When it comes to strategic understanding, data insights are not only all the rave, but also the fundamental foundation to building a evidential intelligence for the organisation to follow. Whilst most brands understand the value of data, many are unsure of the various dimensions of value that it can deliver across their end-to-end operations.
In the 1960 American Western, The Magnificent Seven, a group of seven gunfighters are hired to protect a small village. The seven share traits, but are all different and work best together, so too, when combined, the “Seven Data Dimensions” can protect and empower your brand.
This series will provide an overview of the magnificent seven datasets that most brands have access to and that can be leveraged to gain insight and understanding to design strategies, develop tactics, deliver experiences and drive innovation. Working with the global mTab network and other industry experts this series will pull out examples, and top tips, from across the globe where brands are most effectively harvesting and deploying data.
Focused Feedback
Previously, we reviewed social media channels, online reviews, customer feedback and purchase data streams. The next data source we explore is fundamental insight from customer service. Customer Service has been a staple of businesses which have grown and evolved over the past century. Whilst traditionally customer service data has been thought of as feedback, be that enquiries, complaints or recognition, to employees (both in call centres and retail units) increasingly there is a plethora of useful customer service feedback collected through apps or online service bots. Whilst many brands view Customer Service as a ‘necessary evil’ or a ‘cost to do business,’ customer-centric businesses tend to focus on the information derived from the CS operation, and tie it into the operations, product development, marketing and innovations of products, services and solutions. This overlays another customer generated dimension of intelligence that can advise and guide decisions.
Unlike purchase data, customer service data is similar to social media, online reviews and customer feedback data. This is because customer service insight is more subjective and open to individual personal opinions and prejudices (rather than purely objective and quantitative in nature). However, it can be quantified, measured and analysed for trends. Reviewing customer service data often requires a higher level of interpretation and analysis given the unstructured and subjective nature of the information. However, the value of this information is widely embraced.
As Neil Jessop, Chief Executive Officer of OnePoint Global explains,
“Tapping into customer service delivers a wealth of insight. And while too many businesses have trimmed their Customer Service operations, relying heavily on cumbersome, impersonal automation, those that have invested in the personal dimension often see enhanced customer loyalty, but also an increased visibility to the customer. Individuals who are provided quality support are often more willing to provide feedback on surveys, write online reviews and even make recommendations.”
Having a solid, consistent understanding of customers attitudes, behaviours, engagements and issues is important to identify and fortify strengths across specific products, services, channels and promotions, but, perhaps more importantly, pinpointing and addressing the points of weakness.
Whilst there’s significant value in qualitative insight from sources like social media and online reviews, much can be said when reactions are provided directly from the customer. The challenge is that customer service information is often focused on negative experiences. However, within this lies valuable insight about how to improve experiences, enhance quality and innovate features to deliver exceptional quality.
Intelligence Investment
Customer service data differs significantly from purchase data, in that it’s more complex than tracking purchases. Like qualitative social media content, solicited customer feedback or observational customer techniques, customer service data requires significant investments in the technology infrastructure to manage, capture and respond to it. It also generally requires both technology and employees to translate issues into actionable responses and also both streamline and personalise the experience for the customer.
The good news is that although customer service can be complex in nature, it’s also a standardised mainstream part of most businesses, so identifying appropriate solutions isn’t that difficult or risky. However, you still have many businesses who view it as a cost centre rather than an intelligence opportunity.
According to Justine Clements, Consumer Insights Manager for Samsung Australia
“While many businesses view customer service as a necessary hindrance to operating a business, the smart, customer-centric companies often see the information collected in the process of delivering customer service as core to building better customer-led strategies and inspiring new innovation. Customer service including retail offers us a genuine frontline view into the experience of the customer in terms of their expectations, preferences and needs, as well as the ability of our brand’s products and services to match, miss or exceed those expectations. To ignore it is really to ignore your customers, which is fatal to a brand / company hoping to grow.”
Commanding Control
The direct nature of customer service data can serve as a direct quality control measure for a brand. This is why it can be vital to monitor the trend lines of issues to understand the businesses health.
Beyond this, customer service information can identify issues related to sales channels, promotional campaigns, marketing messaging, product performance and newly introduced features. In other words, like purchase data, customer service feedback can provide both tactical (short term) and strategic (long term) views into how products, services, solutions and the brand as a whole are performing.
The challenge is sorting through the complex, unstructured nature of this data and the fact that it typically sits within IVR, email and automated response systems that often lack integration to effectively translate and understand the cross-channel feedback.
Challenging Complexity
Given all customer service data’s benefits to a business, it’s important for a brand to review and track it on an ongoing level in order to measure the state of the business and performance of its solutions. Unlike purchase data, customer service intelligence can have an inherent bias from the source, which can be challenging as well to identify and filter out. However, despite this, it can still effectively assess the performance of advertising promotions, marketing campaigns, sales channels and product innovations.
It’s the nature of customer service information that tends to frustrate the C-Suite of most companies.
As Mark Langsfeld, Chief Executive Officer of mTab, explains,
“The biggest challenge in embracing customer service information is largely with the negative experiences that drive it. Customers do not tend to contact companies when they are having exceptional experiences with products or services, rather these individuals tend to just keep buying them. Customers more often than not contact Customer Service when something goes wrong. This makes focusing on this information difficult for many companies because it reflects the weaknesses of a brand. However, those that target this intelligence can make rapid improvements in the level of quality they deliver to customers.”
Many leading companies place customer service intelligence at the forefront to help set their strategies and develop their innovations. However, there are other brands that discount its value given the subjective, opinionated nature of the data, due to its potential bias and complexity.
Anticipating Impacts
It’s important to note that spikes in customer service can relate to elements like promotions, offers and product launches. This can result in an array of factors which impact the volume and direction of customer service feedback that includes. But this isn’t limited to lacking inventory, decreased quality or access issues. It’s important to anticipate and note how these types of events and factors will impact the customer service operation and resulting feedback.
Ironically, customer service hold times or inadequate responses themselves can drive customer service issues and negative feedback for the brand. This is an entirely different level of challenge that many businesses are coping with given the shifts to online and contactless interactions with brands.
Getting Started
The first step in understanding customer service data streams is to establish the channels the business wants to use to receive customer feedback whether phone, email, online or app. Identifying the systems that customers will use to engage the business and also collect and manage the data is an important step, as is the team that will oversee and staff these platforms.
Like with other datasets, customer service data should have an identified centralised owner of the information. This generally tends to be Operations given the nature of most of the feedback and the actionability around it. The ownership group should establish a process and frequency of reviewing the data reports to analyse and understand trends in terms of timing, frequency, volume and seasonality of purchases.
As the data is reviewed, there should be a focus on identifying feedback trends to find and isolate issues. From here, there should be point owners across every team, including Marketing, Sales, Product and Technology, given the array of feedback that can be expected which can impact any of these, or other teams.
When a trend or spike emerges pointing to an issue (positive or negative), these individuals should work congruently to quickly determine the scope of the issue, the impact on the company and the response in terms of operation and communication. There should also be an understanding of the potential root cause. This makes communicating changes to sales initiatives, marketing campaigns, promotional messaging, special offers, new distribution channels and added product features vital to understand what may be ‘moving the needle’ in order to address or replicate it.
With each data source, the key is to strategically set a plan to identify, collect, analyse and democratise the intelligence in the most effective manner possible. There also has to be ownership of decisions in terms of assessment, response and reaction. From there, it’s a matter of creating a habit of returning to the data to identify and understand shifts and evolutions to design strategies, develop tactics, deliver experiences and drive innovation.
Customer service data is just one of these ‘Magnificent Seven’ datasets that can empower your brand, and although it is among the most complex, it also can deliver tremendous value. Stay tuned in this series as we continue the review of these dimensions of data to help guide understanding of the holistic health of a brand.
