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Callmebymyname market-research-conjointIt’s well known that humans respond to personalization. But, as consumers do we respond more when our name is used when we are being sold to, and if so, why? Specifically, are we more likely to react positively to marketing emails that include our name in it? It turns out that we do indeed, as revealed by an interesting new study to be published in the INFORMS journal Marketing Science (authored by Navdeep Sahni, Christian Wheeler (both from Stanford) and Pradeep Chintagunta (Univ of Chicago)).
 
The researchers were specifically interested in understanding whether including a consumer’s name in the subject line of an email had a positive effect – in terms of the number of emails opened as well as subsequent conversion into sales leads. They ran a classic A/B test where everything was controlled to be the same except the inclusion of the consumer’s name in the subject line. This one tweak was sufficient to increase the probability of opening the email by 20%, which then translated to a 31% increase in sales leads and a 17% reduction in those who wanted to unsubscribe
 
What is interesting here is the nature of the manipulated content. It is non-informative about the product and its benefits, yet still has a significant impact on the consumer’s behavior. This would seem to imply that the effect should be generalizable to other products and contexts as well. To test this they ran two more studies where the products differed as well as the relationship of the consumers to the particular companies. The results were consistent with the first study, establishing the generalizability of the results. “Aspects of the advertising message that are seemingly unrelated to the product can affect how consumers process the message, and significantly change outcomes,” said lead author Navdeep Sahni. 
 
There is then the question of why this occurs. While there are competing theories the best one (message elaboration) seems to be that once their attention is drawn using their name, consumers process the information more carefully. This, of course, has a potential downside in that if the message is not relevant to the consumer then the more careful processing could translate into fewer sales leads and more people unsubscribing.   
 
A rather clever 2x2 design was used to tease out this effect – the recipient’s name was included in the body of the email (or not) and a relevant piece of information in the form of a product discount was included in the email (or not). By including the name in the body of the email, the chances of the recipient processing the message increases. By including the discount the relevance of the message itself becomes higher (or not). So if the psychological mechanism at play is message elaboration, then the condition where attention is drawn and a relevant message is presented should provide the most leads – and that is precisely what they find.  
 
Additional (regression) analysis showed how the pieces fit together. Seeing the name increases the likelihood of the message being read and processed, and increases the chance of a positive outcome – if the message is compelling. By itself, the personalization still has an effect but not as much as it otherwise could with a relevant message.      
 
This research does not tell us what happens when more and more marketers start using email personalization. Will consumers get desensitized to the effect? What if the domain is sensitive? Would consumers get offended resulting in a backlash? The answers are not available in this research as the datasets examined here do not fall into these categories. 
 
But, for now, we can say that email marketers could benefit from including the recipient’s name, and can enhance the effect by having a relevant message in the body of the email.     
 
Tagged in: Consumer Behavior
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advanced-market-research-methods-and-candyAt TRC, the most popular spot in the office is our snack shelf. It features an array of sugary, salty and carb heavy treats. The contents vary and are determined by one person (Ruth, who stocks the shelf) with influence from the rest of us (based on past usage and suggestions). Sometimes the shelf has exactly what you’re looking for. Other times, not so much. But what if instead of relying on Ruth’s powers of deduction we were to use research to figure out the optimal shelf configuration?  We’re researchers, after all. 
 

Start out with Incentive Alignment 

We would start out by using our Idea Mill™ product to generate ideas on which snacks people want to have. It uses incentive alignment and gamification to bring out the most creative ideas and provide direction on the favorites. It is likely that this will create too long a list of ideas (the candy shelf is only so large) and while we can toss out ideas that are not feasible, we believe it is best not to toss out ideas just because you personally don’t like them (I’m looking at you Mr. Goodbar). Far better to get more consumer input…this time to narrow the list. 
 

Go beyond Simple Ratings, Employ a Choice Method

We could ask our folks to rate all the suggested snacks and then use that to figure out which ones should make the cut. Ratings might be good enough to eliminate some things (my guess is that despite what people claim, healthy snacks would bite the dust), but among popular snacks (like different types of pretzels) we are not likely to see clear differentiation.
 
A choice method like Max-Diff could help but if the list was long it would require a lot of work on the part of our employee respondents. A method like our proprietary Bracket™  would do the job in a faster and more engaging fashion while still finding clear winners and losers.  
 

Find a Combination of Flavors that Would Please the Most People 

Stocking the winners would therefore make the most sense…but would it please the most people?
Currently the shelf features five types of M&M’s (original, almond, caramel, dark and strawberry nut). If dark chocolate was the least preferred it might get cut. But what if those who like almond, caramel and strawberry nut also liked original, but those who like dark only liked it. For situations like this we can take the results of the Bracket™ (or Max-Diff) and use TURF  to find the combination that would please the most people.   
 

Find the Best Position on the Shelf with Discrete Choice Conjoint 

Of course, another factor is positioning. The shelf is only so large. M&M’s can be dispensed from any size canister (in fact Ruth has one that spins so that it can dispense three types) while Pretzels tend to come in large bins that take up a lot of room. In addition, not all of the snacks cost the same. In an effort to keep our expenses and waistline under control we follow a strict budget. Might I trade off having greater quantity of a lesser snack in exchange for an expensive favorite? 
 
For these kinds of questions a discrete choice conjoint is the answer. We can include a variety of candy types and constraints related to the room they take up as well as cost. Simulations can then optimize how to spend our candy budget.  
Despite our love of research and wide array of tools though, I think in this case they would be overkill (we have a very small population of around 40 employees). So I think we’ll stick with Ruth’s instincts. I never go wanting….
 
Tagged in: Conjoint
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Half life-Market-Research

I heard a great episode of the “You Are Not so Smart” podcast in which Sam Arbesman talked about his book called “The Half Life of Facts”. This book has nothing to do with “truthiness”, “fake news” or any accusation that someone is or is not a liar, but it does provide some context for the world we live in.
 
The book’s title is taken from a scientific term (the time it takes an isotope to lose half of its radioactivity) and the notion that as we learn more, some things we took as “fact” will turn out to be wrong. Newton’s laws, for example, were supplanted by Einstein. The point of the book is not that we shouldn’t bother learning facts, but rather that we should be open to the possibility that they might be wrong. Modern medicine acknowledges that they don’t know everything and that some things they “know” will prove to be false. At the same time, they must treat patients based on what is known or thought to be known.
 
It got me thinking about our business. What is the half-life of facts here? You might be tempted to take comfort in the fact that things like margin of error have not changed. While technically true, this ignores that academia is facing a crisis of confidence over statistically significant findings that don’t hold up in subsequent studies. One cause for this is they run lots of cuts of the data and look for anything statistically significant and then build a rationale for that finding. They ignore that with so many cuts of the data they are likely to find some statistical noise. Don’t we run the same risk with each additional banner we run?
 
There is a known problem with Discrete Choice Conjoint that is often ignored. If you have a product made up of say 8 features each with three levels and 1 with 150 the importance of the feature with 150 levels will be overstated by the model. Still, the model will run, utilities will be calculated and a simulator can be constructed…all of which provide a sense of precision that is not warranted. A researcher who knows about it will guide the client either by changing the design OR by putting the results into their proper perspective. There are many other ways that a complex model like this can produce skewed results and I have little doubt more will be found in the future. 
 
This is not to say that we can’t trust results. Doctors have to treat patients based on what is known today and we must do the same for our clients. The important thing is that we have to acknowledge we have things to learn. As researchers that should be easy for us…
 
Tagged in: Conjoint
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hp-trivia-pricing-research-monetizing
In my previous blog about HQ Trivia I pondered how the creators of HQ were planning to make money.  Right now there is no advertising; venture capital funds the app and the jackpots. Apart from occasional sponsorships, there appears to be no immediate source of additional funding.
 
HQ could do many different things to achieve financial success – content sponsorships, jackpot sponsorships, advertising, product placement, buying ‘lives’ by watching a 15-second spot  – even sponsor logos on host apparel. In fact, there are probably different ways to monetize HQ Trivia that we haven’t even thought of yet – making this a perfect research case for TRC’s Idea Mill™.
 
Idea Mill™ is our method that employs Smart Incentives™ – harnessing the principles of crowd-sourcing to ask respondents for their best idea, and the ideas are then voted on by other respondents within the same research survey. The respondents with the best ideas as judged by their peers are rewarded with prizes. This is a great technique to use when you’re in the idea generation phase of product development.  
 
Once we get a list of potential ways to monetize HQ, we could then winnow the list to the ones that would be feasible to implement, and narrow the list using a prioritization-based research method such as Idea Magnet™. Results can be generated quickly.  
 
Before implementing the winning ideas, we could further explore options by building various scenarios of the sponsored game, and asking HQers to weigh in on which one would be most acceptable to them. Through a choice-based research tool such as discrete choice conjoint, we could vary HQ’s potential features, such as:
 
      • •  Number of ads or sponsorships per game
      • •  Where the ads appear (between rounds, upon game entry) 
      • •  Prize pool
      • •  Having sponsor-related questions
      • •  Getting bonus ‘lives’ for watching sponsor videos
 
All of these techniques employ strategies we use in pricing and product development research to include the consumer in the decision-making process. HQ’s creators are good at asking questions – I hope they do the same in further developing their product.
 
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GRIT-TOP-50-report

I appreciate that we are once again in the GRIT 50 Most Innovative Research Agencies. Innovation has always been important to me and so I am quite gratified when I see our efforts being recognized. What I don't know is how people are defining innovation.

I think as an industry we sometimes label things as innovative that are not while failing to recognize some things that are genuinely innovative. In my view, innovation requires that we provide something of value that wasn't available before. Anything short of that may be 'interesting' but not 'innovative'.

I would put things like neuroscience or most AI into the "interesting" category. There is a lot of potential but so far little so show in terms of tangible benefits. Over the years at TRC we've had many ideas that showed promise, but ultimately didn't prove out (my favorite being "Conjoint Poker"). Ultimately it is the nature of innovation that some things will never leave the drawing board or 'laboratory', but without them there would be no innovation.

On the other side, I think ideas that save time and money are often not viewed as innovative unless they involve something totally new. I disagree. If I can figure out a way to do the same process faster and/or cheaper then I'm innovating. It may not look flashy, but if it allows clients to do something they couldn't otherwise do it is innovation.

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Tagged in: Pricing Research

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