Transforming Customer Experience with Big Data Analytics
Transforming Customer Experience with Big Data Analytics
While most businesses know that offering great customer experience creates a competitive advantage, most of them do not have the tools and technologies to approach the issue properly.
The fact that a great customer experience is a sustainable competitive advantage is undeniable. In a recent study, almost 90% of marketers agreed that personalizing the customer experience is critical to their success. Attractive offers, top-notch stores or dozens of features in the products are not going translate into growth for your company if these fail to align with the expectations and needs of your customers. Businesses often find themselves in a situation, where despite doing everything from a textbook, the managers are still seen grappling with basic questions such as ‘What is it that makes my customer unhappy?’
Offering a great customer experience requires a deep understanding of the factors that drive customer satisfaction, or more appropriately, customer dissatisfaction. Identifying key drivers of customer experience and addressing them systematically results in enhanced customer experiences across the customer journey.
So how do you understand what is driving the experience of your customers?
Typical approach to gaining customer experience insights
Typically, companies use surveys coupled with the customer profile (CRM) data to understand their customers. These surveys poll a random sample of customers to learn more about their experience, expectations and feedback. However, a major drawback of customer satisfaction surveys is the actual use of samples. The sample, being just a fraction of the total customer base, may not give you the most accurate insights into customer reality. Practically, the surveys only give an indication of what is happening.
Some shortcomings of this approach are –
- The results can be misleading because they are based on a sample
- The customer profile data does not give a lot of input about customer behavior and dissatisfaction until it is too late
- The results fall short of identifying specific customer experience issues
- The results do not furnish information about the ‘Why?’ behind the indicators
- These results may not be practically useful in providing concrete next steps for the managers or the customer care executives
Adding the missing piece – customer interactions
Throughout the customer journey, customers interact and communicate with a business via a multitude of channels like query emails, support chats, website visits and interactions, social media comments, IVR data, reviews, calls to the call center and call center agent notes. Customers typically use these channels to gain answers to their pressing questions or to voice their opinions. This is a treasure trove of data, rich with insights into experience, behaviors, expectations and pain points of the customers.
Imagine the quality of insights that businesses could achieve if the customer interaction data could be analyzed! But, how do we do it?
Applying Big Data Analytics to Contact Center Customer Interactions
Customer interaction data displays the typical characteristics of big data: it is voluminous: Just the number of calls may run into hundreds of millions in a year! Add to this the transaction and demographic data of the customers. Also, unlike sample-based surveys, analyzing interaction data becomes an exercise akin to a census where each and every piece of information can be utilized to create the most accurate assessment. The data also has variety: dispersed across silos, the data can be structured or unstructured and can come in various formats like text, speech or even visual. Further, the data also has velocity: Unlike the CRM data, the interaction data is very dynamic in nature.
Big data technology enables integration of the customer interactions data with the demographic and transaction data, which can be leveraged to gain insights to transform the customer experience.
Here are a few tips to start the journey of customer experience transformation –
- Assess Maturity: Gartner’s Analytics Maturity Model proposes a 4-step ladder whereby analytics capabilities advance in an organization. Start with an assessment of where your organization stands in terms of basic aspects like people, processes and technology.
- Start small: In terms of data, customer interactions happen across a wide spectrum of channels. Analyzing all of this data can become a complex, time-consuming and capital-intensive task. Hence, it is be prudent to start by leveraging a specific data set, then assess the results and expand the scope to cover other interactions. For example, call center agent notes are a very potent source of customer experience insights. Application of text analytics to the agent notes can reveal crucial insights into customer pain points, call center performance and revenue generation opportunities.
- Go cloud: Cloud platforms are highly reliable and scalable low-cost infrastructure for your analytics pilot. The pay-as-you-go pricing of cloud means you do not incur any capital expenditure upfront. Cloud infrastructure also imparts agility to the project.
- Look for a partner: By sticking to the ‘Start Small’ mantra, you can collaborate with an analytics company to run a pilot and confirm the assumptions. This brings in expertise as well as tools and processes for your pilot before you can scale up the analytics program.
Customer experience is integral to gaining a competitive advantage. Throughout the customer journey, your company’s contact center is the place to go for a confused or dissatisfied customer.When this dissatisfaction or confusion is not handled properly, it results in the customer simply switching to a competitor. In this context, applying big data analytics to the contact center data can provide concrete opportunities to identify the root causes of customer dissatisfaction and address them to offer a delightful experience to your customers.
(The original post appeared in CIO Story magazine. You can also download a PDF version of this article here. Suresh Akula is VOZIQ’s co-founder and CTO.)