Do-It-Yourself Research is on the Rise

Roe vs. Wade, Gun Control, Immigration & Capital Punishment. 

It wasn’t that long ago where a simple conversation about Do-It-Yourself Online Research (DIYOR) among the Market Research community felt like a heated debate with the same intensity of the aforementioned topics.

For all intents and purposes, let’s not debate the pro/cons and the validity/invalidity of DIYOR within this space. These topics and arguments are already well documented and discussed. Instead, let’s take a look at the industry’s past, present and future.

DIYOR began in the late 1990’s and moved past the introduction stage of the product life cycle in the late 2000’s. Its current fragmentation of companies resembles the fragmented Market Research Industry where a handful of major players are accompanied by a majority of smaller companies.

DIY Research is in the growth stage of the product life cycle

The DIYOR Industry, as well as the NewMR Industry in which it is a subset, is presently within the growth stage of the product life cycle as revenues are increasing year over year.  Some suggest the industry is cannibalizing Traditional Research. However, relatively recent worldwide sales figures suggest that NewMR is supplementing Traditional Research, not cannibalizing it.

Some of the major players in the DIYOR market are beginning to behave as if operating within the maturity stage of the product life cycle and are buying competitors, forming partnerships and extending product lines. This behavior seems relatively quick as only a few years have passed since the industry outgrew the introduction stage.  Though, perhaps the move to maturity for some isn’t so quick after all since first and foremost DIYOR companies are technology companies that exist in an ever-changing market.

In terms of present offerings, two key factors have yet to normalize in the DIYOR market: Service & Price.

Service and Research Design in the market range from truly unaided services to aided / self-guided services. DIYOR vendors in the unaided market provide the technology for customers to field quantitative and qualitative studies, but do not assist the questionnaire design process and provide the results of the survey as raw data without data analysis services.  Whereas aided / self-guided companies provide a full suite of self-guided questionnaire design templates as well as data analysis applications. For an extra fee, some aided / self-guided companies can provide an experienced researcher to help design customers’ quantitative and qualitative projects. And of course, there are DIYOR companies that exist somewhere between both ends of the spectrum.

Both services and prices widely vary in the DIY Research market

The relative price of service in the DIYOR market increases or decreases relative to the amount of service provided and overall price points display a fairly wide variance in the DIYOR market.  Charges range from free, to charging per respondent, to charging per month, to charging per year, to charging with sliding-scale credits, to charging for a basic user profile, to charging for an intermediate user profile, to charging for an advanced user profile, to charging for enterprise services, etc., etc. Get the picture?

It's going to be a challenge for consumers to truly evaluate all the different price points, at all the different offerings, for all the different users, at all the different levels of service.  Without a doubt, the rising DIYOR industry is in need of a solid pricing study that will ultimately optimize and ease consumers' purchasing decisions.

So what lies in store for the DIYOR industry? My humble prediction is within the next 5 years, larger full-suite, self-guided DIYOR companies will continue to purchase smaller DIYOR companies that display attractive technology and operate within a niche of the market, in order to add to their portfolios of services. Customers by this time will have determined for themselves which product offering at particular price points makes the most sense.  This combination of vendor consolidation and educated pricing from a consumers point of view will ultimately streamline the DIYOR industry as a whole and normalize its product offerings and prices. 

In your opinion, where is the DIYOR industry heading in the next 5 years? Please comment below.

Chris Ruby is an award-winning Marketing Research & Consumer Insights Executive with Fortune 500 consulting experience. His niche is the ability to turn complex data into compelling stories that induce a call for action among key decision-makers. His work has been featured by MRA, MRIA, IIR, Norstat Times, Chadwick Martin Bailey & the Optimization Group. Keep up with Chris Ruby by following him on Twitter @ChrisRubyMRX or by reading the Chris Ruby Market Research Blog.

The Best Time To Post On Social Media is...?

We've all been there before. We are about to post across Social Media (SM) and that foreboding question finally hits us. “When is the best time and day to post on SM?” I mean, we want as many relevant (maybe even irrelevant) people to see our postings and content, right?

This ever evolving digital social process is called “The Science of Timing” (SOT). If we get it right, everyone lives happily ever after. If we get it wrong, no one gives us a second thought.

The "Science of Timing" predicts the optimal time to post on Social Media

SOT (a.k.a. the optimal time to post) revolves around 5 different paradigms and approaches otherwise known as: The Common Sense Approach, The Segmentation Approach, The Best Practices Approach, The Auto Scheduling Approach, and the Contracompetitive Timing Approach.

Huh?  Keep reading.

The Common Sense Approach is based on an intuitive sense of when people would or would not be on SM. For example, when people are asleep, at work, or at school, they are probably less likely to interact with SM. Whereas, if people are awake and the timing is before, after, or outside of work or school, their likelihood to use SM increases on average.

The Segmentation Approach involves timing based on the SM habits of your targeted audience, which coincidentally, you've collected over time. For example, if you and your organization are targeting teenage gamers during the upcoming summer, you've likely monitored their SM patterns over time, and will run a campaign based on the SM idiosyncrasies they've displayed. In all likelihood, their SM behavior will be different when compared to the entire online population as a whole. Hence, the Segmentation Approach.

In contrast, The Best Practices Approach is based on how the entire SM audience acts as a whole and provides optimal timings based on aggregate online behavior. You can think of it in terms of talking at a cocktail party, where there is a lot of chatter at its peak attendance point.

The optimal time to post on Twitter is late in the weekday, between 2pm – 5pm EST

Dan Zarella, SM Scientist for Hubspot, recently addressed the SOT Best Practices Approach for both Twitter and Facebook. “The optimal time to post on Twitter is late in the weekday, between 2pm – 5pm EST, as this maximizes ReTweets. Coincidentally, we’ve found there is no significant difference in clickthrough rates according to the time of day or the day of the week, so it’s okay to experiment with your Tweets on the weekends and during late hours.”

Zarella further explains, “We've discovered clickthrough rates dramatically reduce, the more you post within an hour.  The clickthrough rate for a second post drops to 50%. The clickthrough rate for a 3rd post within an hour is almost nil.” Zarella is not suggesting to Tweet less as he points to a strong relationship between the number of tweets per day and total followers. Instead, he suggests not to “crowd out” your tweets per hour.

Zarella also suggests three key timing points for Facebook: (1) post every other day as mainstream pages that did this displayed the most likes, (2) post content on the weekends since it elicits the most amount of shares and (3) post content in the morning as shares tend to do marginally better than those published at other times.

Don't "crowd out" your Tweets per hour

But if everyone uses The Best Practices Approach, wouldn't the SM landscape become overcrowded during those specific times and diminish the likelihood of anyone hearing your message?”

Great question.  Keep reading.

The three previous methods require someone from within to personally determine optimal timing. Whereas with The Autoscheduling Approach, 3rd parties determine optimal posting times. But what are these 3rd parties’ optimization practices you say? And how do they measure up to yours?

After investigating Autoscheduling practices, two unique terms surfaced: static vs. dynamic. A static Autoscheduling system optimizes timing based on The Best Practices Approach, not on individual behavior. While a dynamic system optimizes timing through individual / follower behavior, and gets better over time. So which method would you prefer? Find out which method your provider utilizes.

Last but not least, there is The Contracompetitive Timing Approach. This approach is actually the opposite of The Best Practices Approach and circumvents its downside. This territory lies at the beginning and tail-end of the cocktail party, where crowds are smaller in number, thereby improving the odds of individual engagement. By utilizing Contracompetitive Timing, smaller crowds are more likely to hear your voice that would otherwise be lost in the chatter of a full-swing cocktail party.

So which SOT approach is the best? The Common Sense Approach of when people are online? The Segmentation Approach that profiles your specific target audience? The mega-blast to a crowded room, Best Practice Approach? Perhaps the best is The Autoscheduling Approach which leaves it in the hands of the experts? Or maybe the Contracompetitive Timing Approach seems like a valid alternative, so your messages aren't lost in the masses? Perchance it is a combination of all the above? 

In your personal experience, the best SOT approach is _________. (Please comment below)

Chris Ruby is an award-winning Marketing Research & Consumer Insights Executive with Fortune 500 consulting experience. His niche is the ability to turn complex data into compelling stories that induce a call for action among key decision-makers. His work has been featured by MRA, MRIA, IIR, Norstat Times, Chadwick Martin Bailey & the Optimization Group. Keep up with Chris Ruby by following him on Twitter @ChrisRubyMRX or by reading the Chris Ruby Market Research Blog.