The Importance of Supplementing NPS Scores

with Insights Drawn from Real

Comments and ReviewsWhitepaper

INTRODUCTION/EXECUTIVE SUMMARY

The Net Promoter Score (NPS) system has transformed the way businesses approach customer satisfaction surveys and customer experience management (CEM). Because the NPS is a short survey providing only a snapshot of the customer experience, it offers a quick metric of customer brand loyalty. Its brevity and focus on a quantitative summary is proven to both increase survey response rates and decrease the time lag in communication between the customer’s rating and the front-line employees. However, the simplicity of NPS is also its greatest drawback. In this whitepaper, we will explore the primary benefits and shortcomings of the Net Promoter Score system, and discuss how text analytics is the perfect tool to fill that gap.

It is well understood that the NPS is a measure of the customer’s brand loyalty and a robust predictor of business growth. Using a Likert Scale single question survey based on a scale of zero to 10, businesses have immediate access to the likelihood a customer would recommend the brand to others. By focusing on one core question, “How likely are you to recommend [Company X] to a friend or colleague,” NPS dramatically increases survey response rates and improves the delay between survey completion and front line action.

NPS BRIEF

NPS BENEFITS

NPS is a highly versatile number and adaptable to a variety of business models. It can be tracked from week to week and month to month. Additionally, it can be further analyzed by product line, individual stores, customer service rep, or another particular metric. Because the NPS has an established, common terminology (i.e. Promoters, Detractors, and Passives) it can be shared quickly with franchisees and employees to create fast reactions regarding shifts in policies, processes or products.

Furthermore, the NPS can give a comparative snapshot of where your business stands in contrast to others in your industry. Should your business have an NPS 0f 70, but your competitors hold a score with 80 or above, this will signal a need for an adjustment that cannot be located in the numerical score alone.

The Net Promoter Score simplicity and speed along with its strong association with an increase in organic growth make it the go-to metric for several industry leaders. For example, the NPS system has been successfully adopted by: major airlines such as Delta, Southwest, Qantas; industrial powerhouses like Alcoa, General Motors, and Stanley Black & Decker; titans of retail, including Apple, Macy’s, and Porsche; financial services giants like Citigroup, Charles Schwab, and JPMorgan Chase & Co4. These are just a handful of the thousands of companies around the world using and benefiting from the Net Promoter Score system.

WHAT NPS MISSES

While the NPS system creates enormous value for practitioners, it is an oversimplification of the customer experience. Indeed, a high score isn’t an assurance of industry success. Predicating business growth on an average of one score relating to the customer experience overlooks an essential component of Customer Experience Management: real consumer comments. Because customers often leave comments that don’t match their Net Promoter Score, relying solely on single metric places businesses at a huge positional disadvantage. Your goal for business success is to acquire the right information at the right time, and, the right time isn’t always at the point of sale.

For example, let’s meet Stephanie. She’s a young professional who just wrapped up a four-night stay at a hotel while visiting San Francisco for a conference. When asked if she would recommend the hotel to friends and colleagues, she offered an enthusiastic 9. Ordinarily, this would be great! Another promoter has been successfully created, and the hotel’s NPS goes up. But here’s the open-ended response Stephanie left along with her score:

“I had a great stay at this hotel. The room was spotless, and the bed was super comfy. Especially loved the shampoo and conditioner in the bathroom since I forgot mine at home! I did notice the fruit in the bowl at the front desk looked really old, but no big deal. Would definitely stay here again!”

Despite her overwhelmingly positive experience at the hotel, Stephanie’s comment raises a huge red flag that merits immediate follow-up. But a traditional, score-focused NPS system often overlooks comments like hers entirely. Because of the viral nature of social media, should Stephanie decide to post a similar comment on a blog, in a Tweet, or on her Facebook page, this will counter-act the generous “9” score she gave directly on the survey. Her public response carries greater social influence than her private feedback on the NPS survey. This disconnect between a customer’s Net Promoter Score and the comments they leave can be disastrous.

WHAT IS TEXT ANALYTICS?

Broadly speaking, text analytics (roughly synonymous with text mining) refers to the process of pulling information and insights from masses of unstructured text. This means analyzing Twitter posts, scientific papers, hotel reviews, and other text sources to determine the content and tone (sentiment) of those documents. This information, in turn, is used to predict consumer behavior and strategically position your business for increased growth, and market leadership. Before the advent of mass-market text mining software, document review was completed piece by piece and by hand. This was a timely and expensive process that required an enormous labor investment with minimal returns. However, since the early 2000’s, companies like Lexalytics have revolutionized the fields of customer experience management (CEM), voice of customer (VoC), public relations, hospitality, financial services, and more.

This shift was made possible by the rapid advancement of machine learning algorithms and natural language processing (NLP) technologies, such as the current set Lexalytics develops and employs. Furthermore, different organizations analyze various types of content. As such, we offer text mining tools that are flexible and customizable to fit every user’s needs. We’ve provided additional, more detailed, information through our white papers and technology pages.

Modern text mining tools give companies the ability to analyze millions of text documents in mere minutes. The goal is to determine exactly who is speaking, what they are talking about, how they feel about those subjects (or sentiments), and what they intend to do. Those four questions are roughly defined by the core features of text analytics.

Together, these functions provide the kind of detailed insights that were previously a large expense. Textual content is a goldmine for all industries, and companies such as Lexalytics are here to help you extract the most value from this Big Data minefield.

Named Entity Extraction: It identifies named figures within a body of text (people, places, companies, products, and so on). Lexalytics offers full customization of entity extraction with both Salience and Semantria so users can define whatever an entity means for them. If it’s an entity to you, it’s an entity to us.

Categorization: Helps you sort large volumes of text, without substantial labor costs. Processes 10,000 consumer tweets to discover exactly what is being discussed (politics, gaming, religion, food, etc.). Sorts through hundreds of academic papers to find the ones relevant to you. Sifts through thousands of TripAdvisor reviews to see what areas your hotel needs to improve on. The possibilities are endless.

Sentiment analysis: Determines the tone of those conversations (positive, negative, or neutral). Lexalytics goes the extra mile by assigning a sentiment score to every entity, category, and topic we produce. This level of detail will show you exactly what consumers think about specific areas of your business.

Intention Extraction: This is our latest innovation, offering insights into what a consumer will do next. Will they buy, quit, sell, or recommend your product? You can think of Intention Extraction like an NPS score drawn from the consumer’s own comments, rather than a single survey question.

THE BEST CEM = NPS + TEXT ANALYTICS

Although the NPS system provides an easy-to-understand metric, it ignores the nuance of longer customer satisfaction surveys. This kind of oversight may seem innocuous but can have a serious, real-world impact on business growth. Returning to our previous example involving Stephanie, the hotel customer from earlier in this white paper. Because she enjoyed most of her stay, she gave a Net Promoter Score of 9. However, she mentioned in her open-ended survey comment that the fruit at the front desk was starting to rot. It would be pertinent to determine if she also said this on crowdsourced review platforms such as Yelp, or Google Reviews. Because of the immediate sentiment impact of such review systems, this is an oversight that the hotel staff can’t afford to miss. Yet, a traditional NPS system will focus on Stephanie’s score, and her promoter status sent to the company is contrary to what she’s revealed to all of social media. Most customers do not care about your NPS. They want to know how your company, brand, or product/service can benefit them straightaway. In the instant gratification oriented consumer world, what others say about your business maintains a larger influence than any private feedback score.

To view this from a wider lens: Net Promoter Score is a great system for providing big-picture, immediately actionable information to Customer Experience Management professionals. But, NPS doesn’t tell you why you’re receiving your scores. The “why” comes from open-ended survey responses, customer comments, social media posts, and online reviews (which is an information source that is notoriously challenging and labor-intensive to utilize). This is where text mining tools come into play. By continuously analyzing open-ended survey responses, you’ll catch what an NPS system fails to adequately detect, and can further investigate by examining online feedback such as social content reviews.

In short, companies need to engage with both NPS data and insights drawn from real responses, analyze them separately, and then compare the results. For the best results, combine NPS and text analytics into a holistic, powerhouse CEM program.

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