understanding customer retention in the retail industry

8/3/2019 Understanding Customer Retention in the Retail Industry

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Understanding customer retentionin the retail industry

Retailers that monitor customer retention andanalyze its fundamental drivers have a leg up on the

competition. Our recent research suggests, however,

that there are common mistakes in any attempt

at achieving a better understanding of customer

retention. Retailers can learn from these mistakes and

from the successes of today’s industry leaders.

The shit is here to stay

A “New Normal” in consumer spending behavior has been

well publicized. As reported, this shit is the product o a

range o actors such as the recent recession, increasing

globalization, adoption o social media and market

demand or sustainable solutions. The net eect o thenew environment is that retailers across the industry are

seeing decreases in customers’ loyalty to retail brands1

(“Loyalty” has many meanings; or the purposes o this

discussion we dene a “loyal” customer as one who

remains engaged at a retailer, at the same expenditure

level, over a given period o time). This spending

drain presents new and complex issues, especially or

those retailers who rely on discretionary spending

(e.g., department, apparel, and electronics stores). For

1 2009 Deloitte Shit Index

discretionary spend-reliant retailers, understandingbehavior and retention drivers may very well mean the

dierence between survival and ailure.

Importantly, a looming demographic shit is expected to

compound the changes that have already occurred and

dramatically alter the landscape or competitors as they

ght to retain valuable customers. The Baby Boomer

generation stands on the edge o a phase o lie that

has historically been marked by a dramatic decrease in

discretionary spending. 45-54 year old Americans have

the highest discretionary spending o any age group.2

However, this age cohort is expected to decline in

population by 7.5% over the next ten years while the nexttwo oldest age cohorts (55-64 and 65+) are expected to

increase in size by 18.5% and 36.2% respectively over

the same time period.3 We believe that expanding ocus

to include acquisition, retention and improvement in the

share o wallet with a younger generation o customers is

a mandate or growth.

2 2009 U.S. Census Bureau Population Projections , 2008 U.S. Dept. o

Labor Statistics3 2009 U.S. Census Bureau Population Projections , 2008 U.S. Dept. o

Labor Statistics



Average discretionary spend across age groups4

In reaction to the recent change in the retail landscape,leading retailers have already launched initiatives to

understand and drive improved retention. Because the

consumer has changed, however, the way o measuring

loyalty should change as well. Traditional lagging indicator

“scorecards” should be supplemented with leading

indicators that leverage the use o data mining and

predictive analytics to better understand which customers

present an attrition risk and when they are likely to leave.

Furthermore, that quantitative research should be urther

supplemented with Voice o Customer (VOC) research to

understand why customers leave and how that behavior

diers across customer cohorts. The ultimate goal should

be to develop an in-depth understanding o the key

drivers o repetitive shopping behavior so that they may

be used to guide actions to improve retention. In a deeper

examination o these issues, we’ll rst take a look at the

common mistakes that are made and then describe actions

retailers could implement to succeed in this eort. We’ll do

so using case studies o retention oriented programs used

by leading organizations.

4 2009 U.S. Census Bureau Population Projections,

2008 U.S. Dept. o Labor Statistics

Our fndings

Deloitte conducted a series o executive interviews5 across

retail sectors that revealed just how acutely the customer

brand loyalty issue is aecting the industry. Executives

told us that they continue to lose customers, customer

trips and customer spend on a year to year basis (dened

as all customers that made a purchase in the previous 12

months as well as the period 13-24 months ago). While

those customers in the bottom two quartiles o spending

behavior are the usual sources o customer attrition, we

ound that customers in the top two quartiles are also

deecting at an alarming rate. The consensus is that

customers are leaving at a greater rate overall and, unlike

previous periods, those that are leaving span a greater

spectrum o the customer base top to bottom in terms o

annual spend.

Our interviews ound that this issue was even more

acute or retailers that are reliant on discretionary

spending. Interviewees provided a range o perspectives

on why customers are increasingly disloyal; however, a

consistent theme was an increase in sensitivity to price

and promotion. Customers are increasingly “splitting”

their share o wallet to cherry pick dierent items rom

dierent retailers. The executives interviewed speculated

that this shit is due, in large part, to the transparency oinormation that customers literally have at their nger tips.

The availability o competitive options, more aggressive

“high–low” pricing and increased availability o inormation

via the internet and mobile applications are driving

“smarter” consumption in an increasingly large swath o

retail categories.

5 Interviews were conducted in June and July, 2010

2008 Average discretionary expenditure ($)

65 and older55-6445-5435-4425-34>25

$10.3

$19.4

$21.5

$20.4

$16.3

$9.1

36.2%

18.5%

-7.5%

5.8%10.1%

6.2%

Expected % change in population (2010-2020)

2



Current state: Three common mistakes

1. Misguided loyalty programs

An actionable understanding o customer retention is

imperative in this new market. Retail executives should,

however, resist the temptation to use a loyalty program

solely as a method to retain customers. This is the rst

mistake we observed in the subjects o our retention

research. Whether it is an organizational legacy or newly

launched, a loyalty program can oten be misguided. In

many channels, these programs are nearly ubiquitous.

84% o shoppers belong to at least one,6 and most

households belong to at least 12 such programs. Yet, too

many retailers rely on these programs as dierentiators.

Leading companies are demonstrating that what truly

makes a loyalty program a competitive dierentiator

is the ability to develop unique customer insights rommining the program’s data. Loyalty programs should be

evaluated based on their ability to deliver dierentiated

insights across the enterprise, drive accretive business value

and use programmatic treatments that are targeted and

meaningul.

2. Ignoring “free agents”

In an environment where retailers may likely have more

ormer customers than current ones, it is surprising that

so ew are tracking lapsed customers. A lack o attention

to those customers that haven’t made a purchase in the

last ew months creates two signicant problems. First,

it eliminates the ability to create programs designed toreengage ormer customers who may be willing to come

back given their “ree agent” status. Second, it doesn’t

allow marketing analytics to create models based on lapsed

customer date to predict when current customers may

leave so that they may be targeted with retention related

treatments. These two reasons alone provide enough

business value to give old customers a new look and to

monitor existing customers or signs o impending attrition.

6 Deloitte/Harrison Group Study, July 2010

3. Lack of enterprise-wide usage

Finally, we ound a undamental deciency in the

connection between how retailers understand and predict

changing loyalties and where they use that collectable data

to make business decisions. This disparity was consistently

noted across the spectrum — rom dening retention

metrics and developing methodologies or tracking those

metrics, to initiating actions rom the collected inormation

to generate insights about customer behavior and drivers.

Amongst the retailers we interviewed, we ound that

most were using retention inormation in the marketing

unction, but only a ew use that same benecial

inormation in merchandising and/or operations. This

observation underscores the need to develop enterprise

wide transparency.

What are the leaders doing?

Our interviews did reveal a wide variety o innovative

and leading practices. Retailers leading on the retention

ront are already using the data that they have to make

inormed decisions about where to ocus limited resources.

These companies are using well-dened retention metrics

to signal the need to take action. We ound our leading

practices that can be used to properly evaluate the current

retention situation and ormulate a strategy or addressing

the undamental reasons or customer migration.

1. Get the basics right and track them continuously

Start by measuring the basics o retention behavior ona regular basis to answer three questions: how oten do

customers make a purchase, what types o purchases are

those customers making and what is the value o those

purchases?

A specialty apparel retailer we spoke with tracks a series

o basic customer behavior and retention metrics on

a rolling 12 month basis. These metrics include what

categories and channels the customers purchase in, their

relative protability, sale vs. ull price merchandise mix,

online shopping cart and click stream data, requency o

purchase, monetary value o all purchases and time since

most recent purchase. By synthesizing basic Recency,

Frequency and Monetary (RFM) metrics in concert with

more sophisticated behavioral markers (such as an

abandoned online shopping cart analysis), this retailer

identies their valuable customers and targets marketing

actions designed to increase protability. By grouping

customers based on likelihood to make a purchase, this

retailer can ocus scarce marketing resources where they

will make the most impact. By ocusing relevant marketing

eorts to the most likely to respond customers, this retailer

has also seen a positive trend in their retention because

customers value the less requent but more relevant

messages.

3



2. Develop usable analytics

Develop customer engagement analytics and research

to gain a more in depth understanding o key drivers o

retention behavior.

Through intensive customer data analysis, one retailer we

interviewed learned that new customers who remained

active beyond their rst year as a customer were ve

times more likely than others to remain customers or

multiple years into the uture. Because o this critical

insight, this retailer set o on a journey to identiy the

‘rst year’ behavior patterns o customers whom they had

previously retained longer than one year. In short, they

were searching or behavior markers that would enable

them to monitor, track and ultimately infuence ‘rst year’

customer behavior to increase the likelihood o long termretention. Exploratory analysis ound that markers beyond

simple visit requency, spend per visit and recency o visit,

were prevalent in the data. For instance, they ound that

certain product categories and mixes o categories within

market baskets were highly linked to a ‘second year’, and

thus, long term retention. Armed with these and other

key ndings, the client developed a set o predictive

models that were applied to ‘rst year’ customers. These

models assessed the customers’ behavior patterns and

demographics to determine both their level and quality o

interaction with the retailer. Customers ound to be lagging

in their interactions were treated with marketing strategies

designed to stimulate retention-driving behaviors.Conversely, those customers with higher quality and levels

o interaction were not oered marketing treatments or

discounts. This strategy, enabled by predictive analytics,

allowed the retailer to ocus scarce marketing resources

where they would count most.

3. Track retention across retail channels

Enable tracking o engagement and retention markers

across retail channels to minimize retention gaps created

when customers migrate rom one channel to another.

Many leading class retailers are actually ocused on both

customer engagement and retention across channels.

They measure the ecacy o their programs by evaluating

engagement actors to understand where their best

customers preer to interact with the brand and giving

them rewards or doing so more requently and with a

higher level o intensity than the average. These types

o markers are generally a predictor o uture purchase

behavior. One retailer is using their web site click stream

data, Facebook trac, Twitter ollowership, and other

non-purchase engagement actors to identiy these

customers at dierent points in the purchase liecycle.

The engagement score that is developed rom this data

is then leveraged to award that customer or their loyalty

to the brand by giving them targeted incentives to make

purchases, inviting them to unique events and making

special service channels available when needed.

4. Inject Voice Of Customers (VOC) into the mix

Establish a systematic method or getting the Voice o

Customer captured, analyzed and leveraged or identiying

retention improvement opportunities.

An upscale retail client had historically recorded retentionmetrics that varied signicantly across the customer base.

Not surprisingly, they ound that higher annual spend

customers returned year to year at a much higher rate

than lower spend customers. The recent economic turmoil,

however, turned this trend upside down and attrition

became an issue across the entire customer base. Not

satised with merely examining the statistics, the retailer

recently conducted primary customer research and spoke

with sales associates to get a better handle on why

attrition had become so widespread across the customer

base. What they ound was that the commission based

sales associates were ghting over the best customers

and ignoring the customers with unknown value. This

skewed service model was essentially driving customers to

competitors’ stores that oered more egalitarian service.

The insight that the sales and service model was actually

causing customers to deect at both ends o the spend

spectrum led to changes intended to create a more team

based selling approach targeted at known high value

customers and incentives or engaging customers that are

new and/or o unknown value.

4



Take action

I we’ve learned only one thing rom the last two years,

it is that consumers change preerences, attitudes, and

sentiments quickly. This maniests itsel in rapid changes

in behavior. Adapting to the pace o those changes will

make a dierence in retaining the existing level o trips and

basket size. While the state o the consumer and economy

is still very ragile, taking lessons rom the aorementioned

leading practices enables a more thorough, and ongoing,

understanding o retention drivers. However, that baseline

understanding must then be used to hypothesize and

test the right actions to improve retention. Management

actions may take the orm o assortment, pricing,

marketing communication, or customer experience (i.e.,

service model) adjustments. Many retailers, however, don’t

employ well designed tests to truly understand the ecacyo the actions they take.

Retention measurement is a undamental building block or

success in today’s retail environment, but it also has to be

supplemented with customer behavior root cause analysis

leveraging Voice o Customer research and predictive

analytics. This may seem like a complex endeavor;

however, the preerred course o action is to get started

with inormation that is easily accessible, only adding

data and resources when the organization’s capabilities

are mature enough to use them and the business case

is warranted. Engaging valuable customers in today’s

environment is an achievable objective; those that do it

well are already thinking creatively about the problem and

using a variety o resources to make a positive impact on

customer retention.

This publication contains general inormation only and is based on the experiences and research o Deloitte

practitioners. Deloitte is not, by means o this publication, rendering business, nancial, investment, or other

proessional advice or services. This publication is not a substitute or such proessional advice or services,

nor should it be used as a basis or any decision or action that may aect your business. Beore making

any decision or taking any action that may aect your business, you should consult a qualied proessional

advisor. Deloitte, its aliates, and related entities shall not be responsible or any loss sustained by any person

who relies on this publication.

As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary o Deloitte LLP. Please see

www.deloitte.com/us/about or a detailed description o the legal structure o Deloitte LLP and its subsid iaries.

Copyright © 2011 Deloitte Development LLC. All rights reserved.

Member o Deloitte Touche Tohmatsu Limited

Authors

Matt McNaghten

Senior Manager

Deloitte Consulting LLP

+1 216 589 3756

[email protected]

Clark Passino

Manager

Deloitte Consulting LLP

+1 312 486 5854

[email protected]

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