{"id":1895,"date":"2021-09-21T08:02:47","date_gmt":"2021-09-21T08:02:47","guid":{"rendered":"https:\/\/ec2-34-253-215-75.eu-west-1.compute.amazonaws.com\/?p=1895"},"modified":"2022-03-04T12:28:39","modified_gmt":"2022-03-04T12:28:39","slug":"nps-customer-service","status":"publish","type":"post","link":"https:\/\/refiner.io\/blog\/nps-customer-service\/","title":{"rendered":"How to Use NPS in Customer Service"},"content":{"rendered":"\n

Wondering how to use NPS in customer service?<\/p>\n\n\n\n

Customer experience is so critical to SaaS success, isn\u2019t it? 96% of customers<\/a> consider customer service vital to their loyalty to a brand, after all. And loyal customers are 5x more likely to purchase again and 4x more likely to refer a friend to the company.<\/p>\n\n\n\n

So, if you want to thrive in the SaaS business, you have to provide insanely great customer support.<\/p>\n\n\n\n

It\u2019s just, sometimes, you really can\u2019t tell whether you\u2019re making the grade, right?<\/p>\n\n\n\n

Yes, you try to offer a great experience to customers. But are they happy about it? And if not, what, in particular, they aren\u2019t satisfied with.<\/p>\n\n\n\n

Well, in this guide, I\u2019ll show you how to use NPS surveys to get that information. You\u2019ll learn how to use NPS for customer service, and how to use survey data to improve the customer experience even further.<\/p>\n\n\n\n

Intrigued? Let\u2019s get right to it, then.<\/p>\n\n\n\n

What is NPS, A Quick Recap<\/h2>\n\n\n\n

NPS (Net Promoter Score) survey<\/a> is a customer survey used to measure customer\u2019s loyalty towards a brand.<\/p>\n\n\n\n

Frederick F. Reichheld of Bain & Company (the organization that holds the registered trademark to \u2018NPS\u2019) developed the concept and introduced it to the world as The One Number You Need to Grow<\/em><\/a> in 2003.<\/p>\n\n\n\n

And the beauty of NPS is that it\u2019s incredibly simple. Here\u2019s how it works. <\/p>\n\n\n\n

In NPS, you send a question asking about the customer\u2019s likelihood of recommending your product or service to a friend, colleague, or family. The customers then select a number on a 0-10 scale with \u20180\u2019 being \u201cNot likely at all\u201d and \u201810\u2019 being \u201cExtremely likely.\u201d <\/p>\n\n\n\n

For example, this is the most common NPS question:<\/p>\n\n\n\n

\"NPS<\/figure><\/div>\n\n\n\n

[Note: This is a general example. You can use NPS at multiple touchpoints, as you\u2019ll see further in the example of NPS for customer support]<\/em><\/p>\n\n\n\n

Once customers start filling the survey, your NPS system\/software<\/a> will show the NPS or Net Promoter Score in real-time.<\/p>\n\n\n\n

How to calculate NPS?<\/h3>\n\n\n\n

To measure NPS manually, you need to know these three terms first:<\/p>\n\n\n\n

  1. Promoters:<\/strong> This group of people give 9 or 10 on the NPS scale and are highly loyal to your brand. They also happily recommend you to potential customers.<\/li>
  2. Passives:<\/strong> Passives give a 7 or 8 score. Roughly translated, it means they\u2019re happy with your brand but not quite love it to recommend to anyone and everyone.<\/li>
  3. Detractors:<\/strong> These are unhappy customers & give a score between 0-6. They will leave your product or service as soon as they find a better alternative. Moreover, detractors are likely to share negative word of mouth on social media.<\/li><\/ol>\n\n\n\n

    Then, use the findings from your survey results in this formula:<\/p>\n\n\n\n

    NPS <\/strong>= [(Number of promoters \u2013 Number of detractors) \/ (Total number of respondents)] x 100<\/p>\n\n\n\n

    For example, if 120 people fill the survey and Promoters = 40<\/strong>, Passives = 70<\/strong>, and Detractors = 10<\/strong>, then:<\/p>\n\n\n\n

    NPS<\/strong> = [(40-10)\/120] x 100 = 25<\/p>\n\n\n\n

    The Net Promoter Score can fall between -100 and 100, and your next steps of action and priority of action depend on the score you get.<\/p>\n\n\n\n

    The NPS Question To Measure Customer Support Success<\/h2>\n\n\n\n

    The first step to using NPS for customer service is to collect helpful information with a relevant NPS question<\/a>. Ask this immediately after a customer service interaction:<\/p>\n\n\n\n

    \u201cBased on your recent Interaction with [Support Staff Member], how likely are you to recommend [Company Name] to a friend or colleague?\u201d<\/strong><\/p>\n\n\n\n

    \"NPS<\/figure><\/div>\n\n\n\n

    This question keeps customer support at the center to measure customer loyalty. Let\u2019s take an example of how asking it can impact the big picture: <\/p>\n\n\n\n

    Say a customer gives \u20185\u2019 here but has given \u20188\u2019 on the overall likeliness to recommend scale. Then, improving support will likely push the respondent from passive to promoter overall and from detractor to passive or promoter for the same question next time.<\/p>\n\n\n\n

    To improve your support efforts, however, you\u2019ll need to know why they gave the score in the first place. For that, ask an open-ended follow-up question like:<\/p>\n\n\n\n

    \u201cHow could we improve your experience?\u201d<\/strong><\/p>\n\n\n\n

    \"Customer<\/figure><\/div>\n\n\n\n

    Once you have the answers, go step-by-step to improve customer service.<\/p>\n\n\n\n

    How To Use NPS in Customer Service<\/h2>\n\n\n\n

    Step 1: Look at the overall score<\/h3>\n\n\n\n

    As I mentioned, the overall NPS score can be between -100 and 100, and your steps and priority of action(s) depend on it.<\/p>\n\n\n\n

    Refer to this table to determine warning levels:<\/p>\n\n\n\n

    Overall Score<\/strong><\/td>Meaning<\/strong><\/td>Warning level<\/strong><\/td><\/tr>
    -100 – 0<\/td>Horrible<\/td>Very High<\/td><\/tr>
    0 – 20<\/td>Favorable<\/td>High<\/td><\/tr>
    20 – 30<\/td>Good<\/td>Moderate<\/td><\/tr>
    30 – 50<\/td>Great<\/td>Low<\/td><\/tr>
    50 – 80<\/td>Excellent<\/td>Low<\/td><\/tr>
    80 – 100 <\/td>World-class<\/td>None<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

    If the warning level is high, solving customer support issues should be at the top of your priority list. Not focusing on it means your brand image and retention rate will take a hit.<\/p>\n\n\n\n

    Conversely, your team can go about doing their daily tasks if the warning level is low. But, of course, it doesn\u2019t mean you shouldn\u2019t improve your customer service.<\/p>\n\n\n\n

    Note:<\/strong> The above table is a general categorization of NPS. Look for your industry\u2019s benchmarks to know where you stand in comparison to competitors. For example, in the SaaS industry, the average NPS<\/a> is 30, whereas, in the insurance industry, the average NPS is 70. <\/p>\n\n\n\n

    Step 2: Separate Detractors from Promoters<\/h3>\n\n\n\n

    This is the first step for your action plan: Separate detractors from promoters. Your aim should be to improve detractors\u2019 customer experience. In most cases, it will also improve the experience for passives (i.e., passives will turn into promoters if the detractor needle moves to a higher score).<\/p>\n\n\n\n

    As for promoters, when they confirm they are a fan, ask them to promote you. <\/p>\n\n\n\n

    For example, instead of asking \u201cHow can we improve your experience?\u201d, ask them to refer to potential customers with something like, \u201cWe’re glad you like our customer service. Would you like to refer us to your friends?\u201d Similarly, you can ask promoters to sign up to your affiliate program, leave a review (on G2 or Capterra or GetApp or anywhere your SaaS is present), or do anything that boosts your brand.<\/p>\n\n\n\n

    Step 3: Look for patterns<\/h3>\n\n\n\n

    Okay, now the aim (improving customer service) and dataset (detractors) are clear. It\u2019s time to pinpoint the exact issues by finding patterns across unhappy customers\u2019 results.<\/p>\n\n\n\n

    There are two ways to discover patterns from NPS results:<\/p>\n\n\n\n

    1. From customers:<\/strong> Sometimes, only a specific group of customers are unhappy. For example, if your customer support team is based in the US and operates during EST hours, your customers from other regions of the world might not like the late replies to questions they send during their working hours. You can see if that\u2019s the case by segmenting the results based on users\u2019 demography, psychography, geographical location, etc.<\/li>
    2. From customer results:<\/strong> In most cases, the fault will be in the interaction. To catch precisely where the customer service team lacks,