The ABCs of CSAT

CustomerSatisfactionLoyaltyLater this week I’ll be attending the Net Promoter Conference in San Francisco.  I’m really looking covering this event for Research Access.

Customer satisfaction (or CSAT) measurement is a highly specialized, but vitally important, part of the research world.  

Yet I think there are many researchers and marketers who aren’t terribly familiar with the ins and outs of customer satisfaction and loyalty measurement.

Here is a quick ABC guide to what you need to know about CSAT.

S

Satmetrix 

Satmetrix, known as the Net Promoter Company, is the firm that administers the Net Promoter methodology.

A

ACSI

The ACSI (American Customer Satisfaction Index) is a methodology for measuring customer satisfaction.  It factors in the following variables:  customer expectations, perceived quality, perceived value, customer complaints and customer loyalty.

T

Tracking

Customer satisfaction and loyalty are fluid; therefore, most measurement programs involve tracking scores consistently over time.

I

Indicator

Customer satisfaction is a leading indicator of business success; that’s why it’s so important to understand it and take action based on it.

S

SCI

The Secure Customer Index is a customer satisfaction measurement methodology developed by D. Randall Brandt.  The SCI combines three elements – overall satisfaction, likelihood to continue using the service, and likelihood to recommend.

F

Future

The purpose of customer satisfaction research is to assess current attitudes toward a company in order to predict purchase behavior in the future.

A

Answering the Ultimate Question

Answering the Ultimate Question is a book by Fred Reichheld which outlines the Net Promoter methodology.

C

Calculating Your Net Promoter Score

The Net Promoter score is just what the name implies – the net of customers who are “promoters” minus those who are “detractors.”  The core Net Promoter question asks on a scale of 0 to 10 how likely a customer is to recommend the company to a colleague or friend.  The NPS is calculated by subtracting the percentage of customers who give a score of 0 through 6 (“Detractors”) from the percentage who give a score of 9 or 10 (“Promoters”).

T

Truth

Like all research, customer satisfaction research is a search for truth.  There are different approaches, but the search for truth must continue unabated.

I

Index

Most customer satisfaction methodologies yield an index; a single score which is easy for an organization to understand, and, importantly, can be the basis for positive action.

O

Out of Luck

Firms that ignore customer satisfaction altogether will soon find themselves out of luck.

N

Net Promoter

Net Promoter is a customer satisfaction measurement methodology, developed by  Satmetrix, Bain & Company, and Fred Reichheld.  The Net Promoter Score is obtained by asking customers about their likelihood to recommend a company to a friend or colleague.

You can use this link to get a discount if you’d like to join me at the Net Promoter Conference in San Francisco, February 1-3, 2012.

I hope to see you there!

A Primer on the 4 Data Types You Can Collect in Your Market Research

CalculatorMaking a business research questionnaire is no big deal, but making one that successfully derives the information that is actually required by the business to improve its practices is something not every person can do. One of the things that help make an online survey more effective is the understanding of the different types of data that is required out of survey respondents and of the different ways to measure the response. Different situations demand the use of different types of data. Remember, different scales have to be designed to derive these different types of data.

The feedback of survey respondents can be categorized into two basic forms of data – non-parametric and parametric.

Non-Parametric Data

The sort of data that does not have any direction and cannot be divided is called non-parametric data. Usually histograms are used to analyze non-parametric data. There are two basic types of non-parametric data.

Nominal Data

Nominal data refers to alphabetical or numeric data that is used to name people or objects for symbolic purposes and has no mathematical value.

For example, a questionnaire may ask the respondents to name the brand of shampoo they use. Numeric data too can also be included in the category of nominal data such as numbers written on the backs of sportsmen.

Ordinal Data

Ordinal data refers to numeric data that indicates only the relative ranking of different items, without representing the intensity of the mathematical value or the distance between the values. For example, respondents to an online survey may be asked to rank different brands of shampoo.  Hence, the ranking of different shampoo brands will inform researchers the relative preference of survey respondents but will not inform them about the intensity of the difference of preference of one shampoo brand from another.

Parametric Data

Numeric data that has direction is called parametric data. It can be used to analyze the difference the different responses and can also be at times divided. There are two different types of parametric data.

Interval Data

The collection of internal data is done on a scale on which all points are equidistant from the ones next to them. Scales measuring interval data do not have zero because of the nature of thing being measured. For example, respondents can be asked to rate their happiness on a scale of 1 through 10. Interval data cannot be divided because of the non-absolute nature of the data.

Ratio Data

Ratio data is the most absolute form of numeric data collected from respondents. It can be divided and altered in different ways to derive more meaning. All absolute mathematical values can be called ratio data such as income, age, sales, market share, etc.

Although ratio data may seem the most usable form of data and researchers may feel tempted to ask their survey respondents to answer all the questions in ratio form, it is either not practically possible to do so or isn’t the best form of data because of the objective of the research being conducted. An effective online survey questionnaire contains questions that derive the sort of data that will come handy in getting better insight into the respondents’ minds.

The QuestionPro and Survey Analytics online survey platforms allow you to collect all of these forms of data.  The trick is knowing which type to choose to get the best information that you can use in order to make a decision.

Survey Tip: Pay Attention to the Details

blueprintWhy survey creators need to pay more attention to the details of wording, question types and other matters that not only affect results but also how customers view the company. A recent survey from Sage Software had quite a few issues, and gives me the opportunity to share some pointers.

The survey was for follow up satisfaction after some time with a new version of ACT! Call me a dinosaur, but after experiments with various online services, I still prefer a standalone CRM. Still, this post isn’t really about ACT! – I’m just giving a little background to set the stage.

  • The survey title is ACT! Pro 2012 Customer Satisfaction Survey. Yet one of the questions asks the survey taker to compare ACT 2011 with previous versions. How dumb does this look?

  • This same question has a text box for additional comments. The box is too small to be of much use, but also the box can’t be filled with text. All the text boxes in the survey have the the same problem.

  • If you have a question that should be multiple choice, set it up correctly.

Some survey tools may use radio buttons for multiple choice (not a good idea), but this isn’t one of them. This question should either be reworded along the lines of “Which of these is the most important social networking site you use“, or – probably better – use a multiple choice question type.

  • Keep up to date.

What happened to Quickbooks 2008, or more recent versions? It would have been better to simply have Quickbooks as an option (none of the other products had versions). If the version of Quickbooks was important (I know that integration with Quickbooks is a focus for Sage) then a follow up with the date/version would work, and would make the main question shorter.

There were a couple of questions about importance and performance for various features. I could nitpick the importance question (more explanation about the features or an option something like “I don’t know what this is” would have been nice), but my real issue is with the performance question. 20 different features were included in both importance and performance. That’s a lot to keep in mind, so it’s good to try to make the survey taker’s life easier by keeping the order consistent between importance and performance. The problem was that the order of the performance list didn’t match the first. I thought at first that the lists were both randomized separately, instead of randomizing the first list and using the same order for the second. This is a common mistake, and sometimes the survey software doesn’t support doing it the right way. But after trying the survey again, I discovered the problem was that both lists were fixed orders, different between importance and performance. Be consistent. Note, if your scales are short enough, and if you don’t have a problem with the survey taker adjusting their responses as they think about performance and importance together (that’s a topic of debate among researchers) you might consider showing importance and performance together for each option. QuestionPro and Survey Analytics have a special question type just for this.

  • Keep up to date – really! The survey asked whether I used a mobile computing device such as a smartphone. But the next question asked about the operating system for the smartphone without including Android. Unbelievable!

There were a few other problems that I noted, but they are more related to my knowledge of the product and Sage’s stated directions. But similar issues to those above occur on a wide variety of surveys. Overall, I score this survey 5 out of 10.

These issues make me as a customer wonder about the competence of the people at Sage. A satisfaction survey is designed to learn about customers, but should also create the opportunity to make the customers feel better about the product and the company. However, if you don’t pay attention to the details you may do more harm than good.

Idiosyncratically,
Mike Pritchard

[Editor's Note:  This post was originally published on 5circles.com]

Photo Credit

Measuring the Effectiveness of Your Blog

After you’ve been blogging for a few months, it’s a good idea to take a step back, examine what’s worked, and refine your blogging strategy. Especially if you have only recently begun blogging, it’s important to frequently review your strategy and successes, to make sure that you are progressing toward your goals. This can be hard to do if you aren’t sure how to go about measuring your blog accurately, or how to draw the correct judgement out of your information. Let’s examine one methodology to review your blog’s analytics and determine successes. To get started, log into whatever analytics platform that you prefer for your blog, be it Google Analytics, HubSpot, or whatever else is available to you.

Once you’ve signed into your blog, gather all of your blog’s data and export it to a spreadsheet so that you can slice it up and look at it from different angles. Your blog software can usually provide you with this general data, including the author name for each of your posts. If not, you may need to combine data from different systems. This way, you can easily build averages for each of your blog authors for how many views their posts get, or other criteria that you’re interested in. Depending on what data your blog can export, you have many options here – If it exports the tags for each post for example, you could also cut across the tags and see which of your blog’s tags generates the most views, tweets, or conversions on a regular basis.

Break Down Your Post Success By Author

Begin reviewing your blog’s performance by looking at clear breakdowns of your posts, such as by the author. This is an easy to access piece of data, and can show you who your real star authors are. Here is a Google Doc that can help you visualize how to break down your blog analytics by author. If you’d like to use it to get started, you should download it or save it on your own.

While the left contains the raw data from some sample blog analytics, the right hand side breaks down blog post performance by author. In this example, you can see that the average post by Kurt just isn’t performing as well as the other authors. This sheet can’t divine why Kurt’s posts aren’t performing as well, but it can point out the trends that you need to make your own observations. You can take this spreadsheet with you for your analysis – Just paste in your own blog’s data for post title, date, views, and authors into the left, and then fill in the right with the name of each blogger who writes for you regularly.

Look At Other Variables

This process works just as well if if you replace the content of Column D with another attribute that you know – For example, the post category, time of day, or other information. For example, you can do some surface-level research very easily into what times of day are most successful for your blog if you’ve previously tried out publishing posts at different times of the day. Go through your last two months of blog posts and categorize them into rough times of day, like “Morning”, “Afternoon”, “Evening” and “Weekend”. That way, you can break down the post averages by when you post them and see if different times of day lead to more successful posts for you. If you haven’t tried this out yet, spend a month varying up your posting times for your posts, and then check out if there are any consistent patterns.

Consider Your Business Goals

Finally, consider the business goals for your blog. Are you trying to generate conversions or leads? Or establish a presence as an authority on a subject? Review what metric you are trying to change by having a blog, and then look at how you can bring this into the analysis. Remember that the most important part of blogging is how it plays into moving your goals as a business organization. Do not just blog for the sake of doing it; if something is not working in your strategy, or if your marketing analytics show that your hard work is not translating into success, change things up until you find something that makes you successful.

4 Kinds of Survey Error: Sampling, Measurement, Coverage and Non-Response

family feud error

There are 4 generally-accepted types of survey error.  By survey error, I mean factors which reduce the accuracy of a survey estimate.

It’s important to keep each type of survey error in mind when designing, executing and interpreting surveys.  However, I suspect some of them are more ingrained in our thinking about research, while others are more often neglected.

Imagine if we interviewed 100 researchers and asked each of them (“Family Feud”-style) to name a type of survey error.

Which type of survey error do you think would be mentioned most frequently?  Which type would be most overlooked?

Here is my predicted order of finish in our hypothetical example.

Note for the “Feud”-challenged:  Number 1 represents the most commonly named type of error in our hypothetical survey of researchers, while number 4 represents the least commonly named.

1. Sampling Error.

My guess is that sampling error would be the most commonly named type of survey error.

In a recent Research Access post, “How to Plus or Minus: Understand and Calculate the Margin of Error,” I explained the concept of sampling error and gave 3 ways of calculating it.

Sampling error is essentially the degree to which a survey statistic differs from its “true” value due to the fact that the survey was conducted among only one of many possible survey samples.  It is a degree of uncertainty that we are willing to live with.  Even most non-researchers have a basic understanding, or at least awareness, of sampling error due to the media’s reference to the “margin of error” when reporting public survey results.

2. Measurement Error.  

I believe measurement error would be the second most frequently named type of error.  Measurement error is the degree to which a survey statistic differs from its “true” value due to imperfections in the way the statistic is collected.  The most common type of measurement error is one researchers deal with on a daily basis:  poor question wording, with faulty assumptions and imperfect scales.

3. Coverage Error.

Coverage error is another important source of variability in survey statistics; it is the degree to which statistics are off due to the fact that the sample used does not properly represent the underlying population being measured.

There was generally more concern about coverage error in the past; these days, the combination of increasing internet penetration and fast/easy/cheap online survey panels has made it possible to accurately represent many target populations.  Concern about coverage error is still an important conversation; however, it is being discussed more in academic and thought-leadership circles than by the average day-t0-day research practitioner.

4. Non-Response Error.

My guess is that non-response error would be the least named type of error in our hypothetical survey.  Telephone survey houses historically have routinely made 20 or more call-backs to households that do not answer the telephone.  This practice has dwindled due to a combination of the expense of conducting so many call-backs, and the dramatic growth of online surveys, where it is just easier to replace non-responders with fresh sample.  It is also not considered acceptable in an online context to conduct scores of follow-up emails; that would get the sender sent to a blacklist post haste.

Meet the Data Triplets: Data, Metadata and Paradata

tripletsThere are three sorts of data, and very often you need all three to understand and use the data you collect from your survey.

Here are the three sorts:

1. The Data.

The data is the data, that is the actually numbers, codes or open ended text that the respondent enters into the survey. There should probably be a better way of describing this than “the data.”, maybe raw data is a better term to use ?

2. The Metadata

Metadata describes the raw data.

For instance the raw data for question 2 may be a “1” or a “2”. The metadata would say that the value “1” means male and the value “2” means female.  Or the metadata may say that the values for question 3 could be a range of 1-100, or 32-78.

Metadata gives meaning to the raw data, and so it is vital to the analysis process of the raw data that the metadata is present.  Otherwise the raw data is just a collection of numbers with no meaning.

One of the problems with metadata is keeping it connected to the right raw data. The wrong metadata with raw data can be a disaster.

Over the years data formats have got more complex, and one of the big reasons is to keep the metadata with the data. More recent data exchange formats/protocols such as JSON (Javascript Object Notation for the technically minded) have capabilities for attaching metadata to the data, which is a very good thing.

Raw data with no metadata is just a load of junk.

3. The Paradata

Paradata is the least well known of the data triplets. In the past decade or so it has become much more important for the survey research world.

Paradata is data which describes something about the way the raw data was collected.

It is data about data.

The most commonly used form of paradata used at the moment is data about questionnaire and question timings. That is, the time a respondent takes to complete a question or questionnaire.

This type of data is now one of the cornerstones of quality measurements for web surveys.

Obviously there can be many different sorts of paradata. For open ended text questions the length of text entered by the respondent can be measure, as well as the “level of vocabulary” contained in the text.

One metric used for web surveys is that of “speeders,” that is, the number of people who complete the survey extremely quickly. The paradata for time take to complete the questionnaire is used here.

Paradata can also be useful in revealing hidden biases; for instance, using paradata in the gamificaton of surveys is a rising trend. The time taken to do something in a gamified survey as well the action can have a great deal of meaning. Some researchers claim that hidden racism, some times unknown to the subject themselves, can be revealed by measuring someone’s reaction time to specific questions.

In a future post we will delve more into exactly how paradata can be used for quality control of web surveys.

Now We Have Smartphones; Shouldn’t We Try to Be Smarter about Surveys?

This is a presentation from Survey Analytics‘ President, Andrew Jeavons, from the Market Research in the Mobile World Conference in Atlanta in July 2011.

(By the way, it’s pronounced JEH-vons, not JEE-vons, as Andrew explains in the video…)

Andrew presented guidelines for conducting mobile surveys, and he made suggestions for adapting Net Promoter Scores (NPS) in a mobile survey environment.

Enjoy!

How to Use Facebook for Market Research Surveys

It’s an understatement to say that there’s tremendous interest in using Facebook for market research.  Indeed, among the most popular posts on Research Access is one written last year by Survey Analytics‘ CEO Vivek Bhaskaran, entitled “Social Media Research – Using Facebook for Survey Invitations and Market Research.”

What not everybody realizes is that companies are using the power of Facebook’s large audience to conduct research every day.

While Facebook-fueled surveys are not right for every situation, they can be extremely powerful in the right circumstance.  The biggest advantage is access to a massive audience of people who do not normally complete surveys.  However, even Facebook’s large audience will not necessarily yield a sample from the target audience you are trying to reach.  In addition, sampling through Facebook Ads can be expensive, depending on the particulars of your study.

Since Vivek wrote his Facebook sampling post last year, there have been many changes to Facebook, but the fundamental principle outlined in that post still holds true.   So it’s time for an update.

Also, I will explain how to use company or brand fan pages to get valuable feedback.

1) Use Facebook Pages to Reach Your Customers and Fans.

You can ask followers of your company or brand fan page (or your personal page, for that matter) to provide feedback in several ways.

  • Post an open-ended question asking for direct feedback.  For example, “We are looking for feedback on Research Access’ new look and feel.  What do you think?”   You can add language encouraging people to post their comments on Facebook, or you can give an email address for them to contact you directly.  The feedback you receive will be useful but will not be generalizable to all customers or fans.
  • Post a poll.  Facebook now has a “Question” option in the status update box allowing you to post a poll to your fans.  Please note: you can only do one question at a time, and the results will be visible to all fans.  Interestingly, there is an option to allow your fans to add responses which you didn’t necessarily consider when creating your question.

Ask a Question

  • Post a link to a survey.  Instead of using Facebook’s built-in question function, you can simply share a link to a survey.  You should also include explanatory text in the post.  Here’s a hypothetical example Research Access could use: “Please take 5 minutes to give us feedback on Research Access’ new look and feel. Everyone who completes the survey will receive a free eBook copy of QuestionPro for Dummies.”
Post a Link

2) Use Facebook Ads to Reach a Wider Audience.

Using Facebook Ads, you can open your survey up to a massive audience which can be targeted in very specific ways.  Here are the steps for directing Facebook users to your survey using Facebook.

  • Start creating a Facebook by clicking the “Create an Ad” link in the “Sponsored” section in the right-hand column of your page.
Create an Ad
  • Create an ad with an image and a message that will drive the right type of traffic and redirect those who click on the ad to an externally hosted survey.  Select “External URL” in the “Destination” drop-down list.  Put your custom survey URL in the “URL” field.  Use the “Title” and “Body” fields to create a compelling call-to-action for survey-takers.  Be sure to include an image that will garner attention.  In the “Targeting” section, you can target your survey by geography, age, specific interests and more.
  • Define your budget and schedule.  With Facebook Ads you have a great deal of control over your ad’s schedule.  Importantly, you can define a daily budget which will not be exceeded.
  • Finally, preview your ad, then start your campaign!  Good luck.

QR Code-Enabled Mobile Surveys: An Example

 

 

 

 

 

 

 

 

 

 

 

[Editor's Note:  this post was originally published on the Survey Analytics Blog.]

My friend Scott Liang from Parametric keeps telling me – the quicker you collect feedback from the Point-of-Transaction, the better the recall and quality is. While I have absolutely no way of verifying his assertion, in todays Blackberry and iPhone induced ADHD world, it seems logical – and anything that passes the sniff test, works for me!

If we accept that premise, then what the Washington State Ferries in conjunction with the Washington State Transportation Commission is doing is pretty innovative — collecting feedback directly from commuters while they are in the ferry. As passengers are commuting in the ferry, they have options for using their smartphones via QR Codes to give feedback on the ride.

Few innovative options:

Thumbs UP and Thumbs Down:

Instead of having just one QR code that takes them to a survey, the Thumbs Up/Down model has 2 QR Codes – each representing positive or negative emotion espoused by the passenger overall. This is similar to the the universal facebook “like” button that we are all accustomed to in the web world.

FROG on Board Poster

Integrated with MicroPanel:

Users who choose to give feedback are then asked to join a panel for future surveys and feedback. This allows the commission to build a long term relationship with the passengers — the commission can then use this panel for pricing, satisfaction and other kinds of research.

Once the feedback was collected, users are given the option to go to the mobile-optimized page for MicroPanel;

Completely Turnkey:

No custom development. This entire solution is off-the-shelf. This reduces cost and complexity. SurveyAnalytics has as question type that supports creating QR Codes. This enables you to create a survey with multiple QR Codes for each option:




click-here-to-download-the-case-study



How Not to Get Market Research Clients

I’ve worked in many roles in market research, but never as an in-house market researcher in a corporation.  I’ve always felt bad for them in that I know they get a constant stream of suitors among would-be market research suppliers.  In particular, at conferences as it appears they’re being accosted left and right by hungry supply-side sales people.

This Tuesday, November 8th, Tiffany McNeil, Strategy & Insights Manager, Innovation at Del Monte Foods was interviewed by Ray Poynter of Vision Critical on Radio NewMR.  She spoke about a number of topics, including how to – and how not to – get on her radar.

Note:  this interview has been lightly edited.  You can listen to the original interview on the Radio NewMR archive page.

Ray Poynter: What would you define as innovation in market research?

Tiffany McNeil: I’d say that, for me, good innovation is one of two things. Besides a general willingness to be sensible and try new things, which is actually one of the great things about BrainJuicer, I know Tom (Ewing) is the other guest today – we work with BrainJuicer a lot – they have a lot of proprietary tools that are trademarked, and those tools are fantastic, but if you have a question that doesn’t fit with one of the tools that they already have in their toolchest as it were, they are more than happy to try and find a new solution for you. And I think that a lot of other companies do have these trademarked tools, and kind of no matter what you ask them, try to shoehorn whatever your question is into one of those boxes. So I think that’s one thing – just a general willingness to be flexible and try things. And the other is sort of a more traditional answer, which is, kind of a better way to answer questions, either faster, more efficient, or maybe even just more engaging, so that when I present back to my internal partners, it’s something that’s more compelling for them to listen to or to pay attention to.

Ray Poynter: OK, we’ve mentioned one of your suppliers, but in general, when you’re looking for suppliers, what are you looking for?

Tiffany McNeil: It’s hard to say. I think that the suppliers who earn – I can’t speak for my company or my team, but for myself. The suppliers that I’m excited to go back to over and over again are the ones that are just great to work with – the ones who, when you call them, there’s always someone really smart and engaged on the other side of the phone, who are really responsive, who do lots of follow-up work without sort of claiming “scope creep” the second you ask a question you didn’t know the first time. And there aren’t actually that many people who fit that mold, unfortunately. There’s a lot of little mistakes, there’s a lot of sort of people who are really engaged when you’re trying to win the work and they disappear once you get it. So we have probably as a group a pretty small list of suppliers who we feel are always consistently delivering excellent work, and good partnerships.

Ray Poynter: So you have a good list, a small list of people – now, please do not everybody contact Tiffany offering your services…

Tiffany McNeil: [laughter]

Ray Poynter: …otherwise we’ll get nobody wanting to appear on the radio show, from the client side – but, what are the good ways of people getting onto your radar? If somebody is truly innovative, how would you like to find out about them?

Tiffany McNeil: It’s a really interesting question. I was thinking about this a lot yesterday. And I think that – how about this? The way not to do it is to call me and leave me a message, or send me kind of cold emails. I get – you know, everybody gets – but I get tons of them every day. And, not only do I not have time for them, but I also have a lot of guilt about them. It’s just not making me feel good about myself. But I think that when we’re looking for a new methodology or we’re looking for a new supplier, typically the first thing I’ll do is ask around on my team. There is a lot of word-of-mouth – people who have worked in other companies, and may have answered a similar question somewhere else and so might have an idea.

For example, I’m working on a question right now, which isn’t something that I’ve done before – the methodology’s going to require some pretty smart analytics, it’s going to be kind of analytically tough. So in my head I go through the roster of companies that fit that mold. So, you know, who do I know that’s really smart about analytics, and if I come up short, the next thing is I kind of walk around and ask everybody on my team. If I fall short there, I’d say I probably look to thought leadership next. So, Vision Critical is a good example. They are a company that I didn’t really know anything about, and we don’t use them – we do have a relationship with them now, but the way they got on my radar is two things: they showed up at the conference that Lenny (Murphy) chaired last summer – the NewMR new methods conference – but before that, I had gotten a piece of mail that was a list of the top – it actually wasn’t from them – I think it was either from BrainJuicer or from Synovate – one of those two – were also on the top of the list, but Vision Critical I think was top – and it just stuck out as a company that we don’t know, that apparently people like working with. So, that’s an example of how a company kind of got on our radar – now, frankly, we haven’t done any work with them, but I had a conversation with them, and I kind of feel like I know what they do and what they’re good at. And if the right question came up we would reach out to them proactively.

Ray Poynter: Super – and I think probably the list you’re talking about was a thing called GRIT, which is a study that GreenBook run in conjunction with lots of other people, and it has got some interesting questions in there, “Who do you think is innovative?” and yes, BrainJuicer do very well and a number of other companies do very well, including some of the large ones, which I think was an interesting part of that. I’m going to change tack now, and Tiffany, thanks for that, and I hope you don’t receive even more emails especially now that you said that’s not the way to reach you.

Here is Tiffany’s biography:

Tiffany McNeil is a client-side research manager whose circuitous career path brought her most recently to a Strategy and Insights role in the CPG world. Before that, she spent time in New York and London, where she worked primarily in the television industry, including content and editorial research roles at UKTV and Channel Five in London. She is passionate, smart, and opinionated – um . . . and modest charming, but she wrote this herself, so take that how you will. She lives in San Francisco(ish) with her family and spends most her time making lists.