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Retail Marketers, does NPS really answer your customer monitoring questions in these turbulent times?

eTradeWire News/10709715
Hive Marketing Cloud
There's no doubt that the world feels pretty upside down right now. Retail brands are especially at risk of alienating customers if they misread the signals. But what data-points can you trust when everything is changing so fast?

BRISTOL, U.K. - eTradeWire -- Now, more than ever, keeping a watching brief on both the health and revenue potential of your customer database is paramount.  But how can Marketers consistently and accurately monitor these attributes?

RFM (Recency, Frequency and Monetary value) analysis is a database marketing technique that seeks to understand an individual customer's *current* relationship with your organisation by determining the recency, frequency and monetary value of the purchases they make with your business.

RFM fundamentally differs from other more simplistic measurement techniques like NPS scores (Net Promoter Score) as it is rooted in fact.  For example an NPS score tends to indicate how a customer feels based on the service they have recently experienced.  While this has some intrinsic value, especially where measuring customer experience could act as an early warning indicator in service or product delivery teams, there are alternatives that can directly inform marketing strategies to specific customer segments based on customer data analysis.

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NPS-styled feedback suffers from the fundamental issue that scoring must be volunteered (usually once prompted) by the consumer; because of this scores are provided in an ad hoc and usually quite polarised way as consumers only 'bother' when they feel they have had a particularly compelling, or negative, experience.

Conversely RFM analysis is based on a customer's actual buying behaviour to determine their score, and therefore segment.  Equally it does not require any further action on behalf of the customer as analysis is conducted passively by looking at recent transaction and engagement behaviour.

RFM can identify each individual customer's score, which when grouped into key segments, can classify customers as lapsed, at risk, promising, loyalists, champions and more.  Understanding who your highest and lowest value segments are alone is a compelling aspect of monitoring in todays turbulent times.

Not least, RFM can provide the opportunity for companies that manage multiple brands to monitor the movement of consumers between segments and brands, which can be very illuminating.

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Knowing your customers' live RFM score also helps you to understand the current customer risk and advocacy status, historical customer trajectory over time, as well as facilitating better planning and budgetary decisions, rooted in evidence.

To learn in detail about how to assign scores to your customer database, download the NEW eBook from Hive Marketing Cloud: RFM ANALYSIS, A MARKETERS' GUIDE.  Saving lapsed customers and turning them into brand loyalists with RFM at https://rfmformarketing.com/

Claire Thatcher

Source: Hive Marketing Cloud
Filed Under: Retail

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