Author Archive

Finding Your Frictionless Feedback

Posted on: April 30th, 2013 by Kurt Williams - CTO

Survey Taker vs Survey Analyst

I recently received an email inviting me to fill out a customer satisfaction survey from one of my favorite online outdoor equipment retailers. I freely admit that I only opened it out of competitive curiosity. When I opened the email, and it promised to take only two minutes and ask two simple questions, I exclaimed, “An NPS survey! ROCK ON!”

But that was me speaking as the survey taker. As a data scientist and survey analyst, I recognized the shortcomings of an NPS-style survey. There’s no way to control the data points in the sample, so this equipment retailer wouldn’t be getting the data required to slice and dice my results in interesting and meaningful ways.

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Analytics and the Power of Early Information

Posted on: June 13th, 2012 by Kurt Williams - CTO

    What kind of an edge can analytics give your business?

It’s a question that’s been asked by anyone who has ever considered investing in analytic technology of any kind. Another way of asking the same question is, “What is the ROI of analytics?”

During a recent visit to San Francisco, an interesting history lesson revealed a powerful answer.

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All Text Analytics Systems are NOT the Same

Posted on: August 1st, 2011 by Kurt Williams - CTO

Claiming that all Text Analytics solutions are the same is like saying all forms of transportation are the same. They’re not.

 

Research your Text Analytics options. Ask your vendor, even Mindshare, all of these important questions. You’ll be happy you did.

  1. Does the vendor’s text analytics platform categorize comments with similar-themed keywords and phrases for comparing and trending? (For example, would the comments “lukewarm cheeseburger” and “the hamburger patty was cold” both be classified under “Hamburger” and “Temperature”?)  Or would you have to mentally group terms such as “cold” and “lukewarm” to understand the scope of a problem.
  2. Does the vendor’s text analytics accurately identify the key topics in each comment individually as they come in? Or does it require a large sample size and batch process?
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Analyzing “Analytics”

Posted on: July 8th, 2011 by Kurt Williams - CTO

It seems you can’t swing a baseball bat without knocking over three or four people asking for analytics: Text Analytics, Predictive Analytics, Social Media Analytics, Decisiolytics, whatever (Mindshare’s CEO recently coined the term “Decisiolytics.” Your guess is as good as mine). The list seems never ending.

What exactly does everyone mean by “analytics” anyway?  For most, I think it refers to the application of arcane mathematical and statistical techniques to mass quantities of numbers. It’s when data geeks and quant freaks in white lab coats pour over reams of data, invoke some sort of mystical incantation, kill a chicken or two, and out pops some kind of interesting “insight” – whatever that is.

Well, that’s all changing. More and more the term “analytics” refers to a packaged-up application that hides the complexity and does the analytics for you, providing the uninitiated workers the ability to take action based on the data. Mindshare’s CoachTM product is a perfect example. Store managers don’t have to know anything about ordinal-logistic-dogeewhatsists. They are directed what to do and they just take action. There was a great article last month that discussed this topic in Information Week:

“What’s Next in Analytics”

“It’s official. The term “analytics” no longer refers only to advanced statistical methods and operational research. It’s now shorthand for what people really want from business intelligence: concise, actionable insight that lets them (1) respond to what’s happening now, and (2) anticipate what will happen in the future, rather than just react to the events of last week or last month. Enter prebuilt analytic applications. As the name suggests, these are off-the-shelf apps, ready-made for specific industries …”

Small, pre-built, easy to consume nuggets of analytic goodness.

Yep.  Analytics. Mindshare has it.

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2011 Sentiment Symposium Wrap-Up

Posted on: April 14th, 2011 by Kurt Williams - CTO

Sentiment. What exactly is it? Why does it matter and why would you want to analyze it anyway? I’ve spent a few days with these questions and have come to a few — hopefully interesting — conclusions.

Jon Sanderson, Mindshare Technologies’ VP of Marketing, often tells me that the key to a good story, whether PR announcement or movie script, is conflict. Think of the last bland movie you saw. Chances are it was lacking sufficient conflict to keep you interested. Conflict is a sentiment – a negative sentiment. Sentiments like conflict are interesting and to your business no sentiment is more interesting than conflict with your customers. This drives many businesses to be hypersensitive to negative reviews in surveys and social media. But negative emotions aren’t the only sentiment worth watching. Both positive and negative sentiment reveal emotional connections with your customers that can and should be monitored.

The best way to monitor sentiment is by simply asking your customers how they feel, like in a survey. This approach has worked for decades and shouldn’t be thrown out just because we think the sum total of human brand opinion is spewed out by Twitter every few seconds (it isn’t!). But surveys have limitations too.  For example, the Milan Travel Bureau found that when customers were asked, “Did you come to Milan for Arts and Culture?” customers overwhelmingly answered in the affirmative.  However, when analyzing Twitter feeds, they learned that the exact opposite was the case. This may have been because most people want to appear sophisticated and cultured, even in an anonymous survey. Unstructured data sources like social media and open-ended survey comments can reveal sentiment insights other methods miss. But what kind of analysis is possible using sentiment?

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