How to Analyze your Survey Data Part 2

How to Analyze your Survey Data Part 2

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As we pointed out in Part 1, analyzing your online survey data is tricky business, but nonetheless worthwhile. There are many data points related to surveys that not only illuminate areas of your business but also how effective your surveys actually are.

However, in this case, we're looking at the overall value of your online surveys and how to interpret the data so that you can ensure your next survey is a success.

We're going to do things a bit differently in this post – we're not going to look at how to calculate the data since the basic equations used for all data also applies here.

Click-Throughs (Website)

Essentially, this data point demonstrates how intriguing your online survey is and whether your customers are interested in learning more about you. Visiting your website after they've completed your survey also indicates whether your incentive was compelling enough for them to immediately cash in. To piggyback on this data point, you can see how many pages your customers are visiting after the initial click-through.

Typically, this data point applies mainly to surveys emailed directly to customers, but also can be used with surveys posted on your site. What's different about click-throughs on a posted survey is that you're looking at how many pages your customers are visiting after completion.

Further, social media (Twitter, Facebook, LinkedIn) click-throughs is another data point worth analyzing as well.

Incentive (Most Successful)

It is commonplace for companies to offer a variety of incentives to lure customers in to take their surveys – from coupons to online discounts, incentives are a great way to increase your survey completion rate.

Taking a peak at the incentive trending will give you an idea of which works better. To analyze this data point takes a bit more work because you'll have to backtrack and look at data from older surveys.

Essentially, figure out which incentive drew in the most responses and stick with it.

Also, this indicates the ratio between type of incentive and the number of website click-throughs

Incentive (Least Successful)

Clearly, this is the flipside of the previous data point. You may think, "Well, we already know which promotion is working the best, so why do we need to know what's the worst?" Good point.

Consider the bigger picture: knowing which incentive doesn't work may also indicate which promotion doesn't work in your other marketing strategies. Say, it comes out that the least successful promotion is a discount on shipping. By comparing this data to your other marketing strategies, you'll see a similar trend.

From there, you'll realize that you're going to have to bag the shipping discount in favor of what's universally successful.

Type of Survey (Most Successful)

This data also points to the correlation between the type of online survey and the percentage of completion. Also, this indicates:

  • The ratio of the type of survey and the percentage of customers "cashing in" your incentive.
  • The ratio between the type of survey and the number of click-throughs to your website and social media pages.
  • The ratio between the type of survey and the percentage of incompletes.
  • The relationship between the type of survey, the medium (email or website posting), the percentage of completion and the percentage of incompletes.

Did you miss part 1 of this series? Check out how to analyze your survey data part 1.

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