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Robert Walker, Editor of ARF Marketing Glossary

Robert Walker, Editor of ARF Marketing Glossary

by | Feb 25, 2020 | Marketing research, Marketing terms, Media Planning

The New-York based Advertising Research Foundation ARF has released a glossary of commonly used marketing research and creative testing terms, aiming to ‘bridge the gap’ between creatives and researchers, and to help professionals keep up with the ever-changing language of marketing. Robert Walker, CEO of Surveys & Forecasts, LLC was the editor, personally reviewing over 1,000 submissions. The glossary is featured in recent editions of Forbes, Media Village, and MR Web.
 
The ARF released this resource for free on its website to those in the industry, students, and the general public who might be interested in learning more about these marketing and advertising terms. An example for “ad recall” can be found here.
 
The ARF uses industry-level research to help its 400 members enhance their marketing advertising initiatives. The ARF describes this effort as ‘the world’s first, definitive glossary’, which will provide standardized terms, and serve as an initial set of guidelines for the industry around often confusing terminology. After one such study, the ARF found a lack of trust and misalignment of terms often fuels the ‘creative-researcher disconnect’, resulting in miscommunication and wasted effort.
 
ARF Chief Research Officer Paul Donato told Forbes: “Methods of creative testing are changing very rapidly. We have recently published a survey among creatives and researchers. Creatives tend to want to use traditional methods of focus groups and ethnographies. Researchers tend to want to use biometrics, facial coding and neuroscience. The glossary attempts to bridge that gap.”
 
For more about the research and consulting services of Surveys & Forecasts, please visit our site or contact us.
 
 
Why Attention Checks Are Essential

Why Attention Checks Are Essential

by | Jan 27, 2020 | Data quality, Marketing research

Typically, when we conduct research of any type, at least two “trap questions” are included.
 
Take the following example from a 2019 study on a consumer product in which we asked: “Which word best describes two people”?
 
Did you know that more than 10% think that Walmart describes two people? These are “insights” that we can do without! Overall, 16% of the responses were (at worst) fraudulent, or (at best) inattentive.
Quality control is but one of many things we care deeply about. Please contact us to talk about how to make your customer relationships healthier through smart research and insights programs. We’re happy to chat even if there’s not a project involved. Click the icon to schedule a call.
Attribution, Walled Gardens, and the Future of MTA

Attribution, Walled Gardens, and the Future of MTA

by | Jan 25, 2020 | Media Planning, Multi-touch Attribution, ROAS

Marketers in the programmatic digital ad space are no doubt familiar with the term “multi-touch attribution”, or MTA. When we speak of attribution in this context, we are speaking of a specific digital “touch” in the customer journey to which we can attribute more or less weight that leads to a “conversion”. A conversion is something measurable: it can be the click of a mouse, a visit to a website, a sale, or some other behavior desired by the marketer. The availability of data at the granular level (individual, behavior, time) has led to the field of analysis known as MTA modeling. Each touch along the attribution train may carry more or less weight depending on where it falls in the sequence of touches for each individual consumer.
 
Now enter the more recent notion of “walled gardens” (aka the ‘attribution apocalypse’). Major providers of digital data, e.g., Facebook, Google, Amazon, Apple, smart TV manufacturers such as Samsung, digital ad exchanges, first-party providers, and any other sources that monitor digital journeys (aka ‘digital exhaust’), are starting to say “we don’t want to play with you”. They are beginning to erect significant barriers to digital data access due to two key factors:
 
  • Regulatory pressure about privacy (e.g., GDPR, California’s CCPA, and others), and;
  • Enlightened self-interest: digital data owners (e.g., Facebook) are preventing outside access, and by implication now claim that they are the best choice for performing any analysis of their digital warehouse (a little like grading your own homework). This entirely freezes out independent companies from performing cross-platform/device analysis.

 

 
The sheer availability of addressable digital data identifiers (e.g., cookies) is also changing. Google is joining Safari and Firefox in blocking third-party cookies in its Chrome web browser (phased out over the next two years). They are happy to go slow: Google makes its money on search and the ability to target. So Alphabet and Chrome are a bit at odds with each other. While cookies were never intended to share as much information as they currently do, how we will replace them will be fascinating. One solution, written about here before, is blockchain. This is an emerging technology that depends upon decentralized identities (either a public blockchain, or a private/consortium-style blockchain) with data that can be acquired or shared by media measurement companies and attribution consultancies.
 
Ultimately, this is an economic decision that has to be made by the end user. How much information is a browser user willing to share in exchange for the convenience and power of the tools they now use for free? And how much of that information are browser developers willing to share with the media measurement companies that want their data?
 
Several important constructs in how advertising actually works are overlooked in the rush to leverage the massive volumes of digital data used in MTA modeling. Data scientists lack industry knowledge about building awareness, memory and message decay, decreasing marginal returns in advertising, and other dynamics that involve brand choice/evoked set, or for that matter, emotion. Three simple examples: context (i.e., environment in which an advertisement is delivered); creative (i.e., the ability of advertising to break through and persuade); and brand (i.e., salience and momentum) have been, more or less, neglected. I have written about the power of great creative in sales forecasting. This concept applies to MTA as well.
 
The objective of all delivered media/advertising, and especially for MTA, is to “get the right ad to the right consumer at the right time”. The hidden assumption is that the consumer is always in the mood to receive the message, and that the consumer fully understands the message. In a world of screen clutter and six second ads, some companies are beginning to change their media and messaging strategy.
 
For example, P&G has shifted its focus to brand penetration (i.e., reach). Excess frequency (which MTA delivers well) has been criticized as wasting media dollars (as I noted, data scientists simply aren’t familiar with decreasing marginal returns in advertising spend). With the savings, P&G is (re)investing in reach. P&G’s Chief Brand Officer, Marc Pritchard, stated “The best measurement is people who are searching. So when we see an increase in search, we see an increase in sales.” This is largely consistent with the overall message of the book “How Brands Grow” by Bryron Sharp, which emphasizes this point and provides many data-supported case studies. Arguably, targeting is perhaps less critical if a company’s products have few demographic or media consumption skews. For others, precision targeting is essential.
 
Up until this point, media and marketing measurement firms have enjoyed a good ride with MTA (such a pun). First-mover companies who are nimble, smart, and have deep pockets can implement big data projects like MTA. And they are achieving significant ROAS – often in the very high double-digit range. And, these companies are able to adjust their models in real time and can continue to reap significant rewards. But, as more competitors build MTA models (or the technology becomes less costly, or the tasks less daunting), a company’s relative advantage will diminish. Think of it as an “MTA trickle-down effect”.
 
I wonder, in 10 years, whether MTA will be thought of as simply a targeting strategy to deliver excessive frequency for the short-term. Or, alternatively, a tool that really helped to build lasting brands and businesses. No doubt, the models will “learn” and become more precise and more “brand conscious”. One of the thought leaders in this space, Joel Robinson, often talks about “brand” vs. “performance” marketing. This is a very useful and provocative discussion: MTA penetration is now at 45% of US marketers based on the 2019 Mobile Marketing Association marketer study.
 
Until then, I hope we do not lose sight of what brands are all about, and that some aspects of brands are simply not measurable. That is, after all, the essence of brands – and marketing.
S&F Conducts Study on 2020 Design Trends for 1stdibs

S&F Conducts Study on 2020 Design Trends for 1stdibs

by | Jan 21, 2020 | Marketing and strategy, Marketing research, Quantitative research, Strategic research, Survey research

1stdibs, the leading global marketplace for vintage, antique and contemporary design, has posted the results of its annual Interior Designer Trends Survey, completed by hundreds of interior designers around the world. The data reflect the tastes of design experts, informing the industry and consumers of the interior trends we will see in 2020. The findings indicate a focus on creating one-of-a-kind spaces through the use of unique, antique or customized products; a growing preference for sourcing items from local artisans and makers; green as the most on-trend color of the year; nature motifs; and an increase in the use of digital platforms for furniture purchases.

“Our partnership with 50,000 of the world’s top interior designers allows us to share the noteworthy trends anticipated for the coming year,” said Sarah Liebel, Senior Vice President and General Manager of Trade at 1stdibs. Survey responses indicate that clients want spaces that showcase unique designs. A majority of designers (55%) expect to source more artisanal and one-of-a-kind pieces in 2020, up from 49% the previous year.

Designers are increasingly using digital tools to discover pieces for their clients, and more than half (56%) say that their purchases were made online last year, compared versus 44% in stores or galleries. In addition, approximately half (49%) of designers say they shop/scan for items on Instagram.

 

Since 2017 Surveys & Forecasts, LLC has conducted this ground-breaking trends report for 1stdibs. S&F is full-service strategic research consultancy based in Norwalk, CT, and for this research conducted 700+ online interviews in Q4’19 with interior designers who are part of the 1stdibs Trade Program.
 
For more info on the findings, read the full press release here, or visit 1stdibs.
 
And let’s set up a time to discuss your research issue – click below!
SurveyMonkey & Customer Satisfaction: Perfect Together

SurveyMonkey & Customer Satisfaction: Perfect Together

by | Nov 11, 2019 | Data quality, DIY software, Marketing research, Research design, Survey research

Happy Birthday to SurveyMonkey, who turned 20 this week.
 

In 1999, when SurveyMonkey burst onto the scene, there were virtually no cloud-based (SaaS) DIY survey platforms in existence. Looking back, we can see that SurveyMonkey was the original “disruptor” in the online survey space: it democratized the process of gathering feedback for companies of all sizes.

 

Unlike it’s far more expensive brethren (e.g., Qualtrics, Confirmit come to mind) who use a “turnstile model” (pay per complete), SurveyMonkey is a flat rate. This lets researchers leverage the platform’s power at almost limitless scale. I can think of no other software platform that is as economical and feature-rich (see a short list of hacks below).

 

Much like disruption in other areas, everyone instinctively knew that online research would change everything. And so it was. Costs were driven lower. Project timing was vastly compressed. But there was a trade-off: the true identity of respondents was often unknown.


This opened the door to a “professional respondent” problem, automated (“bot”) survey taking, and thus outright fraud.

 

In the past 20 years, progress has been made. De-duplication technology (e.g., RelevantID) and identity technologies (e.g., Veriglif, blockchain) are creating positive disruption with solutions to improve data quality. Ultimately, newer technologies and reward structures will put more power in the hands of those who choose to participate in survey research. Data breaches have added to the pressure for more comprehensive solutions. Greater oversight and government regulation are already playing an increasingly powerful role in shaping the future of research and data collection.

 

SurveyMonkey completely changed the “price of entry” for marketing researchers and data scientists. Many tasks can be handled within an environment like SurveyMonkey. But trained professionals in marketing research understand experimental design, buyer psychology, questionnaire construction, and sources of bias that can completely invalidate a research study.

 

The question that companies must ask themselves is: do I have the skill set to grasp these issues, or to leverage the full power of this great platform?

 

As an example, here are 12 powerful SurveyMonkey hacks you should be expert in if you want to hang with the pros (you’ll need a Premier or Professional plan, but they are quite affordable):

 

  1. Block rotation: control order bias by creating identical blocks and then randomizing them. This is extremely helpful for concept screening or conjoint designs.
  2. Skip logic: use choice responses to re-direct to other questions (individual conditions by response).
  3. Advanced logic: show/hide questions/pages using multiple conditions or complex criteria.
  4. Modules: cross-link entire questionnaires by passing system variables.
  5. Stimuli: obtain reaction to concepts or full-motion video, which is easily embedded.
  6. Alerts: use the API, or services like Zapier, to send alerts and feed CRM systems or vizualization tools like Tableau.
  7. Incentives: integrate external rewards (e.g., virtual Visa or Mastercard codes) with services like Rybbon.
  8. Scoring: use algorithms to assign respondents to segments and route them through the survey.
  9. A/B Testing: this allows you to test different language for introducing a question to determine whether there is a biasing effect of wording or not. This is especially helpful in academic work.
  10. Quotas: set quotas based on specific question completion, or quotas based on total responses.
  11. Export: grab your raw data as SPSS or comma-delimited files for use in analysis packages like WinCross or visualization tools like Tableau or PowerBI.
  12. Show Off: create a custom URL for your survey to give it a more professional image, or create “white label” surveys for your company or business, or use CSS to create an entire look and feel for your business.

     

    But maybe you don’t care about these geeky details. What does this mean for you as a Research/Insights Director, Director of Analytics, Marketing VP, or a CMO?

It means that you can get world-class customer feedback for a fraction of what you are probably paying now — without paying any penalty in data quality.

Give us a call to discuss how we can work together to provide you an affordable customer satisfaction or feedback system that really works.
Surveys & Forecasts, LLC