Categories
Research Methodologies
March 2, 2017
Very few companies and models actually take into account the customer profile when reporting out NPS Scores.
Net Promoter Scores – We all have heard of it and most of us have drunk the cool-aid. NPS Scores are a measure of customer loyalty, and thereby a reflection of profitability. Most companies measure NPS by asking customers, after a recent purchase, via a simple transactional survey.
However, very few companies and models actually take into account the customer profile when reporting out NPS Scores. In our experience and modeling, most companies are not leveraging the power of NPS to determine service delivery perfection.
Let’s take a small example to illustrate a point;
ID | Customer Type | NPS Score |
1 | SMB | 10 |
2 | Enterprise | 2 |
3 | SMB | 7 |
4 | SMB | 8 |
5 | Enterprise | 6 |
Now, let’s calculate the standard formula for the NPS Score – which is the % of the folks who are promoters – % of customers who are detractors;
In this above example;
Promoters | 40% |
Passive | 40% |
Detractors | 20% |
Finally, we arrive at the cumulative NPS Score:
NPS Score: 20
Note – the NPS Score is always a “Score” that can have valued between -100 and +100.
Now – let’s bring in actual revenue. Let’s propose that the Lifetime Value of an Enterprise Customer is much higher than the value of an SMB Customer. The concept of loyalty and rewarding customers who spend more – is to stratify and design programs for customers in the appropriate spend category.
For conversation’s sake, let’s say the LTV of an Enterprise User vs. an SMB User is as follows;
Customer Type | LTV |
Enterprise | 8000 |
SMB | 2000 |
We will see this in a minute, but the _absolute_ numbers (8000 and 2000) don’t matter. What matters here is that we are saying that the Enterprise Customer is worth 4X more to the company than the SMB Customer – from a revenue perspective. Now this metric in this example we are using is revenue – but as you can imagine, you can replace revenue with profit margins also. What we are alluding to here is that – customers can be stratified by either spend or by margins/profitability.
Now, since we have the NPS survey response at an individual level, we can compute the NPS Score taking into account the spend/revenue on a customer level.
Let’s take into account the same NPS Score calculation, but this time use the Customer LTV into the equation;
In the above example – we have 2 promoters – but both of them happen to be SMB customers and 1 detractor who happens to be an Enterprise customer. Without taking LTV and Customer Tier into account, we would come to the incorrect conclusion – that we have 40% (⅖) Promoters and 20% (⅕) Detractors in the system. But this would be incorrect – from a pure business and economic perspective. We run the risk of losing $8,000 in value – while we pat ourselves on the back for keeping $4,000 in value as promoters.
To prevent this, we can “weight” the NPS Scores based on LTV of the Customer Tier;
Revenue | Revenue Weighted | ||
Promoters | 40% | $4,000 | 18% |
Passive | 40% | $8,000 | 45% |
Detractors | 20% | $10,000 | 36% |
If you notice, in our sample dataset, we have 2 Promoters with a cumulative revenue of $4000 (2x$2000). The cumulative revenue in our sample dataset is 3 SMB’s and 2 Enterprise customers – this is a total of $22,000 (3x$2000 + 2x$8000)
Revenue Weighted Promoters : $4,000 / $22,000 | 18% |
Revenue Weighted Passive : $10,000 / $22,000 | 45% |
Revenue Weighted Detractors: $8,000 / $22,000 | 36% |
Thus, the Revenue Weighted NPS Score : 18-36 = -18
Revenue Weighted NPS Score: -18
Compare this to our Non-Revenue weighted score of +20 – so in effect, we went from a +20 of NPS Score to a -18 because we applied revenue weighting to the score. Without this insight, most companies will continue to make decisions that are directly orthogonal to their overall goals – which is to increase revenue and profitability.
In the example above, we focused in on Revenue as a metric to anchor and weight the NPS Score by. Companies in their lifecycle are generally interested in only two broad financial metrics – Top Line and Bottom Line – which is Revenue & Profit. If you are interested in making a profit based NPS model – the formula and the model is exactly the same – just replace revenue with profit and the weighting will automatically apply. All you will need to do is to – instead of plugging in the LTV (Lifetime Customer Value) – you would use the Customer Gross Margin – which is the margin you expect to make for each Enterprise Customer or SMB Customer.
If we all assume that the customers who are actively NOT willing to recommend you – are at risk of leaving you for a better product or service. With the Revenue weighting model, we can not ascribe a clear dollar value that is at risk – of leaving.
In our example above, our Revenue At Risk : $8000
In our experience, showcasing revenue metrics to line-managers has a _direct_ impact on strategy and behaviour. Line managers relate to revenue and can understand the model. As Peter Drucker said, you always manage what you measure – if we wan’t revenue and/or profitability to go up, we need to provide the tools and the underlying model to help increase revenue and profitability. The Revenue Weighted NPS Score will allow for managers to take their NPS Scores seriously – since all the metrics are tied to real world metrics – like revenue and profit margins.
Flying blind does not help!
Comments
Comments are moderated to ensure respect towards the author and to prevent spam or self-promotion. Your comment may be edited, rejected, or approved based on these criteria. By commenting, you accept these terms and take responsibility for your contributions.
Disclaimer
The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
More from Vivek Bhaskaran
QuestionPro has tried and tested a new model for identifying and measuring cognitive stress in surveys using crowdsourced usability testers.
Sign Up for
Updates
Get content that matters, written by top insights industry experts, delivered right to your inbox.
67k+ subscribers