Market Research on the Cheap

Working people didn’t spend 20% of their annual income on Encyclopedia sets because some door to door salesman tricked them into thinking how nice it would be to own a bunch of books. People paid high prices for those gold bound Encyclopedias because they wanted to feel like good parents who were giving their offspring an advantage.

Emotions and the desires that spring from those emotions are the reason that people buy almost everything. A successful business understands the buying emotions and the desires of its customers, and finds a way to satisfy them.

Master salesman will tell you that it is impossible to create a need for a product or service that will not plainly satisfy what people want. Some business schools still teach that wants and needs can be created with slick marketing. How little those academics know about human nature.

The purpose of market research is to know your customer, to unravel the bundle of human emotions and find out what your potential customers really want.

Here are three ways that you can do market research on the cheap. Just because the research method is online does not mean that it cannot also be applied to an off-line business.

1. Keyword Analysis. Everyday people type queries into Google and the other search engines on an almost infinite variety of topics. There are free keyword research tools offered by Google and Microsoft, among others, that will return hundreds or results of the exact phrases that people used to find out more about any topic.

Your job as a market research analyst is to look behind the words and phrases that people use to search. Do some phrases have a greater sense of urgency than others? Are some searches more specific about the nature of a problem?

It will take a little practice, but after a while you can develop a sense of what people really want from the keyword phrases they use when they search on the Internet.

2. Active Forums. There are online forums or communities on thousands of different topics where strangers get together and talk about a common problem with more frankness and honestly then they probably would in person. Anonymity has its virtue.

You would spend thousands of dollars to do market research with a focus group. You can do nearly the same thing for free with online forums.

3. The Competitions’ Sales Letters. A professionally written sales letter will deliberately target buying emotions. Top copywriters get paid thousands of dollars to write those sales letters. You can take advantage of your competitor’s research and the copywriter’s expertise by studying the well written sales letter to identify and understand those dominant buying emotions.

Discover the Types of Analyst Resumes

An analyst is a person who does all the investigation, examination and researches on any specific area or sector and then implements the required strategies for improved efficiency and higher productivity. These people should have strong analytical skills and also possess strong thinking capabilities. To start a career in this field, the first step is creating an effective resume that should reflect all the analytical skills of the applicant and also the relevant work experience.

There are many types of analyst resume depending on the type and scope of the job profile. Though the basic structure of all the types remain the same but the specifications and keywords used for creating each type of analyst resume. Specified keywords and other specifications should be kept in mind while writing the resume.

Here are some of the most important types of analyst resumes:

Chemical Analyst Resumes

Chemical analyst is a person who should have an eye to drug formation techniques and methods. He or she examines various techniques to get the best possible methods to verify the reliability of drugs and also determine its quality and stability. The resume of chemical analyst should also possess the same analytical skills. It should have strong keywords showing relevant work experience.

Business Analyst Resumes

Business analyst is a person who analyzes and examines all the business processes and takes care of the operations and functions. Depending on new strategies and techniques based on the research, an analyst plays an influential role in improving efficiency and productivity of any business. The resume of business analyst should also comprise skill sets that define applicant’s role as an examiner of business operations. It should also dictate the achievements and accomplishments of the applicant in the same field.

Marketing Analyst Resume

A marketing analyst is a person who analyzes and verifies price, product competition, customer strength, and economic data of various business firms. This helps any firm to take a firm decision on what to improve and where to improve. This also helps to adopt new strategies and techniques to improve business efficiency. The marketing analyst resume should be written in precise and expressive manner. It should contain work experience with relevant skills and abilities.

Systems Analyst

System analyst or computer system analyst is someone who analyzes the technical design and system requirement. He or she is also responsible for development of new software and also implement the deadlines of various projects. The system analyst resume should also explain in detail the analytical skills of the applicant in terms of computer operations and development.

To know more, check Analyst Resumes.

Careers As a Research Analyst

A research analyst is one who prepares an analysis report based on the research that they convey of the market, product or any business and certain kinds of products or issues. Mostly, this research is done for the upper management in order to have a thorough view of the competitor’s market. The analysis report helps the company to recognize the opportunities in investment or a financial issue that they have.

Career as a Research Analyst

There is comprehensive growth of the research analyst through proper contribution and internal training and development. The career paths of a research analyst progresses as follows:

Research Analyst

Research Analyst is the entry level position where the subject mainly conducts market research at both the primary as well as at the secondary levels. Their analysis provides knowledge about the strategies and trends that have been functional.

Industry Analyst

Industry Analyst creates the overall presentation of the market research in order to evaluate and identify the growth processes. It is an advanced role and requires proper mastery of the industry. One who is an industry analyst should possess proper communicational skill in order to provide the presentation and they should also have leadership skills to excel in their specified industry. Participants in the industry analyst job have entrepreneurial thinking.

Research Director

The next step towards being a research analyst and an industry analyst is research director. The Research Director contributes to the entire management of all the different analysis of the industry by the industry analyst. The manage groups and multiple teams under them. This advanced position requires the candidates to be motivating ad proficient in all different forms of industry analysis.

Program Manager

The Program Manager forms the interface between the client and the research team. They take the primary responsibility to manage the analyst team to ensure the project quality according to the standard of the client requirement. They should meet the standards as well as generate the revenue for the development of the business.

Key Concepts

The research analyst career is highly rewarding in every country. It requires analytic power to properly distinguish the opportunities within an industry. Generally it asks for an advance degree in business, accounting or mathematics. One should have the standard knowledge and the basics about computer. As a part of the organization which makes such analysis reports one can take the opportunities to advance from being a research analyst to industry analyst, director or even program manager. You can advance to masters level or doctorate level if needed.

Meet the New Software Analyst

As US equity markets closed out 2013 at new highs, the future of equity research is facing significant change. With “price targets” being reset for many soaring social, cloud and big data analytics stocks let’s meet the new software analyst. But first, a little background.

Equity research has marginally evolved with investment styles and trading strategies over the past couple of decades. The days of primary fundamental research, particularly on the sell-side, faded long ago. Most analysts don’t have the gumption or the time.

Shrinking commissions and heightened regulatory scrutiny yield lower returns on investment, continuing a cycle of reducing research resources. The sell-side analyst role now has three principal components: 1) to provide access to company managements in their existing coverage universe; 2) to provide coverage for companies that are underwriting clients; and, 3) to provide “hot data points” – particularly for handicapping quarterly results. Buy-siders compete for management access and seek to combine these data points with their own findings to feed trading decisions.

Unfortunately, individual data points legally obtained and disseminated rarely move the needle in providing an adequate sample size on which to base an investment, no less a trading decision. For buy-siders, even aggregating data points from numerous analysts covering a particular sector or company does not provide a relevant statistical sample.

Limitations of today’s analytics

For example, let’s say a mid-sized publicly-traded technology company goes to market with a blend of 100 direct sales teams (one salesperson and one systems engineer per team) and 500 channel partners (mixed 75%/25% between resellers and systems integrators). Further, assume that these teams and partners are dispersed in proportion to the company’s 65%/35% sales mix between North America and international. How many salespeople and channel partners would an analyst have to survey to get an accurate picture of the company’s business in any given quarter?

If a typical sell-side analyst covers 15-20 companies (quintuple that for buy-side analysts), the multiplier effect of data points that an analyst would have to touch makes it humanly impossible to gather sufficient information. Moreover, with 50% of most tech company deals closing in the final month of a quarter, of which half often close in the final two weeks of that month, how much visibility can an analyst have?

Further, why would a company’s sales team talk to anyone from the investment community in the final weeks of a quarter when the only people they are interested in speaking with are customers who can sign a deal? Now consider that many companies throughout the supply chain have instituted strict policies in response to recent scandals to prevent any employee from having any contact with anyone from the investment community.

Even the best-resourced analysts lack the tools to correlate the data points he/she does gather to identify meaningful patterns for either an individual company or an entire sector. Finally, with shorter-term investing horizons and high-frequency trading dominating volume, how relevant are these data points anyway?

The big data approach to research

Stocks generally tend to trade on either sector momentum or overall market momentum. Macro news or events are far more likely to impact a sector’s movement, and therefore a stock’s in that sector. This includes volatility around quarterly earnings – which can run 10%-30% for technology stocks – because the majority of “beats” or “misses” are frequently impacted by macro factors. Excuses such as “sales execution” or “product transition” or “merger integration” issues are less frequent than conference calls would suggest. “Customers postponed purchases” or “down-sized deals” or “customers released budgets” or “a few large deals closed unexpectedly” are more likely explanations.

Now, major sell-side and buy-side institutions are trialing new software that leverages cloud infrastructure and big data analytics to model markets and stocks. Massive data sets can include macro news from anywhere in the world, such as economic variables, political events, seasonal and cyclical factors. These can be blended with company-specific events, including earnings, financings or M&A activity. Newer data sources, including social media, GPS and spatial can also be layered into models. Users can input thousands of variables to build specific models for an entire market or an individual security.

As with any predictive analytics model the key is to ask the right questions. However, the machine learning capabilities of the software will allow the system to not only answer queries but to also determine what questions to ask.

The advantages to both sell-side and buy side firms are significant. They include:

  • Lower costs. Firms can avoid major technology investments by leveraging the scale and processing power of cloud-based infrastructure and analytics software. They can collect, correlate and analyze huge, complex data sets and built models in a fraction of the time and cost that it takes in-house analysts to do.
  • Accuracy. Machine learning and advanced predictive analytics techniques are far more reliable and scalable than models built in Excel spreadsheets. Patterns can be detected to capture small nuances in markets and/or between securities that high-frequency trading platforms have been exploiting for years.
  • Competitiveness. The software can make both sell-side and buy-side firms more competitive with the largest, most technologically advanced hedge funds that have custom-built platforms to perform analytics on this scale in real time. In addition to enhancing performance, the software can be leveraged to improve client services by making select tools available to individual investors.

Analysts become data scientists

The analyst skill set must evolve. They will still have to perform fundamental analysis to understand the markets they follow and each company’s management, strategy, products/services and distribution channels. And they will still have to judge whether a company can execute on these factors.

But to increase their value, analysts will have do statistical modeling and use analytics tools to gain a deeper understanding of what drivers move markets, sectors or particular stocks. Data discovery and visualization tools will replace spreadsheets for identifying dependencies, patterns and trends, valuation analysis, and investment decision making. Analysts will also need a deeper understand client strategies and trading styles in order to tailor their “research” to individual clients.

These technologies may well continue to shrink the ranks of analysts because of their inherent advantages. But those analysts who can master these techniques to complement their traditional roles may not only survive, but lift their value – at least until the playing field levels – because of their new alpha-generating capabilities.