4 Ways Big Data can Help Get the Most from Customer Surveys

For the majority of companies, customer surveys continue to be the primary source of customer feedback. Regardless of growth in other feedback sources such as word of mouth, social media and email customer surveys are still top of the game.

Typically a customer survey will contain a number of structured questions asking the customer to rate their experience satisfaction levels. There are many types of surveys on the market but the most popular are transactional and relationship surveys with the sole purpose to improve strategic decision making.

RELATIONSHIP SURVEY measures a customers attitude over a period of time

TRANSACTIONAL SURVEY measures a customers experience based on one experience

The Data

The data received from surveys is rich with information about customers experiences. Use this information wisely and it can help drive a business forward. But what can a company do to improve the information that comes from their customer surveys?

Have a Clear Goal in Mind

Due to increasing changes in technology, companies can gain information on almost anything. Having access to lots of data is great but it can be mind blowing and leave companies in a never ending cycle of data analysis.

With data coming from difference sources and thousands of variables to consider it is not surprising that companies in the United Kingdom struggle to get any action points to take forward.

From the offset it is important to get clear goals. Take a look at the data with a clear problem in mind to be resolved. Another way to look at this is to think of an outcome and review the data to see whether this outcome is possible. Alternatively look at customer ratings and create a plan on how you can improve these in the near future. Here are some tips from Survey Monkey.

Personalise Reports

Not everyone interprets reports in exactly the same way. Reports and metrics should be tailored to meet the different needs for different levels in the organisation.

Executives will need information at a summary level to enable them to make strategic decisions whereas those on the shop floor would prefer extensive metrics to help them improve processes and controls. Shop floor staff may also appreciate real time data as suggested by survey provider Questback. Processing data will help each group of individuals to make decisions quicker.

Dealing with Text Analytics

Text analytics is perfect for gauging how happy a customer is. The data is classed as unstructured. Unstructured data is raw data and is the role of the data analyst to pull out key information from the text analytics. See here for info.

Text analytics should be categorised into general themes to help develop a plan going forward. Having a good understanding of what your customers think of you is the first step to putting relevant controls and processes in place to make improvements.

No company is perfect so any negative feedback should not be ignored or brushed under the carpet. A successful company would turn this feedback around and use it to make improvements.

The most common way of getting text analytics is via social media channels such as Facebook and Twitter.

Customer Loyalty Metrics

A customer relationship survey is often used to include questions about loyalty. Typically opening questions would include the words buy, buy more, recommend. However this sort of information is often found in a CRM system which would make these questions in the customer relationship survey obsolete. Companies are very interested in predicting the loyalty of their customers rather their behaviour.

In the past we have over inflated the importance of a customers experience. Companies need to do what they can to monitor loyalty of their customers. Feedback will dictate why customers are loyal and therefore companies can ensure they continue doing what they are doing.

Conclusion

We live in a world now where we are surrounded by data. It is the responsibility of companies to take advantage of this data and use it in the best possible way. Data can dictate customer behaviour and their future spending behaviour. The feedback can also give companies autonomy to improve controls and processes so that they become the leader in their chosen field.

There are four things companies needed to incorporate into their process of analysis customer surveys; identify goals, personalise their reports, manage text analytics and measure customer loyalty metrics. Adapting these four headlines will ensure companies get the most from their customer surveys.