Commentary
CRM Meets The (New) Voice Of The Customer
- by D. Daniel Ziv , March 16, 2010
With the proliferation of social media networks and other forms of non-traditional customer touch points, in addition to advances in unstructured mining technologies such as speech and text analytics, there is a surge of structured and unstructured data that can be categorized as representing the new voice of the customer.
Organizations can no longer ignore VOC when developing or evolving their CRM strategies if they hope to truly understand underlying consumer behavior and drivers of brand loyalty.
Categorizing the Voice of the Customer
The term "voice of the customer" has been used in many different contexts to mean different things. These VOC references generally fit into four key categories: Direct Structured, Direct Unstructured, Indirect Structured and Indirect Unstructured.
| Voice of the Customer | Structured Data | Unstructured Data |
|---|---|---|
| Direct (Internal) | Closed Questions: Web, IVR, Email, Mail, POS | Actual Voice and Text Interactions, Focus Groups |
| Indirect (Public) | Online Ratings, 3rd Party Survey | Blogs, Social Media, Public Media, Word of Mouth |
Direct Structured
Direct structured fits within the most traditional definition of VOC -- customer feedback and post interaction surveys. Conducted via the Web, interactive voice response (IVR), email or even at the point of sale, these surveys are frequently used by marketers to collect VOC data. Making this customer information available to the broader enterprise helps companies better understand purchasing decisions, product/service preferences, and more.
However, this VOC data can be limited in detail because of its inability to capture the full depth of what is discussed during customer interactions. That, coupled with limited survey response rates and typical non-random participation (i.e., mostly very positive or very negative responders), the result may provide a clouded picture of customer behaviors. While it is critical to the VOC equation, it is not the only source of insight into customer trends.
Indirect Structured
Indirect structured VOC differs in the sense that information is collected and typically distributed outside the organization. These ratings come from data and marketing research services or via public Web sites with "rate this" or "recommend this" functionality. Because these ratings are widely available, ignoring them can be dangerous since they may impact customer buying decisions, as well as your competitors' strategies.
Direct Unstructured
Direct unstructured VOC includes customer interactions -- in the form of voice, email, chat and open feedback from focus groups. At one time, such data were more difficult to aggregate and quantify than structured data, and thus have not been included in most CRM systems or strategies. This is now changing, however, with innovations in speech and text analytics software.
Direct unstructured data are much richer in nature and captures more detailed nuances, behavior drivers, root causes and insights when compared to most VOC structured data. It also reflects a true random sampling of all customers, eliminating the potential bias of self-selection response samples. When fully integrated into a CRM strategy, it offers greater insight into genuine customer behaviors.
Indirect Unstructured
In today's digital world, indirect unstructured VOC refers primarily to information generated among the social networks, as well as word of mouth. Indirect unstructured data provide a glimpse into everyday public conversations on specific brands, products and services. Emerging social media monitoring tools can track, categorize and even try to associate positive or negative sentiments to this type of VOC data to gain knowledge and understanding on the customer decision-making process. Creating structure and mapping some boundaries around this valuable information based on other forms of VOC can help separate real trends from irrelevant chatter.
Connecting the Dots with CRM and VOC
VOC data are much more accessible with today's tools, creating an opportunity for organizations to move beyond siloed thinking by formulating the right mix of categories.
For a national payment processing company, spending roughly $600,000 for speech analytics software created a $3.4 million return on investment. The organization captured and acted on direct unstructured VOC data by analyzing calls coming into its contact centers. In doing so, the system identified key words/phrases that were typically associated with customer conversations just prior to them terminating an account.
Taking that same VOC database, the payment processor ran automated searches for these indicative words/phrases in recorded interactions with existing customers to determine and flag those with a propensity for defection. After cross-correlating the customers' "value" through its CRM data, it established a process to proactively contact the most high value and "at risk" customers -- saving more than 600 accounts that represented over $4 million in revenue since the project was deployed in mid-2009. These results were achieved because the company leveraged the rich unstructured voice data in tandem with its CRM data to tap into and act on the real voice of its customers.
Now's the perfect time to take a look at your organization and the potential VOC available to you. Such technologies as speech analytics and text analytics that mine unstructured VOC data are a starting point. To fully maximize investments already in place, ask your CRM vendor if it has the ability to integrate both structured and unstructured VOC data to help create a richer and more actionable customer relationship management strategy.
Daniel, this is an excellent summary. My primary interest of in the area of Indirect/Unstructured analysis of VoC, and we specialize in processing Customer Reviews into detailed metrics. In other words we measure products reputation and publish them in a form of syndicated Market Research.
I would love to learn how often do you see enterprise integrating traditional CRM model with Social Media tools to decipher VoC messages?
Thanks Gregory.
There are more and more examples of companies leveraging Indirect/Unstructured analysis into their CRM models and processes. Companies are using text analytics to extract and mine social media content from review forums, communities and other social media sites so that they can attribute, to each content creator, a CRM analytic “profile” that they can then use to track the content creator’s posting habits, and the impact that content creator has on a social media content source’s tone, sentiment, and overall audience engagement. One example is Clarabridge - a text analytics company - that is being used to “listen” to the postings from contributors to a developer forum, and their tool is used to identify valuable contributors, so that the company can reach out to those posters, offer incentives to them to continue to drive their engagement, and develop a more close relationship with those individuals. Effectively they are creating a customer relationship with those posters by using CRM techniques to engage with the customers through social media. Other companies like Comcast use Twitter to listen and engage with “vocal” customers to help resolve their issues and hopefully sway them to become “vocal” supporters.
Daniel,
Outstanding way to approach this topic. Agree that each of these categories represent a distinct type of "voice". When considered in this way, it becomes clear that the traditional listening approaches (generally direct structured) provide only a small glimpse of a much larger picture.
Great article!