Predictive promoter – take a step beyond Net Promoter Score℠

Predictive Promoter is a bundle of software, tailored services and bespoke training delivery based around IBM SPSS Modeler and designed to help organisations improve their Net Promoter Score by better understanding which customers are loyal and what factors are driving that loyalty.

What is your Net Promoter Score?

Net Promoter Score is a popular metric used by thousands of businesses to understand how likely their customers are to recommend them to other people. The NPS® is calculated by asking customers how likely they are, on a scale of 1-10, to recommend you to others. Respondents can then be divided into three groups – loyal enthusiasts (promoters), unhappy customers (detractors) and people who don’t feel strongly either way (passives). The net promoter score is calculated by subtracting the percentage of detractors from the percentage of promoters. A score of -100 would indicate that all customers are detractors, whereas +100 would indicate all are promoters. Anything over zero indicates that more people are promoting than are detracting.

How does Predictive Promoter improve upon Net Promoter Score?

Your Net Promoter Score gives you some insight into how loyal your customers are but it has two crucial weaknesses. Firstly, it only tells you how loyal the people that you surveyed are – you don’t know anything about the loyalty of those that weren’t surveyed. Secondly, it doesn’t tell you anything about what actions you need to take in order to improve customer loyalty. Our Predictive Promoter bundle enables you to address both of these weaknesses.

  • With Predictive Promoter you can calculate Net Promoter Scores for all your customers, not only the ones that you surveyed
  • Predictive Promoter helps you identify the factors that are driving your Net Promoter Score so you can take action in order to improve it

What is Predictive Promoter and what can it do?

Predictive Promoter is a bundle of software, services and training – all tailored to the requirements of your particular organisation. Thus, each Predictive Promoter installation is unique, put together in order to enhance net promoter scores and customer loyalty initiatives specifically for your particular organisation.

Using Predictive Promoter will allow your organisation to:

  • Understand how patterns in your operational and transactional data correlate with and explain variations in NPS scores and satisfaction ratings – this will help you identify the specific factors which are driving customer loyalty in your organisation.
  • Generate a hierarchy of the 10 most critical factors associated with customers’ likelihood to recommend your organisation to a friend or relative so you can effectively prioritise the actions you need to take to improve customer loyalty.
  • Build a predictive model that will allow you to predict the NPS status all customers (current and past) not just those surveyed, so that you have complete oversight of your whole customer base without the expense of having to survey everyone.
  • Analyse ‘what if’ scenarios to understand the likely impact of changes in policies or processes on customers’ propensity to recommend you in order to best understand what actions you need to take and when.
  • Exploit hidden patterns in unstructured (text) such as free text fields in surveys or social media data in order to enhance model accuracy, and uncover the subtle but critical details that make the difference between detractors and promoters.
  • Identify ‘Persuadables’ i.e. those customers whose profile indicates they could be converted from ‘Passive’ to ‘Promoters’
  • Develop the basis of a real time ‘Red Alert’ system that will identify high value customers at risk of becoming ‘Detractors’ due to changes in circumstances or experiences and allowing organisations time to intervene and take remedial action

Who should use Predictive Promoter?

Each installation of Predictive Promoter is tailored to a specific organisation and is designed to help address the particular challenges that it faces, so there is no typical installation. This means Predictive Promoter has relevance to many different kinds of organisations. We’re confident that Predictive Promoter will be able to help you if your organisation is in one of the following groups:

  • You are heavily reliant on customer recommendations and referrals as important generators of new business.
  • Your products or services are regularly reviewed or discussed online.
  • You’re already using loyalty metrics, customer satisfaction or feedback to drive better customer relationships and want to take this to the next stage.
  • You’re already using NPS but would like to be able to estimate ‘likelihood to recommend’ across your entire customer base.
  • You’d like to be able to make evidence-based decisions about what actions to take to improve customer loyalty in your organisation.
  • You’re interested in assessing the likely impact of policy changes on your corporate NPS score before you take action.
  • You’re ready to move beyond simple BI tools and dashboards and learn from our IBM Certified experts how to develop a more sophisticated approach to NPS
  • You have large amounts of untapped, unstructured data (customer feedback letters, social media data etc) and would like to use it to gain a deeper understanding of satisfaction and loyalty in your organsiation

Net Promoter, NPS, and the NPS-related emoticons are registered service marks, and Net Promoter Score and Net Promoter System are service marks, of Bain & Company, Inc., Satmetrix Systems, Inc. and Fred Reichheld

Find out more by watching our Predictive Promoter video series

In this four part series Jarlath Quinn shows how predictive analytics can be used to drive stronger results in Net Promoter Score programs. Using Smart Vision’s Predictive Promoter solution, Jarlath shows how you can uncover the key factors that 1) drive positive and negative recommendations; 2) build a predictive model to identify ‘persuadable’ customers that could be converted to ‘promoters’; 3) apply the same model to estimate the ratings of the entire customer base and 4) mine the open text responses of customers to uncover the subtle but critical factors in customer evaluations that drive NPS.

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