As I previously wrote, Google Customer Surveys is a true business model innovation. It helps publishers unlock value from their digital assets and enables market researchers reach new audience they otherwise would not have found. I expressed my reservations on their positioning in my previous article
But I do not get what they mean by, “look for correlations between questions” and definitely don’t get, “pull out hypotheses”. It is us, the decision makers,who make the hypothesis in the hypothesis testing. We are paid to make better hypotheses that are worthy of testing.
Since I wrote that article, their Product Manager emailed to say they removed their statement on, “pull out hypothesis”.
This is a limited tool with ability to ask just one question and no way to ensure that the same user will answer multiple questions for doing customer level analysis.
There is one more item which is their minimum sample size. You cannot order anything less than 1000 samples.
Despite these reservations I see Google Customer Surveys as an effective tool for product/brand managers, researchers and small businesses for these purposes:
1. Aided Recall: Present them a choice of different brands ask them how many of these they recognize. 
When you are trying to get very quick and high level data on customer awareness or preference of your brand, this is a great tool. The results are especially actionable when you get extreme results like no one knows about you.
If you are trying to find which brand they recognize the most then you can do that as well with different question type. However, due to its question format limitation, Google Customer Surveys cannot help with Unaided recall.
2. Finding Consideration Set: Present them a choice of different brands and ask them how many will they consider buying for solving a particular need. This is similar to Aided Recall but the question is more focused. You are not simply asking about awareness but whether your brand makes it into their consideration set.
3. Brand Association: Present them an image or a statement and ask them to pick a tag-line or brand they believe 
goes with it. Another variation of this question is asking them to associate your brand with an unrelated field. A typical example is, “if our brand were a movie actor, who will it be”.
Ability to use images is a very powerful feature. It creates many different opportunities. For example for testing your advertising copy or the images you use in your collateral. It is better to poll your audience whether the image you used looks more like a bean bag or boxing glove before you launch your expensive advertising campaign.
4. Consumer Behavior Research: This is a whole class of hypothesis testing you can do with Google 
Customer Surveys. While it is not a tool for A/B split testing, you can use it test your hypothesis on customer preferences or their susceptibility to anchors and other nudges. Before collecting results you need to specify a reasonable hypothesis that is worth testing. When you collect data you can test for statistical significance using Chi-square test to validate your hypothesis. Do keep in mind that sometimes data can fit more than one hypotheses
There is however a big limitation because of the length of questions you can ask (as you see in the third option in the image on the left).
There you have it. A tool with limitations but is effective for specific areas. It opens up new ways to collect data and test when none existed before.
A corollary for this post would be cases where you should not use this tool. That includes finding price customers are willing to pay or asking them about how important a single feature is. You have to wait for another post for the reasons.
Iterative Path 
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