How Big Data Can Improve Customer Surveys

By Jyoti Nigania |Email | Jun 7, 2018 | 6894 Views

Customer survey is the primary source of deriving customer feedback for many companies, despite the growth in embracing of other customer feedback sources like social media, call center conversations and emails. It usually contains structured questions, requesting customers to rate their level of satisfaction with their experience. Two common customer surveys are relationship and transactional surveys. The main difference between these two surveys is that relationship surveys measure attitudes about the experience and transactional surveys measure attitudes in the experience. These approaches of the survey are used to help businesses to improve the both strategic and tactical decision-making power.

Customer surveys provide the relevant information about the customers. This provides the customer experience analytics which leads to generate the customer insights drive the business forward. In this Big Data world, it's clear that businesses can use different sources of data like buying behavior, number of calls etc. as well as the latest technology to get extra customer insights. Companies can do following things to improve their customer surveys: 

Set clear analytic goal: Companies are integrating different data sources collectively to get better insight about their customers. Companies are scrutinizing data from CRM systems, public data and inventory data to make better predictions about customers. We should set very clear goals for the analysis and approach data with a specific problem and try to get solve the problem at the earliest. Analytics is the best way to identify how to optimize an outcome and how to improve the operations to increase customer satisfaction. 

Personalize Reporting: As more the data the more analytics and metrics will come, and this can also be presented in a variety of ways because not everybody didn't need the same the report with the same metrics so in this manner reporting can be personalized. As different level of person in the organization needs different type of information as high level management requires the reports for the strategic decisions and in this same manner this report is useful at different levels in the organization.
Hence, different roles in the organization require different types of information to support the decision making.

Leverage Text Analytics: The data which is collected is in two formats like structured and unstructured. As more the data generated is the amount of unstructured data. Hence there are many more ways to collect the data from the customers. Text analytics is only applied to know the right insights about the various things.

First, text analytics can classify comments into general themes, which helps in identifying the common critic points of the customers. Basically we can get the feedback from the customer whether they have positive or negative attitude.  
Second, from text analytics we can also extract customer's sentiments or attitudes. Facebook and Twitter the social media sources are the best example for analyzing the customer's sentiment.

Use real loyalty behaviours in analysis: These surveys basically include questions asking from the customers to show their loyalty intentions and build the relationships with them like they get to know they recommendations, whether they buy in future or not.  Companies also maintain the history of the customer's loyalty behaviours in their respective CRM. If the business understand the behavior of their customer then it's very easy to survive in the market. 

Customer experience programs need to adapt in this world of Big Data. Companies need to integrate four things in their customer survey process as mentioned above like identify business goals of analytics, personalize reports, leverage text analytics and use objective loyalty behaviors in their analysis. Leveraging these practices will help in expanding the growth of the companies by getting feedback from customer surveys.

Source: HOB