Making Analytics Work For You: How To Improve Customer Service

One thing especially important to businesses is data. While on the surface, it may seem like customer service doesn’t lend itself easily to analysis, that just isn’t the case. As someone who’s worked at a top market research company, I understand intimately how important tracking consumer responses is to a business. 

Providing a good customer experience is absolutely vital, and it’s something that can make or break a company. Knowing how to interpret the resulting data enables businesses to make sound decisions.

Gathering & Analyzing the Data 

Long-term relationships begin with quality customer service. Businesses need to understand who their customers are and what they want, so that they can deliver their requirements effectively. Customer research provides insight into how to improve services and can allow connecting with customers. 

Here are three ways customer data analysis can help: 

●      Identifying key trends: Making decisions requires looking at all the key performance indicators (KPIs) across varying functions. If product delivery lags, knowing where in the supply chain the slowdown occurred will allow decision-makers to fix the problem easily. Data analytics should allow managers to easily visualize what’s happening, so that any issues can be fixed before they become real problems. 

●      Deeper analysis: Customer service data should allow you to analyze which aspects of service delivery work well and which aspects need tweaking.  If complaints are coming from a certain location or specific products, data from customer feedback should provide some insights into eliminating these problems. Knowing where the problem lies will allow you to fix it. 

●      Greater customer satisfaction: You need a way to gauge how satisfied customers are, not only with specific products and services but also with delivery. Quicker delivery can outflank a competitor’s lower price, though assessing this information isn’t always straightforward. Having the right tools to identify what you’re doing right is just as important as knowing what you’re doing wrong.

Retaining customers costs a fraction of what it takes to acquire new ones, so it makes sense to spend where it counts the most.

Plans & Tools

Changes in technology and increased use of social media platforms mean customers can share their bad experiences widely, potentially causing considerable damage to a brand or where there are good experiences, potentially multiplying the customer base. Retail especially needs to understand how consumer intelligence plays a role. 

It’s important, however, to be prepared and have mitigation plans in place. With online giants like Amazon disrupting the traditional retailer business, it’s necessary to address changing circumstances quickly and allocate resources accordingly. While you might not be able to provide rapid delivery of goods/services or the lowest prices, having an effective and responsive customer service will enable you to remain competitive and keep your customers loyal.

Customer service makes up three-quarters of all consumer interactions, so investing in interactions with customers should always be a priority. Dedicated customer service departments can and should help:

●      Analyze data to uncover patterns that explain customers’ needs and preferences. 

●      Create personalized offers in real-time to increase sales and provide targeted assistance. 

●      Gather relevant data through social media and market research surveys to gauge and understand customer sentiments.

●      Use metrics to track customer attitudes to identify issues and opportunities. 

●      Utilize software wherever possible to reduce manual tasks. For example, electronic signatures that make it easier to sign agreements with customers.

Business analytics and other software that supports customer service needs can help predict and optimize relations between businesses and customers. Such tools allow customer service representatives to act fluidly, responding immediately to consumer behavior to help businesses achieve greater loyalty. These capabilities allow representatives to up-sell, cross-sell, or retain customers by refining offers to their needs and desires. 

A Case Study

As an example, Blue Apron – a meal kit delivery service – uses analytics to understand its customers’ behaviors and preferences. It provides subscribers with fixed menus they can purchase, using predictive analytics to project demand. This helps the company avoid spoilage and fulfill orders. 

Using algorithms, Blue Apron uses three categories of variables to predict demand, relating to its customers, recipes, and the season. It predicts what customers will want based on historical data given order frequency and preferences, while taking into account order rates for the time of year.

The company’s engineering team examines the relationship between variables to create models that consistently fall within six percent of actual values. This high level of accuracy shows how employing predictive analytics helps improve user experience and identify customers’ changing tastes over time. 

Author’s Bio

D. A. Rupprecht is an internationally-based freelance writer who writes about business, with an extensive background in market research and customer service. He also writes books occasionally.