Creating an Effective Survey: SurveyStud

Creating online surveys is as much an art as it is a science. It involves attention to detail in the design and flow of your survey. Creating an effective survey that yields actionable insights can be difficult.

Here are 4 tips for creating an effective survey.

1. Keep It Simple

Do you remember taking the SAT or ACT? It’s a long and boring process. Your average survey respondent can start to feel that way about 15 minutes into a survey. Fifteen minutes is a strong upper-limit for most surveys.

When a survey is too long, two bad things can happen:

— Respondents mentality drop out

— Clients get frustrated

2. Use Scales Whenever Possible

Scales are more than a little important.
Rather than asking respondents a basic yes or no question, use scales that measure both the direction and the intensity of opinions.

Scales extend the power of analysis from basic percentages to high-level analyses based on means and variance estimates

3. Keep Coded Values Consistent

Every survey response, option, question, or answer is coded as a numeric value that is reported as a percent of responses or as a mean, median, range, etc.

These values are the basis for analysis.

  — Mean: Often referred to as an average, it is the sum of all the values divided by the number of values.

  — Median: The middle point in a data set. To determine the median, lay out a distribution from lowest to highest and select the middle value.

  — Range: The highest and lowest data points in a distribution form the range. VARIANCE: A dispersion measure of how far a set of numbers is spread out.

For simplicity, keep your scale direction consistent throughout your survey. This makes it easier for respondents to answer and for you as a researcher to conduct your analysis.

The simplest solution is just to keep all scales consistent throughout every survey.

4. Explain Why

Respondents are more likely to help you if they see something of positive value for them. Value offerings can range from a very general altruistic appeal for their help to a very specific offer of an economic incentive. For instance, with a customer feedback survey, you can explain that feedback will help improve customer service.

Here are some quick examples:

Make it specific to them: With employee evaluations, you can explain that feedback will be used to determine awards, promotions, and pay raises and will help management make organizational decisions that will affect them.

Explain unexpected questions: For instance, if it’s important for you to ask toy store customers their preferred color of jeans, you might want to explain why that is relevant.

The plug:  If this made sense to you try our smartphone (survey) app… SurveyStud https://appsto.re/us/Ddj18.i

StartUp Market Research

Research, as a general concept, is the process of gathering information to learn about something that is not fully known. Nearly everyone engages in some form of research. From the highly trained geologist investigating newly discovered earthquake faults, to the author of best selling spy novels gaining insight into new surveillance techniques, to the model train hobbyist spending hours hunting down the manufacturer of an old electric engine, each is driven by the quest for information.

For Startups, research is not only used for the purpose of learning, it is also a critical component needed to make good decisions. Market research does this by giving Startups a picture of what is occurring (or likely to occur) and, when done well, offers alternative choices that can be made. For instance, good research may suggest multiple options for introducing new products or entering new markets. In most cases marketing decisions prove less risky (though they are never risk free) when the StartUp can select from more than one option.

Using an analogy of a house foundation, marketing research can be viewed as the foundation of marketing. Just as a well-built house requires a strong foundation to remain sturdy, StartUp decisions need the support of research in order to be viewed favorably by customers and to stand up to competition and other external pressures. Consequently, all areas of the StartUp and all marketing decisions should be supported with some level of research.

While research is key to StartUp decision making, it does not always need to be elaborate to be effective. Sometimes small efforts, such as doing a quick search on the Internet, will provide the needed information. However, for most StartUps there are times when more elaborate research work is needed and understanding the right way to conduct research, whether performing the work themselves such as using apps like “SurveyStud,” to get a pulse within a specific social-ecospace, or hiring someone else to handle it, can increase the effectiveness of these projects.

Gender vs Survey 

The purpose of this article is to examine the correlation between online (i.e… smartphone via Twitter, Facebook etc.) survey non-response and various demographic factors, including gender.

Studies have shown that trends exist with regard to who responds to surveys, at least with regard to traditional modes of survey administration. Reports suggest that many demographic and other correlates with non-response to online surveys may indeed mirror those of more traditional modes of survey administration. However, the influence of such a basic demographic factor as gender on online survey response behavior is unclear.

In this study, a record-linking technique was employed to compare the gender of online survey respondents directly to available demographic data of all members of a sampling frame, thus allowing comparison of demographic information of both respondents and non-respondents.

The sampling frame, which consisted entirely of university faculty members of a large research university in the southeastern United States with a full-time faculty of approximately 1000, was specifically chosen to minimize the effect of other potential correlates to non-response behavior, such as education level, Smartphone access, geographic location, occupation, and income. Pearson’s chi square analysis showed a significant relationship between gender and survey response rates: female faculty members contributed disproportionately to the respondent data set.

One possible explanations for the observations is that the observed differences in female and male faculty response rates is a product of differences in female and male values operating in a gendered online environment.

Results of this study suggest that researchers should not assume that response behavior toward online surveys, and therefore data gathered from online surveys, is free of gender bias. 

Hence highlights the value of smartphone survey apps such as SurveyStud: https://appsto.re/us/Ddj18.i

Measured Data Analytics: #SurveyStud

History and evolution of big data analytics
The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. But even in the 1950s, decades before anyone uttered the term “big data,” businesses were using basic analytics (essentially numbers in a spreadsheet that were manually examined) to uncover insights and trends.

The new benefits that big data analytics brings to the table, however, are speed and efficiency. Whereas a few years ago a business would have gathered information, run analytics and unearthed information that could be used for future decisions, today that business can identify insights for immediate decisions. The ability to work faster – and stay agile – gives organizations a competitive edge they didn’t have before.

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers; value is abtained in the following ways:

Cost reduction: Big data technologies such as Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.

Faster, better decision making: With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.
New products and services auch as “SurveyStud,” have the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want.

Such as smartphone apps like “SurveyStud,” which mine data analytics, to meet customers’ needs.

Why Conduct a Survey: SurveyStud [Smartphone]

Businesses and researchers across all industries conduct surveys to uncover answers to specific, important questions. These questions are varied, cover a diverse range of topics, and can be asked in multiple formats. Your questions should be strategically planned and structured in the best way possible in order to receive the most accurate data. When structuring your survey questions, consider the following:

– The main goal of the survey

– How you plan to apply the survey data

– The decisions you will make as a result of the survey data

What are the 4 main reasons why businesses and researchers should conduct surveys?

1. Uncover the answers: In a non-intimidating survey environment, you will learn about what motivates survey respondents and what is important to them, and gather meaningful opinions, comments, and feedback. A non-intimidating survey environment is one that best suits the privacy needs of the survey respondent. Respondents are more likely to provide open and honest feedback in a more private survey method. Methods such as online surveys, paper surveys, or mobile surveys are more private and less intimidating than face-to-face survey interviews or telephone surveys.

2. Evoke discussion: Give your survey respondents an opportunity to discuss important key topics. Communicate with your respondents about your survey topic. This allows you to dig deeper into your survey, and can incite topics related to your survey within a broader perspective.

3. Base decisions on objective information: Conducting surveys is an unbiased approach to decision-making. Don’t rely on “gut feelings” to make important business decisions. You can collect unbiased survey data and develop sensible decisions based on analyzed results. By analyzing results, you can immediately address topics of importance, rather than waste time and valuable resources on areas of little or no concern.

4. Compare results: Surveys results provide a snapshot of the attitudes and behaviors – including thoughts, opinions, and comments – about your target survey population. This valuable feedback is your baseline to measure and establish a benchmark from which to compare results over time.

Bottomline if this makes sense to you–try our smartphone app “SurveyStud” (in the app store), and it can help you make well informed decisions.

Embracing Ambiguity 

Instead of offering definitive answers to the country’s biggest questions, the 2016 election results provoke even larger questions. How could the forecasters and the campaigns themselves been so wrong? What and maybe who did all the pollsters miss? Was there a late breaking voter phenomenon that was hard to measure?

These are critically important questions, and investigations are already underway. We may find answers to many of them; we may find others where the evidence will not be conclusive. But we need to let the chips fall where they may, including on my plate as a pollster with a newer platform.

I’m confident in one fact: we canvassed enough people. At SurveyStud we interviewed thousands over the course of the campaign, more than any other public source and more than the campaigns themselves. Our data consistently got big things right: like Donald Trump’s outsized support in the Midwest and Rust Belt.

But there’s another thing that’s absolutely clear to me, and it’s a categorical failing of data wonks trying to grasp certainty through research: too often we are guilty of failing to embrace uncertainty — specifically, the uncertainty embedded in the data itself.

Even our electoral map contained clues that the prevailing narrative was wrong. In our final 50-state map, we had Clinton with only 257 solid Electoral College votes, shy of the 270 needed to win and trending down from the 307 number we showed when we launched our daily tracking two weeks before Election Day. The rest were toss-ups. Our own data showed an open path for Trump. But the surface narrative lined up with the Clinton sweep that our own national numbers and everyone else was pointing to — from the New York Times to HuffPollster to the neuroscientist tapped as this year’s “Nate Silver.” Even the Trump senior adviser who told CNN on Election Day that it would “take a miracle for us to win. It all made the countervailing data points seem smaller than they should have appeared.

Now, people are asking if they can ever trust data again. In fact, we need data more than ever.

We will understand our numerical misses only by getting more information, doing deeper data analysis, and committing to even more rigorous efforts to constantly challenge our assumptions. Since pride tripped us up, humility may prove a better guide.

Some of the big areas for further exploration throughout the polling industry are already clear:

Likely voter models. Whatever the true magnitude of the errors this year, estimating who will actually cast a ballot — a future, yet-to-exist population — has long been a weak part of survey research. In the end, this year’s surveys may have collectively done a really good job at registering voter preferences, but where we all seemed to have slipped is in adequately gauging intent. It’s one thing to support a candidate in one’s head, with a yard sign, or on a survey. It’s another thing entirely to cast an actual ballot for that candidate. We need better, more reliable ways to bridge the gap between attitudes and actions.

Uncertainty estimates. We need better, more user-friendly ways to express the likely variability around polling estimates. More sophisticated poll consumers expect a “plus or minus” around our numbers, but even they latch onto the specific numbers we present. In a sports-dominated culture, numbers automatically become scores. A false sense of precision sets in when media narratives get created out of those numbers. For the most numerate out there, forecasters’ probabilities are a welcome and sufficient way to build in some doubt. Everyone else needs something more.

We are working on all of these challenges — and have the tools to tackle them. At SurveyStud, we’ve built a methodologically rigorous, smartphone-based program for political polls that rivals the best surveys around. But surveys need to be better, and we have the tools to improve our data even more. We’re already moving to develop advanced adjustments to our samples to handle a range of non-response issues; we will leverage external data to make more robust likely-voter models; and we will make everything, including possible errors, more comprehensible.

As usual if this seems plagiarized that’s because it probably is–so if you see something and I need to remove it let me know.  Cool Beans…

President Donald Trump: A Must Read

Donald  Trump represents a throwback to the 1950s — a time when the Midwest was a beacon of affluence for many working class whites with high-paying factory jobs.

What you saw [Tuesday] is the revenge of the angry white working class voter, but I think this really will be the last gasp of the angry white male. 

For months Donald Trump has dismissed polls and experts and proclaimed that he was at the head of a movement of disaffected voters that would upend conventional political wisdom and kick out the Washington establishment. 

The New York businessman was proved right on Tuesday as he rode a wave of anger with economic change, dogwhistle racial politics and pledges to crack down on immigration and rip up trade agreements to a stunning upset win. 

More so one demographic above all took him there: the once solidly Democratic blue-collar white voters that may now be known as Trump Democrats. “The forgotten men and women of our country will be forgotten no longer,” the tycoon declared in his victory speech.

According to exit polls, across the US Mr Trump carried the white voters who made up 70 per cent of the electorate by a 58:37 margin over Hillary Clinton.

Among white voters without a university degree that margin grew to 67:28. But even among white voters with a degree, exit polls showed him carrying the day 49:45, despite surveys that for months had predicted they would be part of a demographic firewall benefiting Mrs Clinton. 

Some have said this was a whitelash. This was a whitelash against a changing country;  others believed It was a whitelash against a black president, in part. And that’s the part where the pain comes.

Tuesday’s scream of the angry white voter was heard loudest in rust belt states such as Ohio and Indiana and threw into play previous Democratic strongholds such as Michigan and Pennsylvania — neither of which had voted for a Republican presidential nominee since 1988.

Overall Mr Trump’s campaign and his appeal to white voters had an ugly side, unleashing a previously unseen level of vitriol in American politics  He was criticised widely for courting the vote of white nationalists and the “alt-right” movement that has taken anti-semitic and racial bullying to new levels on social media.

Yet at the end of the day… regardless of how some feel he [Donald Julious Trump] is the next President of “These” United States of America.

Ok as usual if you feel any of this was plagiarized that’s because it probably was.  If you see something that may be yours let me know and I will remove it.  Cool Beans…. 

New Business

This may sound like a no-brainer, but if you don’t know who your target customer is, you’ll have a tough time retaining loyal consumers. I don’t mean just knowing who your customer is, but really being attuned to everything he or she does, wants and thinks. How old are they? Where do they live? How much money do they make? What colors do they prefer? Where do they buy their clothes? A middle-aged housewife with a disposable income may not be looking to buy a sequin G-string with matching garter, and failing to tailor your product to her needs can quickly result in loads of missed opportunities.

Surveys (using SurveyStud), focus groups and research can be a great way to learn about your customer’s preferences and buying habits. Another helpful tool that worked for me was to identify an actual person (celebrity, athlete, musician) as my target customer. I got to know everything about that person, and was soon able to pick up on little cues and details of what they wore and where they shopped. Now, whenever I’m unsure if a certain style will resonate with my customers, I always refer back to that person and ask myself, “would they wear this or not?” to help me decide. Having a consistent vision across the board, from your product to your marketing, is invaluable these days and can save you a lot of money in the long run.

Startup… Strategy

…keep working at it

Think of a company as a machine you design and build. Your ‘machine’ always has certain parts. It sells something to someone, and re-invests some of that to help make more sales in future. What’s left over is profit for the owners.

A good example of this would be McDonalds. McDonalds built a business that works even if they hire almost entirely minimum wage workers. Their process makes it work: every burger is efficient and nearly indistinct, and nothing is left to chance. Their brand is so strong people line up worldwide to eat there. Your business may be radically different, but it should be similarly robust.

As a company grows the rules and your culture change completely. You may even find yourself disliking the company you created (many founders feel conflicted like this, eventually). If you’ve made it this far, you have many options: hire help, sell, or double-down and see where the ride takes you.

Remember no business can grow indefinitely. Most industries are more efficient at different sizes – it’s easy to be a two-man plumbing company, but near impossible to build a 1,000 man plumbing corporation. Know the limits of yours well in advance. Software is an example of an industry that scales exceedingly well, which is why it creates so many young billionaires.

And finally It’s never been easier to start a company. You can create a killer product in your student dorm without even registering any paperwork – that was enough for Facebook. 

I think entrepreneurship is a form of enlightened gambling. Skill and tenacity are big factors, but luck plays a big part. However, as long as you can keep picking yourself up when you get knocked down, try different things and keep learning, the odds are in your favour. You just have to dare to chance them.

As usual if you feel I plagiarized some of this maybe I did, and if you are aware of some plagiarization let me know and I will change or remove it.  Cool Beans…

Eyes of a Venture Capitalists 

…what a Venture Capitalist wants to see in a pitch deck.

You only get 30 to 60 minutes in front of a Venture Capitalists (VC), so it’s critical the deck has structure–VC Structure.

It’s fair to say I’ve seen many pitches, and I can specifically recall sitting in a pitch thinking, why don’t this guy get to the bottom line. I get tired of seeing thesame miscalculated  presentation week after week–sorry just being honest.

Anyway lets get to the point. I put together what “I feel are critical points during a pitch.”

So the below 6 Slides are critical in a pitch:

          – SLIDE 1: Founders

          – SLIDE 2: Problem / Solution

          – SLIDE 3: Demo

          – SLIDE 4: Scalability / Defensibility

          – SLIDE 5: Distribution

          – SLIDE 6: Projections

Pitch Deck Slide #1 – Founders:  An inviting picture/image, the name of the company, and Management Team up front if you don’t know the investors ahead of time.

Pitch Deck Slide #2 – The Problem and Solution: 

– Problem: You want to move into the problem you are solving, pretty quickly. Skip the backstory, and get to the point – “The problem is X.” If there are multiple problems, focus on the largest and most immediate to start. Avoid jargon and acronyms…keep it straightforward and simple.

– Solution: Within the first couple of minutes, you should be through the introduction, and stated your problem. From there, you should be ready to show the solution, either live (mobile app), or in graphical format on your slide. Speak clearly and confidently.

Pitch Deck Slide #3 – Demo: We are now in the Information Age.  You should not pitch a product… specifically an app, without a demo.

Pitch Deck Slide #4 – Scalability and Defensibility:  At this point, the VC is thinking, “I’m interested in this, or not.” This is another side that should be high-level, without getting too deep into details. Prove two things: show that your product is scalable, and show that it is defensible (can’t be easily copied). Nothing impresses VCs more than founders who show that they are really smart, and are on to something that not many people know about yet.

Pitch Deck Slide #5 – Distribution:  It’s really about communicating how you’re getting to market; this slide shows you have taken the time to research what the best method(s) will be for getting your offering out into the world. A lot of incubators and accelerators today will spend time with their member companies to assemble a proper distribution strategy.

Pitch Deck Slide #6 – Projections: Keep it to one slide, with 2-3 years of revenue projections. Top line operating expenses. Most importantly, what does the cash burn look like, and what’s the head count? Avoid going into a five year model at the early stages. Keep it simple…VCs are only going to remember a few key numbers.

Unfortunately, as a reminder there is no such thing as a “perfect” pitch deck because pitch decks are always being refined and tweaked to optimize for the immediate audience to whom the deck is being presented. In other words, one size does not fit all when it comes to a pitch deck.  BUT one thing I do believe, if you have a demo of your product/app… that means more than any slides you could ever put together. Something to think about…

As always if it seems I may have plagiarized, heck I probably did… BUT I ask that you forgive me, leave a comment, and have a nice day.