Data analytics (DA) is the process of examining data to draw actionable conclusions. Data analytics requires specialized systems and software. Data analytics softwares range from basic reporting, online analytical processing to advanced analytics.

Data analytics can help companies

  • Increase revenues,
  • Increase efficiency of operations,
  • Optimize advertising channels and
  • Enhance customer service.

Companies can also map their target segments to customer behaviour to identify faults. This not only increases their marketing effectiveness but also helps them in responding better to market trends. The ultimate goal is to boost business performance and stay ahead of its competition.

The rise of internet, e-commerce, and social media has changed how the industry looks at consumer behavior data. Cash registers have made way for e-commerce sites which record customer moves. Customers post their views and purchases on social media platforms and forums.

Thus, we see that companies have an overwhelming amount of data to measure and analyze. Data Analytics transforms all feedback into customer insights.

Data collection across all channels

 Studying customer behaviour requires collecting a huge amount of data from various sources. These sources could be internal or external (social media or regulatory bodies).  Internal sources for data is all relevant information throughout the customer journey. It includes a lot of transactional data and customer feedback.

External data from social media helps companies peek into the minds of customers. It provides an unfiltered view of customer opinion.

Some industries use governmental bodies to collect complaints. For instance, Consumer Financial Protection Bureau collects all complaints against any financial body.

Incorporating data analytics into the feedback system is beneficial for a company in many ways:

1.Establishes the company as a pioneer

 In today’s competitive market, it is important to do something first and be the pioneer. Companies can come up with creative offerings with the help of data analytics tools. This data could be about customer preferences data, market movements and shopping patterns.

  1. Easy decision making and measurable results

Decisions made without the backing of data can be inaccurate and time-consuming. Using data analytics, a company’s every decision can be data driven.

Customer feedback helps companies stay on top of his ever-evolving preferences. Analyzing this feedback can help companies work on specific legs of the customer journey.

The results that are quantifiable (in revenue or CSAT scores) can go back into the system for learning.

  1. 360-degree view of the customer, leading to a better customer experience.

A customer analytics tool considers every single facet of his experience with the brand.

Without knowing the customer well, a brand cannot engage with him effectively. Without meaningful engagement, providing a great customer experience is not possible. Data analytics tools help a brand get a 360-degree view of its customer. They analyze every single piece of information to understand the customer as a whole.

This way, attention to detail becomes a part of the customer experience strategy. Moreover, it becomes easier to address issues which customers often do not voice.

Predictive Analysis

 Traditional method of problem-solving deals with issues as and when they happen. Here’s where data analytics acts a game-changer. Using predictive algorithm tools, companies can predict how customers react. They can then change their strategy to avoid unfavorable outcomes.

These tools also benefit customers. They can customize the offerings to them, based on their interests.

Different ways in which companies can use predictive analysis tools are:

  • Change strategies to tackle customer attrition.
  • Make appropriate changes to key touch points to enhance customer experience.
  • Improve cross-selling and add on selling rates.
  • Improve voice of the customer program.

The work that goes into delivering an excellent customer experience is immense. In the past, brands experimented with strategies to narrow down on the ideal recipe. Data analytics makes it easier to identify his demands and form an engagement model. Data analytics is a vital link between feedback systems and a delightful experience.

 

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