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In the age of predictive analytics, businesses are always looking for the next crystal ball to solve the riddle of customer behaviour. Algorithms are supposed to tell you who’s most likely to buy again. Machine learning processes are expected to infer customer satisfaction levels from huge data sets. Artificial Intelligence is taking over and we just can’t get enough of it. Providing we’re still in charge, of course (hold your horses, Skynet!).
This seems great and indeed very promising, but it should not distract us from the basics. And in the field of customer experience, what should be considered the basics? What is the best way of knowing how happy someone is with your service?
It turns out the most effective system ever invented to find out what people think is… (insert drum roll sound) to ask them what they think. Amazing, right?
Now, you need to figure out what to ask people. What type of question would result in answers that are both easy to analyze and rich in insight?
NPS (Net Promoter Score) was created to help you with that task.
What is Net Promoter Score?
Net Promoter Score is a common metric used to measure the customer’s loyalty to company.
It was first mentioned in 2003 by the business strategist Fred Reichheld in his Harvard Business Review article The One Number You Need to Grow, where he explains the need for a more straightforward approach to customer surveying:
“Most customer satisfaction surveys aren’t very useful. They tend to be long and complicated, yielding low response rates and ambiguous implications that are difficult for operating managers to act on. Furthermore, they are rarely challenged or audited because most senior executives, board members, and investors don’t take them very seriously.”
That is why NPS is based on a simple question that businesses ask their customers:
“In a scale from 1 to 10, how likely is it you would recommend us to a friend?”
The underlying argument is that recommending something to a friend is the ultimate practical demonstration of loyalty. Based on the answer, you can calculate the share of customers who are:
Promoters (9 to 10) – These are your brand’s most enthusiastic fans. They will spread the word about how great you are. They are the ones you absolutely need to keep engaging with.
Passives (7 to 8) – They are happy, but not too excited. Some studies suggest that passives will repurchase and refer your business 50% less than promoters. They are not necessarily loyal, so you need to make sure they have the right incentives.
Detractors (0 to 6) – These are people whose experience did not correspond to their expectations and therefore they are very likely to buy from a competitor and spread negative views of your brand.
The Net Promoter Score itself is then calculated by subtracting the share of detractors from the share of promoters. For example, if 3 out of 10 (30%) were promoters and 5 out of 10 (50%) were detractors, your NPS score is -20.
Those who developed NPS argue that there is a strong positive correlation between NPS and growth. Or at least, as Reichheld states, growth cannot be achieved without a positive outlook on customer satisfaction.
Make no mistake: the existence of this correlation is widely disputed. According to the MIT Sloan Management Review, “correlation between companies’ customer satisfaction levels for a given year and the corresponding stock performance of these companies for that same year, on average, satisfaction explains only 1% of the variation in a company’s market return”.
What we do know for certain is that the simplicity of NPS allows companies to gauge customer loyalty more frequently.
Also, the response rate will probably be higher than if you use long customer surveys.
Which one would you be more likely to respond?
What’s next? NPS and Personalisation
Being able to measure loyalty is just the first step. Whilst it’s great to know how loyal people are, it is quite pointless to worry about it if you do not plan to do something to improve those levels of commitment.
The simplicity of NPS makes its analysis scalable. The initiatives to improve customer loyalty that follow it should also abide by this principle. This requires some degree of automated personalization.
Once you have classified customers as detractors, passives or promoters, you can introduce elements of differentiation in your website experience, for instance.
Here are two simple examples:
If you know someone is a detractor, it might make sense to provide a higher degree of customer support throughout the customer journey. Offering detractors the chance to request a free callback or chat with a dedicated agent can be a good way to improve the way they see you. But here’s a very important detail: make sure the connection with the support team works smoothly, otherwise you might make matters even worse. You most definitely should not put these on hold for a long time. Also, people at the other end of the line should know what type of customer they will be talking to beforehand.
If you know someone is a promoter, social sharing buttons are the way to go. Whenever a promoter purchases something, reads something on your blog or downloads a whitepaper, make sure that person is able to share the event with friends. You can also target referral programs such as Member Get Member (MGM) specifically at promoters.
NPS is just another piece of actionable data
NPS adds a little more information to the huge pile of customer data that is growing every single day.
Just as any other metric, its aim is to provide the basis for informed action. It’s not an end in itself. For this reason, your NPS information should be easily actionable. Ideally, you should be able to act over a customer’s stance on loyalty immediately (i.e. right after their answer) and automatically (i.e. certain scores triggering certain content).
Make this a key concern when planning NPS initiatives – and avoid being stranded with a negative score and very limited options to improve it.