What do customers really want? That's the question at the heart of every company's digital transformation.
Practically speaking, this means more departments and employees need to be better attuned to what customers are saying – in all the ways they can say it: vocally, socially, physically, and through behaviors at every point of interaction. Happily, data and technology provide more and more options for forging that understanding. Here are five to consider.
1. Voice Analytics
Capturing and analyzing vocal patterns from customer interactions can yield a wealth of data. Most companies that already use voice analytics do so only within the confines of the customer service department or call center. This approach effectively restricts employee-to-customer communications to one sliver of your company’s workforce.
Instead, consider using voice analytics at every customer-employee touchpoint. Some examples include product engineering, parts, and billing departments. These groups may use the data to better understand points of frustration or enthusiasm that help anticipate product failures, reduce customer churn, identify new service opportunities, and more.
But look outside your organization too. Voice and other analytics can be used to analyze interactions with business partners and supply chain vendors.
“Want something that’ll really blow your mind? What if we put that data in front of our customer’s customers? Go one, two, three steps further down the value chain,” said David Nour, CEO of the consultancy The Nour Group and author of books including Relationship Economics and Return on Impact.
Nour said distributors sell to a wholesaler or a retailer, and that’s where most organizations stop their analysis. “What if we asked ‘how is that retailer doing with their end customers’ and ‘how is that customer actually getting value from the product, the service, and the experience’?
“By doing so, a manufacturer can get dramatically better at their respective customer-centricity challenges and opportunities and in the process, the entire value chain will enhance its agility and responsiveness.”
(For more on the emerging role of voice communication, read Machines, Talking Their Way into the Workplace.)
2. Content Consumption DataMost companies have at least a rudimentary content strategy in place, as the trend of shift from direct advertisement to more conversational or informational kinds of content shows no sign of abating. Web analytics packages such as Google Analytics, Omniture, Chartbeat, and others provide granular insights into what content people view and how they interact with it. This information can in turn help optimize conversions on ecommerce sales or provide a human salesperson in a brick-and-mortar with a strong idea of a customer’s interests. Strong interest in 'how to' content regarding an app could guide developers in making a user interface more intuitive or to add a feature.
Some companies blend in data from customer support chats to provide additional insights on how and why content is being searched for and/or consumed. Analysis can also guide the type of content and topics you should include on your website.
“A simple word cloud analysis can show themes and problems that your customers are having. Content teams can then write how-to articles and tutorials on how to solve these issues and put it on the website. Second, this data will be extremely helpful in support training, as new call center staff or support members can quickly understand the trends in customer feedback and support needs,” said Jacob Dayan, CEO and Co-founder of Community Tax, a finance and accounting company based in Chicago.
Further, chat data and content consumption data can provide guidance for your training, sales and call center, and other department staffs.
“Once a week, we have all of our engineers run the customer support chat to make sure our organization is always customer-centric. They document any common denominators they see and share as a group after the exercise,” said Gene Caballero, co-founder of GreenPal, which he described as “Uber for lawn care.”
“This lets them stay close to the customer so there is no question when we need to implement an iteration on our site and keeps everyone on the same page.”
3. Enhanced Social Media Sentiment Analysis
Social sentiment tools aren’t new, but companies are finding new ways to use them in combination with other tools to provide employees a better view of the customer.
“I often advise clients to combine both lagging indicators — such as traditional analytical reports such as sales, wallet share of total spend, market share gain — with leading drivers such as sentiment along the customer experience journey for specific predictive indicators,” said Nour.
Typically, companies look to sentiment analysis to understand how customers feel about a specific issue or product. But you can also look for patterns among related issues, persons, brands, and events for a more nuanced view of customer emotions and behavior.
Applying machine learning takes social media sentiment analysis to the next level. One of the benefits of social media is the massive amount of data available to effectively train machine-learning systems.
oMelhorTrato.com, a loans and insurance comparison shopping website that claims 21 million users in Mexico, Central and South America, uses Google’s TensorFlow platform to examine customer queries.
“Based on all the conversations that we have graded during the last nine years in South America, we were able to automate 56.9% of queries. In this way the user receives their response in seconds and our team only has to answer those questions that were never consulted before,” said Cristian Rennella, CIO and co-founder of the company.
4. Change Data Analysis
Since big data opened the floodgates of possibilities, companies have focused on gathering as much data from as many sources as possible. In many ways, the effort has paid off. But it has also burying companies in a mountain of data that just keeps growing and choking networks.
But if there’s one thing IoT has taught us about efficiently handling a tsunami of data, it’s the concept of “change data.” It other words, you ignore data that keeps repeating itself and note and analyze only the data that is different from the norm, denoting a change in the status quo.
Humans are creatures of habit. It is typical for customers to buy the same brands and product types over and over again – until they don’t. Ceasing to continue to buy same product, size, brand, or other routine expenditure indicates a change in a customer’s life that can indicate new opportunities and challenges.
For example, if a customer stops buying a man’s shirt in large that could indicate that a child has grown up and moved away, or that the customer has lost or gained weight. Nothing the change in the purchasing trend tips you off to looking for a cause that can in turn guide you on how to continue the relationship with the customer.
Similarly, changes in use of an IoT device can indicate a change in lifestyle, a new need, a now obsolete device (in terms of that consumer’s use patterns), discontent with the product’s performance, or other signals your employees can respond to proactively in either or both the short-term and the long-term, depending on the circumstance. For example, a proactive, short-term fix may appease the customer and keep them loyal to the brand, but a near-simultaneous change in design planning can improve product sales in the mid- and long-term as well.
Blockchain is making a splash in the finance sector as a straightforward distributed ledger of transactions, but it is also gradually finding applications elsewhere. One area it can help with is building trust by exposing data to your customers. Starbucks, for example, just announced a pilot program using blockchain technology to verify the source of coffee beans.
“To truly become ‘customer centric’ and transparent to customers, companies should embrace blockchain across all marketing efforts with customers,” said Robb Hecht, Adjunct Professor of Marketing at Baruch College in New York City.
“For example, show customers the source locations of their building materials, show customers the amount the company gives to charity, show customers product defect rates, show customers retention, show customers rates of on-time delivery. But that data must be shared in transparent fashions with potential and existing customers through effective campaigning that engages them, making them continually loyal to the brand.”
By finding relevant blockchain applications, customers can relate to your company and brand in the ways most meaningful to them, whether that’s environmental impact, fair trade, employee treatment, or verified quality of products. This enables your employees to connect with customers based on their interests and individual buying motivations too.