Land your Dream Job in 2017: A Guide for Students and Grads in Optimizing your Resume

Best Practices for Resumes

Here are the facts of life: most entry level jobs now require 2 years’ work experience, a university degree, and a part of your soul. Okay maybe not the last part, but in today’s job market it is more difficult to land that dream job based on increased competition and job requirements. Your resume is an incredibly important aspect of your application, if not the most important. Your resume should reflect your ability to organize your thoughts, be detail-oriented, and an effective communicator all without ever using these words in your resume. I am responsible for all hires at Semeon Analytics, and I am here to share with you the most important aspects we, as recruiters, look for in your resumes. This guide will help you craft a relevant and effective resume to propel you to the interview stage! The guide will be broken down between content and format, each with an example resume that showcases the type of resume that recruiters are looking for.



  • Skip your birthday or age, you don’t want an Ageist recruiter disqualifying you because you’re fresh out of school
  • Use a professional email address; this means no Hotmail, Yahoo, or school email accounts . If you don’t already, create a Gmail account with your first and last name
  • Use one line for your contact information, using 4 lines for your personal information wastes a lot of horizontal space on the page and it shows a lack of organization

Ie: Jordan Lavoie | 2135 de la Montagne, Montreal | | 514-778-9637


  • The idea here is to show the recruiter you have previous experience in a relevant field, usually you want to place your most relevant or most recent positions at the top.
    • The reasoning here is Primacy/Recency effect which states that the first and last things you heard will be most likely remembered.
  • Bullet points are the way to go
  • Skip the Skills section (unless you are applying to a technical position like developer) and instead pepper your work experience with skills you learned along the way
  • Skip the fluff words, recruiting software and recruiters usually skip right over the overused fluff words such as; team-player, self-starter, etc.
  • Mirror the language from the job posting so you can ensure your resume reflects what the recruiters are looking for, just don’t copy/paste
  • The name of your resume file is important. Think how many other applicants write “resume” as the title of their document and how complicated it is for the recruiters to find your specific resume in the sea of documents they have. Write your full name and resume to ensure they can search for your resume
  • Remove Microsoft Office from your skills, it is as relevant as a typewriting proficiency in the 90’s
  • Do not add your GPA to the resume, unless it is a magical number such as anything above 3.8
  • Proper grammar is essential in resume writing
  • IMPORTANT: Focus on your accomplishments instead of your responsibilities because they want to see what you could accomplish instead of what was in the job description
  • Remove “References available upon request” as they will ask regardless and it takes us valuable real-estate


  • Use bold to focus the recruiter’s attention on your most important accomplishments, remember recruiters are usually scanning resumes so using format will highlight what you want the recruiters to remember
  • Hyperlink what you can such as your LinkedIn profile
  • Minimal colour can be effective to divide your resume into sections
  • Use the whole width of the page when talking about your work experience and accomplishments –> This shows you are organized and make sure nothing is wasted
  • Keep your resume one page, unless you are applying for a position in management it is unnecessary to have more than one page

There you have it, follow this simple guide and you will be swimming in interviews before you realize.

BACK TO THE BASICS: Understanding Online conversations with Big Data, Sentiment Analysis, Concept Clouds, and Semantic Analysis

Harness Big Data for Big Insights

With the availability of resources online being limitless, Internet users’ each have their own unique browsing habits: visiting social media pages, shopping online, reading about a topic, etc. Naturally, internet users are also having conversations online; it is now easy for someone to voice their opinion online and be heard by thousands.


To put things bluntly, the practical opportunities from a business standpoint are fantastic; online conversations are the equivalent of massive unbiased focus groups and can be leveraged to the benefit of a business.

Take for example Lenovo’s success story: after sifting through thousands upon thousands of online conversations (social media, blogs, forums, etc.), Lenovo created new products in response to the voice of the public. These new products achieved fantastic sales simply because they responded to customer needs that were previously unanswered.

We are now able to gather massive amount of data points (referred to as Big Data) and the ability to analyse them now propels companies to a whole new level of customer experience.

For further insights, we recommend our guide to leveraging your influencers:…/branding-technique-101-leveraging-your…/



Gathering data for consumer behavior used to be time consuming and an expensive endeavor. Today, data can be collected en masse through various channels and networks available on the internet, hence the term Big Data.


There are other important factors besides the obvious time and cost reductions that make Big Data attractive. For starters, the massive amount of data grants businesses the ability of gathering insights with statistical validity, meaning that the voice of consumers is correctly represented. Furthermore, gathering data that is already available online is different than asking for opinions; the data gathered is less likely to be bias, so the true emotions and opinions of consumers will be depicted.

For example, Hertz used to handle customer satisfaction surveys locally for all their 8600+ locations! Not only was it inefficient, but the insights gathered were unable to truly depict the needs, wants and behaviors of the customers because of the surveys being isolated from one another. By switching to Big Data, Hertz went from throwing 8600 small sized fishing nets with difficulty, to easily throwing 1 giant sized net + leveraging new customer data channels previously inaccessible. The value that Hertz received following the implementation of Big Data is easily in the millions.

For further insights, we recommend how big data is revolutionizing how Ad Agencies operate:



We’ve established that online conversations are pivotal for businesses to improve their customer experience. However, having to read every bit of conversations manually and extracting insights is humanly impossible. This is where sentiment analysis come into play.

Sentiment Analysis at its core is the process of analysing conversations and gauging the strength of the emotions behind them in an attempt at understanding a) if conversations are positive, negative or neutral, and b) what aspects of the conversation are positive, negative or neutral.


Sentiment Analysis is a fantastic way for companies to track their brand or products and understand how their consumers react. The main benefit from sentiment analysis alone is the ability to understand the reception of a brand or product in the face of change, for example: after a new product release or a marketing campaign.

The perfect example to highlight the strength of sentiment analysis would be Whole Food’s Asparagus Water situation. After releasing the product, customers were quick to express their discontent online. Had Whole Food implemented sentiment analysis, the whole Asparagus Water situation would have been killed. However, since they did not leveraging sentiment analysing, they were ridiculed by the media, continuously criticised by consumers and their stock dropped in the process until the product was removed.

For further insights, we recommend reading on the trends that are happening in social media analytics:



Powerful insights can now be automatically extracted by understanding the meanings of words and sentences of online conversations, assigning meanings to words be known as semantic analysis.


While Semantic does a wonderful job assigning meanings the words and sentences, the perfect sidekick and the true hero in this story is contextual concepts cloud; the ability to portray and identify the driving forces that influence public opinion. Having the possibility of identifying the elements that bring value to customers, to observe what they care about and see the language they use, are fantastic ways of improving the customer experience.

When Apple released their Apple Watch, the company was keen on gathering the initial feedback from their users. Concept clouds were able to identify that the top concepts were “Apple” and “Watch”. This methodology offers little insights because no meanings can be placed after observing single words with no context. On the other hand, semantic analysis paired with context concept clouds was able to identify that the battery life in the apple watch was a problem that consumers cared about and something that they would want improvements on.

The ability to paint a full 360 degree view enables companies to attain new heights and identify opportunities that would have been impossible to observe without contextual concept clouds.

For further insights, we recommend understanding customers with the use of intent analysis:

Optimizing your Resume-filtering process to improve Quality-of-Hires

Talent Match: Filtering the Best Candidates

A day in the life of a Recruiter usually includes a large portion of reading and reviewing resumes. Since it is now much easier to mass-apply to job openings online, on average corporate job openings attract 250 resumes each! While the number of applicants are continuing to increase, the Quality-of-hire are still inefficiently low. The gap in quality long-term hires starts with the errors at the resume-reading stage. From spending too little time on each Resume, to mismatches between the candidates and the open positions, to the human error layered throughout the reading and matching process. Ask any professional Basketball player to make 100 shots in a row, even they make mistakes and they are the best in the world at what they do. Imagine you are required to read resumes all day long, even the best get tired, distracted, “hangry”, leading to decreased accuracy and even bad employee-position fits.

Here are three Pain Points that decrease accuracy of hires and increase the cost-per-hire:

  1. Latent Human Bias embedded in the resume-reading procedure
  2. Accents/capital letters/differences in language/document formats which are usually automatically disqualified in most Resume Parsers because the Parsers are only Keyword-based
  3. Showcasing why you chose the candidate, without gut-decisions, while ensuring compliance for the Diversity of hires

Machine Learning-powered Resume Parsers such as Talent Match solves these issues with its context-based analysis process. Through the analysis and categorizing of resumes in any format, Talent Match rates candidates based on their whole resume, compared to keyword-based searches. This ensures an accuracy rate of more than 85%, an increase of quality-of-hires, and a decrease in time-to-hire. When looking to integrate Parsers into your ATS or resume databases, make sure the parser can analyze different document formats, otherwise you will lose a large portion of candidates to incorrect digital formats.

Global Recruiting Trends show that the average time to hire is between 1-2 months, this can be greatly improved with a strategy that includes automating the assessing and classification of incoming resumes and organization’s
database of resume. If you are looking to increase your quality of hire while decreasing your time to hire, Talent Match will find you the right candidate faster than ever.

Contact us today for a demo showcasing the benefits of automating your talent matching, leading to higher quality of hires in less time than ever before!

Microtargeting: The Elections, and what Marketers can learn to boost Customer Experience

Trump and Microtargeting

Since the 2000 elections, Microtargeting has been an essential piece in winning the American elections, that is 5 elections in a row that are influenced by this data-driven tactic. Let’s start with a simple definition, what is Microtargeting? Microtargeting is the use by political parties and election campaigns of direct marketing datamining techniques that involve predictive market segmentation (aka cluster analysis). Thanks Wikipedia, us Marketers can learn a lot from how political parties divided up their audiences into segmentations from the data collected online. 17 years later and modern Marketers are now implementing similar techniques to their digital channels.

This data-driven approach starts with collecting data from their multiple channels; whether it be polls, social media data, and demographic interests by state. The next step is the most difficult to execute and regarded as the most important; finding the relevant patterns. Once teams understand the patterns in the data they divide (the demographics) and conquer. In 2004 Karl Rove, considered the “architect” of presidential election by Bush Jr. himself. What Rove realized is each micro-demographic, as in young Latina families in California, have majorly different political agendas. Once these micro-demographics were defined, specific and targeted messages were crafted for each group. For example: These young Latina families mentioned earlier may care most about public schools, while families from the same heritage and state may care more about work opportunities if their children are older. This division of message, is a major technique used in every election, especially this last one by Trump’s political team. Trump, whether you love or hate him, tapped into the voter interests and preferences and possibly most effective was voters’ fears.

In 2017, successful brands can tap into the interests of each relevant demographic, and provide actionable messaging that drives sales and Customer Experience. Consumers have much more power than they did, say 30 years ago, this is due in part to the accountability provided by Social Media networks and the increase in competition over the years. Crafting effective, engaging messaging starts with a robust data analysis strategy.

Semeon provides organizations with the tools to turn consumer data into digestible and actionable Insights, leading teams to customer-focused strategies. Align your marketing campaigns with the relevant audiences to boost ROI and increase Customer Experience. Contact Semeon today for your free Demo today!

Semeon Analytics

How to Get the Most out of Facebook Analytics

“Highly Data-driven organizations are three times more likely than others to report significant improvements in decision making”. The amount of data at company’s disposal is no longer the road block, rather creating Actionable Insights that fuel business decisions from the ocean of data is holding companies back from the full potential of Big Data. Two of the biggest businesses in the United States, Facebook and Google, are Ad Tech. This should showcase how many millions of data points are fuelling advertisement decisions already, and the types of analytics continues to grow. Just recently Facebook updated their Facebook analytics tool to improve the benefits for Marketers and Product Managers, by leveraging Facebook’s user data.

Demographic insights are going to be very important in the next few years within the analytics industry. The amount of data is no longer the problem, but the type of insights created from your business data is. Demographic insights will be fuelled from data coming from multiple sources, to create very clear and descriptive perspectives of the clients throughout the sales lifecycle. Facebook is now incorporating their own anonymized audience data so users can learn what Facebook pages their users like, among other insights, so users can be attuned to their customers and provide products that are aligned with their clients. The other massive feature update from Facebook allows users to compare their audience segments side by side. This is huge for Marketers who are trying to compare and learn what search engines provide the most traffic, or which age group is more likely to engage with video content for example. For marketers, this means the power of asking the right questions, which will lead to the “a-ha” moments. As I have said earlier, successful marketing strategies are at the axis of creative and scientific.

Leveraging your data analytics should be involved in every part of the marketing decision, including the planning, implementing, and especially looking back on past campaigns to learn for the future. Like your history teacher in high-school always said: “if you do not learn from the past, you are doomed to repeat it” Ask your data questions every chance you get, this will lead to new perspectives on your consumers, your digital channels, and your marketing campaigns. Marketers need to be empathetic enough to care about their customers’ wants and needs and how they go about learning and eventually buying their products and services. In this age, we can learn a great deal about our customers and use that to fuel better business decisions across leadership teams, product teams, and especially sales and marketing teams. Modern Marketers need to be able to leverage data to uncover who their clients are, by searching the data to find user patterns that lead to improved communication and product strategies. With the increase in Big Data, marketers will be expected to know more, but with the right data analytics strategy in place they can perform their research and implementation in less time but with more accuracy that ever before.

Semeon Analytics is here to help you make the most of your campaigns analyzing Facebook and Social Media data to fuel better business decisions! Contact Semeon to request a free demo surrounding your digital marketing strategy today!

Big Data & Ad Agencies: Giving Reason to Gut Decisions

Big Data & Ad Agencies

“an overwhelming 83% of [Ad Agency] clients are looking for unique skill sets and specialized capabilities not found in most Ad Agencies or media buying firms.” Two of the areas with the most negative ratings are; Managing the Data explosion (70% were not satisfied) and analyzing data to create personalized experiences (only 29% gave positive reviews). There is not a marketer today who doesn’t want to know more about their customers, but for most teams this is next to impossible based on exclusive data silos, proprietary labels, and the different types of unstructured text. Big Data has allowed Ad Agencies and Brands to proactively learn about their customers from many digital channels, the biggest road-block is transforming the ocean of data into Actionable Insights.

It is said that genius lies at the intersection of creativity and science. Creating engaging, aligned campaigns, comes from a statistics-backed creative process. Netflix and Spotify have fantastic use cases that showcase the benefits of leveraging consumer data to create customer-centric products or advertisements. Netflix has been using Consumer-data from their own streaming service to create products that have high-chance of success in terms of viewership. Using viewer habits, they could make purchase decisions with high predictability rates based on what directors, genres, and the actors’ viewers watched most. Spotify used consumer data to create an engaging campaign surrounding the users’ listening habits in a fun and unique perspective. Another aspect of leveraging data comes from digital channels accelerating the feedback-loop process for testing campaigns before purchasing media space.

Social Media is an effective testing ground for campaigns before they hit the national stage, quickly gauge public perception and proactively align with customer-centric data. Listening to digital channels allows teams to prioritize the channels that help them optimize their customer experience. Ad Agency teams and Brands require a solution that is robust enough to tackle data from any source, transform the sea of data into relevant insights, and analyze textual data instead of counting the frequency of keywords. Semeon Analytics can help Ad Agency teams win more pitches by helping them become industry experts by turning customer data into Actionable Insights quickly. Using customer data, teams can align their campaigns with their clients’ consumers to improve engagement and boost ROI.


Make sure your gut decisions have statistical support, leading to winning more pitches and showcasing your ROI more clearly. Contact Semeon Analytics to learn how you can proactively align your next campaign with the customers that matter most!