developed a unique platform that affords Semeon’s customers the ability to track what is being said about their brands, products, customers, competitors and helps them do so more rapidly and efficiently than with competing products.

Apple Watch and Digital Branding- Extracting insights from the online dialogue

Apple Watch - Consumer SentimentConsumer electronics is one of the most competitive industries, with the top technology companies duking it out to be the gizmo in your pocket or briefcase. Once the Iphone 3 came out back in June 2007, Apple products were the most used products in most markets. The Apple Watch came out in April 2015, to a much different public response. The number of devices purchased pale in comparison to the previous iPhone and iPad sales, so what changed?

People were talking about the small screen, the battery life, and the customization to fit their style. Here is where the problem lies; while consumers are eagerly discussing their likes and dislikes of the device, Apple wasn’t listening, and thus was not leveraging the concepts that influenced the markets the most.

The Apple Watch Year-over-Year growth is at a staggering -55% from 2015 to 2016. The overall brand health is dropping, while Apple is still the most valuable brand in the world, companies like Google and Microsoft are growing faster than Apple. Apple has enjoyed overwhelming market share for many years, thanks to its intuitive products and effective marketing. The conversation around Apple products has changed in the last few years, while positive sentiment surrounding competitors has grown. Apple has some of the most dedicated Brand Advocates

Semeon ran two different analyses, one as the Apple Watch came out, and one exactly one year later to see how the consumer opinions have changed. By gathering discussions that happen all around the world, we were able to dissect the ocean of conversations, and extract Insights that provide a 360-degree view of the public perception surrounding the Apple Watch and the Apple brand.

On average, the Apple Watch generated twice as many negative mentions as positive ones. The positive comments were mostly focused on design, rather than functionality or the abundance of apps. The Health and Fitness category is underserved due to the inefficiency of the heart rate monitor, and the poor battery life. These issues, along with the lack of visual variety compared to traditional watches added to the overall negative perception towards the Apple Watch.

Understanding consumer purchase habits starts with extracting the most influential consumer Intentions; such as Intent to Inform, Intent to Complain, Intent to Purchase, etc. Through the Semeon analysis, the most popular actions surrounding the Apple Watch were Intent to inform, which showed up twice as much as any other consumer behavior, and Intent to Complain. The analysis of consumer behavior found online can lead to more aligned Marketing Campaigns, an educated sales force, and a prepared Customer Service team ready to deal with the issues that matter most.

To keep up with constantly changing consumer habits and expectations, Marketing and Branding teams need to stay ahead of the online conversations that drive their brand health and in the end their ROI. The only way to do this is to understand the consumer sentiment, concepts, and behavior that surrounds your brand or campaigns. Semeon Analytics provides teams with Actionable Insights that leads to better business decisions based on the consumers themselves.

If you would to learn how Semeon Analytics can leverage consumer interactions to align your marketing and communication strategies, check out our website www.semeon.com

Post-Election Pondering: What the Data did and did not predict

Trump and ClintonWas Big Data wrong about the American elections?

How can we trust Big Data with Medicine and our finances when it was wrong about the Elections last week?

Big Data Analytics, especially implementing Machine Learning to big data sets, has been a popular topic in Silicon Valley for the last decade. Just in the last few years, it has received celebrity status among popular media sites and dinner tables across the country. The issue lies in the umbrella term that encompasses Big Data, and our inability to take data results with a grain of salt. A popular saying in the Data science realm is “Garbage in, Garbage Out”. What this refers to is the results of Data Analysis depends, to a large extent, on the quality of the data feeding the analysis.

There is something to be said about the quality of data feeding the predictive Election forecasting systems this time around, or specifically the omission of certain groups. In 1968, the “Silent Majority” helped Nixon win his Presidential race, described by Wikipedia as “an unspecified large group of people in a country or group who do not express their opinions publicly”. An easier feat without the advent of the internet and more importantly Social Media as a means of creating a global discussion. Yet, if you perform a simple Google search, you will find a collection of news articles using this term to describe a group of voters who checked off Trump on their ballot.

With the growth of Social Media, there is now a wealth of information on public opinion to be tapped. If I were a man of Statistics, I would choose the sample size of 10,000 opinions over a focus group of 6 any day (margin of error, conformity bias, the list goes on). This being said, the majority of pollsters, data scientists, and predictors were wrong on Election Night. The results of the predictive analysis showed Clinton winning the popular vote. There were a few variables under-considered during the prediction process. The “Silent” Trump voters; those who were less vocal towards their views to save themselves from the moral shaming which was commonly found online and on Social Media.

Many predictive systems employ Machine Learning to perform the number crunching, which is usually based on historical data. The historical data did not prepare the analysis process to consider another previously invisible group, first-time voters. Trump was able to motivate voters who were previously jaded by politics in the past, those who felt their vote did not matter.

What does this say about Big Data and Machine Learning? In the end, these are tools that we can leverage. As businesses and brands alike start to implement a data-driven strategy for their Marketing, Sales, or Customer Service teams, they need to ensure their data solutions properly ingest and clean the data before analyzing. There is only a small number of Data Analytics companies that collect and cleanse the data in-house, Semeon Analytics being one of them. Like everything else concerning Artificial Intelligence, Big Data, and Machine Learning these tools are not meant to replace humans, instead these solutions are meant elevate the human process. The predictions towards the elections does not prove that Big Data Analytics is flawed, rather it should remind us that we still have work to do in adapting these tactics to businesses around the world.

About Semeon: Based in Montreal, Canada, Semeon combines the best semantic, sentiment, intent and statistical analysis. Thanks to its 100 person-years of experience with natural language processing systems, our team of experts has developed a unique platform that affords Semeon’s customers the ability to track what is being said about their brands, products, customers, competitors and helps them do so more rapidly and efficiently than with competing products.

Intent Analytics brings real Insights to Social Media and Big Data teams

Text Analytics drives ROISocial Media and Big Data analytics areinefficient business tools until they take advantage of purchase intent, sentiment, and consumer behaviour.

Without Intent, Social Media Analytics produces flawed and shallow results. Those who can harness the power of consumer intentions, will stay ahead of the competition, create a better relationship with consumers, and sell more effectively. Consumers have more choice than ever, and perform a large portion of their research online while marketers still advertise without utilizing the power of timely and effective user data.

Marketing is more and more about targeted and timely approaches utilizing data to predict purchase cycles for consumers. With Intent Analysis, companies have the ability to send out a targeted coupon to someone who has been comparing products online, or motivate a brand advocate who plans to speak the good word about your company. In the end it better helps you leverage data online and in your business tools and provides insights that benefit multiple departments in a company.


Intent Classifiers

Intent to Inform

“Hey have you guys tried the new Pokémon GO!? it lags but I’m already addicted!”

Intent to Compare

“What has more battery life, the IPhone 6S or the Samsung Galaxy 7?”

Intent to Purchase

“Planning to pick up a new road bike, any suggestions?”

Intent Analysis provides companies andbrands with rich information on not only what people are talking about but how they interact with your products and services in the past, but more importantly in the future. It is true that people do not outright, explicitly, communicate their intentions:

This is why Intent Analytics takes a Machine Learning and Semantic approach to the massive amount of data. Intent action items are key indicators on how your customers and prospects interact with your offerings, how they discuss amongst each other, and how they will interact with your products in the future.

Intent Analysis can also be applied to inbound emails sent to customer service departments, contact center feedback, and data stored in CRM systems.

Smart Analysts will utilize these results to help create effective Marketing Campaigns, personal and targeted advertising, and predictive customer service among other benefits.

Interested in learning more you can visit our website www.semeon.com, follow our blog or follow us on social media

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Elon Musk, and his very expensive Tweet

Elon Musk TwitterElon Musk grew up a self-proclaimed wimp, reading comics, and creating video games from scratch at the tender age of 12. Musk is now one of the most influential titans in many industries, and he is just getting started. Using the power of social media, Elon Musk is shaping the social environment, and empowering his customers to do the same. From researched rebuttals towards the New York Times, to increasing his companies’ stock by $900 million from one single tweet (1). Using Social Media Analytics, we are able to see the effects Elon Musk’s social media has had on his company, and vice versa. While only 10% of CEO’s use Twitter (2), Elon Musk is leading the pact while using Twitter and other social channels for PR, release dates, Marketing, HR, and more. Elon Musk has a unique ability to see what technological tools will help the human race move forward, no wonder he has attached his brand to social media. The social media market has grown substantially in the last 5 years, with predictions of aprox 20 billion in revenue in 2015 (3). Musk has believed in the effectiveness of technology in the everyday life, for decades now. While everyone was trying to get their high score on Minesweeper, Musk was creating online banking services in the form of PayPal and Zip2. In 2002 Musk saw the need for online payment services, and he executed a multimillion-dollar deal with eBay to show for it. He was soon to set his sights to sustainability in the form of electric cars, and solar panels.

Elon Musk is a human predictive analytics machine. He is able to spot global trends years before they happen. Musk has a rare ability to know when the technology, and the market are both ready for a new product offering. Not only this, but he is able to make these products sexy enough that the average consumer wants the products, but just as important, are able to purchase his products. This is all fine and dandy if you are arguably the real-life version of Tony Stark (By the way, he is way more like Bruce Wayne than Iron Man, but that’s an argument for a different post). Companies don’t have the luxury to bet on a feeling, this is where Predictive Analytics comes in. Brands and Marketing Agents are able to see what worked well in the past, what is working in your market from competitors, and what behaviour is most likely to lead to success in the future. Tesla and Musk are marketing kings, with just 35,000 car sales in 2014; they are in the headlines almost everyday, a marketing feat for even the largest companies. Tesla, SpaceX are two examples of content marketing that resonates with users. Through these marketing practices, anyone can increase brand recognition, and motivate your brand advocates to sing the song of your company. Elon Musk is buzz worthy by himself, but his celebrity status has helped improve recognition with his technology companies. Using Semeon’s Sentiment Analysis, we were able to decipher the concepts most relevant to Elon Musk. Understanding the most popular concepts (which you can see in the table below) allows Marketers to get to know their audience better, and allow them to curate content that is more targeted and effective.

Semeon Analytics was able to analyze public opinion towards Elon Musk and the companies he is part of. While Elon Musk’s personal accounts tower over his brands, in terms of followers, his social media channels have strong engagement. Our Sentiment Timeline was able to follow Tesla Motors and SpaceX closely and find out what was truly being said and why. We found that large spikes in posts (by Tesla and SpaceX) align with posts made by Elon Musk. While Social Media exploded with negative comments (6% Negative vs. 2% Positive) following the recent SpaceX rocket crash, Elon Musk’s brand was hardly affected. This is due to Musk’s intuition and his quick responses via Twitter and his social channels.

(1): http://www.telegraph.co.uk/news/worldnews/northamerica/usa/11505566/Elon-Musks-1bn-tweet-news-of-secret-product-line-sees-Tesla-shares-soar.html

(2): http://recode.net/2015/05/17/the-worlds-top-ceos-are-tweeting-more-facebooking-less/

(3) http://www.emarketer.com/Article/Social-Network-Ad-Spending-Hit-2368-Billion-Worldwide-2015/1012357

Learn more about Semeon at: www.semeon.com