Introduction to Net Promoter Score (NPS)

Sachin Rekhi, a former Director of Product at LinkedIn, shares his practical insights on measuring and implementing Net Promoter Score (NPS) as a key performance indicator (KPI) for customer loyalty. This article provides a practitioner's guide to effectively utilizing NPS within an organization to drive more delightful product experiences.

The Origin of NPS

NPS, a metric devised by Fred Reichheld at Bain & Company in 2003, measures customer loyalty. Reichheld's seminal HBR article, "The One Number You Need to Grow," highlights NPS as a simple yet powerful alternative to lengthy customer satisfaction surveys. It demonstrates a strong correlation between NPS and long-term company growth.

NPS is based on a single, simple question: "How likely is it that you would recommend our company to a friend or colleague?"

Responses are categorized into promoters (9-10 score), passives (7-8 score), and detractors (0-6 score).

The NPS score is calculated by subtracting the percentage of detractors from the percentage of promoters.

How LinkedIn Implemented NPS

At LinkedIn, Rekhi emphasizes the importance of integrating NPS into the company's standard KPI framework. He highlights its significance in understanding customer loyalty and its role in enhancing the product experience.

LinkedIn utilizes NPS alongside traditional acquisition, engagement, and monetization KPIs to gain a holistic view of customer satisfaction and loyalty.

NPS serves as an actionable metric for product improvements and enhances overall customer delight.

Best Practices for Implementing NPS

Rekhi outlines several best practices for effectively implementing an NPS program within an organization:

**Additional NPS Questions:** In addition to the primary NPS question, ask an open-ended question about why customers gave a specific rating. This provides valuable qualitative data for understanding customer feedback and making informed decisions.

**Collection Methods:** Utilize both email and in-product prompts to capture responses from a wide range of customers. Consider employing NPS survey solutions like those offered by SurveyMonkey.

**Sample Selection:** Ensure that the NPS survey sample accurately reflects the engagement levels, customer tenure, and other key characteristics of the overall user base. This prevents biased results and ensures representativeness.

**Survey Frequency:** Determine the appropriate survey frequency based on the size of the customer base and the product development cycle. At LinkedIn, quarterly surveys aligned with their product planning cycle proved effective.

**Analysis Team:** Include key stakeholders from product development, marketing, research, and operations in the NPS analysis team to ensure that findings are effectively leveraged for product improvements.

**Verbatim Analysis:** Categorize open-ended comments from promoters and detractors to identify recurring themes and address pain points effectively.

**Promoter Drivers:** Analyze promoter feedback to understand the specific product actions that lead to positive experiences and customer loyalty.

**Methodology Consistency:** Maintain a consistent methodology for asking questions, competitor lists, and sampling to ensure comparable results across surveys.

**Seasonality:** Be aware of potential seasonality in NPS results and consider year-over-year comparisons to mitigate its impact.

Limitations of NPS

While NPS is a valuable tool, Rekhi acknowledges its limitations:

**Infrequency of Results:** NPS is a lagging indicator and is not suitable for real-time operational decision-making.

**Margin of Error:** Sample size affects the margin of error, so smaller samples can lead to less reliable results.

**Not a Replacement for Product Strategy:** NPS is a tool for understanding customer perception and informing product optimization, not a substitute for overall product strategy.

Conclusion: The Power of NPS for LinkedIn