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The best method for your business

Linkage using other business metrics

Financial linkage + how it works


Let’s discuss

How do you measure

CX program success?


• Demonstrates the relationship

between customer service and

loyalty and sales

• Gives a richer understanding

of the customer experience

• Helps prove out a “what’s

in it for me” for franchisees

or locations

Financial linkage Linkage with other business metrics

• CX data can be related to

location attributes and

business metrics

• Connection contributes to

improved field engagement—

locations are seeing the CX

metrics relate to other

important business metrics

they already believe in

There are multiple ways to look at linkage




loyalty and sales





or locations




business metrics







Let’s look closer at financial linkage


Financial linkage + The Service Profit Chain

The Service Profit Chain,

by SMG co-founder

Len Schlesinger

From Analysis techniques used

to demonstrate financial linkage,

an SMG white paper

Putting the Service Profit

Chain to Work, a Harvard

Business Review article

Customer loyalty

Financialperformance

Employee loyalty

• Satisfaction

• Retention

• Productivity

• Satisfaction

• Spend/recommend

>>


Customer

Experience

The customer experience is one of many

factors impacting financial results

Products

Competition

Economy

Financial

Management

Location

Customer

Experience

Factors Impacting

Financial Results

Marketing/

Advertising

Store-Level

Drivers of

Satisfaction

Overall

Satisfaction

Loyalty

1. Top Drivers

1. Likelihood to Recommend

2. Likelihood to Return

$

Sales Growth

$


Key ways to analyze financial linkage

Store-levelLinking store satisfaction

and loyalty with store comp sales

Transaction-levelLinking respondent satisfaction

and loyalty with individual spend


r=..109; p<.05

The relationship exists between

Likelihood to Return and comp sales

-0.2%

0.8%

1.6%

-1%

0%

1%

1%

2%

2%

Bottom 33% Middle 34% Top 33%

Co

mp

Sale

s

Average Return:

Range of Scores:

71% 77% 82%

65–74% 74–79% 79–87%


r=.116, p<.05

There is a significant, positive relationship

between Return and comp transactions

-5.5%

-4.4%

-3.8%

-6%

-5%

-4%

-3%

-2%

-1%

0%

Bottom

33%

Middle

34%

Top

33%

Co

mp

Tra

nsa

cti

on

71% 77% 82%

65–74% 74–79% 79–87%

Average Return:

Range of Scores:


r=..202 p<.05

There’s a relationship between Likelihood

to Return and higher comp sales

Bottom Middle Top

Co

mp

Sale

s

20%

10%

0%

-10%

50% 55% 60% 65% 70% 75%

Likelihood to Return

Store: 1234

Return: 73%

Comp Sales: 6%

Store: 5678

Return: 53%

Comp Sales: 9%

“Tourist Location”

Store: 5555

Return: 72%

Comp Sales: -9%

“Construction”


Key ways to analyze financial linkage

Store-levelLinking store satisfaction

and loyalty with store comp sales

Transaction-levelLinking respondent satisfaction

and loyalty with individual spend


POS receipt links VisitView survey measures to data from actual visits

Linking satisfaction + loyalty

to customer behavior

• Date of visit

• Product(s) purchased

• Amount spent

• Associate or server’s name


The customer experience drives

average spend

$41.82

$51.31 $52.98

$58.03

$67.25

Highly Dissatisfied Dissatisfied Neither Satisfied Highly Satisfied

Avera

ge T

icket

INCREASE16%

SMG retail client – Transaction-level linkage


Service standards impact loyalty

measures + spend

Visited Fitting Room

Associate Made Helpful Suggestions

Showed Additional Products

✔ ✔

✔

✔

✔

✔

$44.42

$56.83 $57.55

$62.08 62%

40%

85%89%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

$35.00

$45.00

$55.00

$65.00

$75.00

% H

igh

ly L

ikely

to R

eco

mm

en

d

Avera

ge S

pen

d

SMG retail client – Transaction-level linkage


Tip amounts correlate

to satisfaction levels

% H

igh

ly S

ati

sfie

d w

/ S

erv

er

Att

en

tiven

ess

Tip

s

1% 2% 4%

24%

69%$7.23 $7.19

$7.56 $7.76

$8.67

$0

$1

$2

$3

$4

$5

$6

$7

$8

$9

$10

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Highly Dissatisfied Dissatisfied Neither Satisfied Highly Satisfied

SMG restaurant client – Transaction-level linkage


Chipotle Not Highly Satisfied n=3,312; Chipotle Highly Satisfied n=4,606; All other n=107-6,056

Great experiences drive

actual return behavior

33.2

31.0

Not Highly Satisfied Highly Satisfied

Average days to return to

Chipotle by OSATBrand

Difference in days

to return for Highly

Satisfied guests

Jimmy John’s +0.3

Noodles & Company 0.9

Jason’s Deli 1.7

Panera 1.8

Potbelly 2.1

Chipotle 2.2

Panda Express 2.2

Pei Wei 2.4

Wing Stop 2.8

Qdoba 4.1

Quiznos 5.1

2 d

ays


Linkage using other business metrics




loyalty and sales





or locations




business metrics







Linkage types




loyalty and sales





or locations




business metrics







Let’s look closer at linkage with other metrics


Let’s discuss

What metrics could you

connect to your CX data?

What metrics are valued

within your organization?


Other business measures to consider

Direct metrics

• Employee metrics – Contact center, employee engagement, manager tenure, turnover

• Operational metrics – Traffic information, drive-thru timers, EcoSure Audit

• Merchandise metrics – Inventory turns

Indirect metrics

• Store layout

• Store remodels

• Other store attributes – # of registers, type of kitchen, etc.


SMG client – Employee engagement linkage

Connecting Associate Voice with VisitView

71%

76%

Bottom 20%

Engagement

Top 20%

Engagement

Overall Satisfaction by employee engagement

Key learning: Employee engagement correlates with CX performance


Connecting employee engagement

performance + turnover data

55%

226%

16%

179%

0%

50%

100%

150%

200%

250%

Average Manager Turnover Average Team Member Turnover

% A

vg

. S

ix-M

on

th T

urn

over

Bottom Performers Top Performers

SMG client – Employee turnover analysis

Key learning: Top performers on employee engagement also see less turnover


r=.169; p<.05

On average, higher Recommend scores =

better comp sales + better SocialView ratings

-2.5%

-1.7%

-1.3%

-3.0%

-2.5%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

Bottom 33% Middle 33% Top 33%

Avera

ge C

om

p S

ale

s

Avg. Comp

Sales: -1.8%

2.8 2.9 3.2

58% 66% 73%Average Recommend:

Key learning: Social ratings follow store sales and loyalty


Manager interactions strike a chord with guests

Situation Insight Action

As an international restaurant

chain that differentiates

on the dine-in experience,

Hard Rock Cafe knows

the important role

manager interactions

play in ensuring customer

needs are being met.

But to quantify the service

standard’s impact and make

sure it was being executed

consistently, they decided

to use their customer

measurement program

to look into the data.

Results

Pairing the results of the

service standards question

with Overall Satisfaction

scores, Hard Rock Cafe

learned that guests who

interacted with a manager

were consistently more

satisfied than those who

didn’t—unfortunately,

these interactions were

only happening 40%

of the time.

Having made sure restaurants

were staffed appropriately

during peak times, they

knew it was lack of

execution—not limited

resources.

01 | Included Manager

Interaction scores in internal

communications as a key

performance metric

02 | Distributed monthly

communications to

restaurant and regional

managers to call out top

and bottom performers

03 | Invited SMG team

to company conferences

to relay the importance

of front-line execution

Overall Satisfaction3+ pts

Problem Resolution

6+ pts

of locations improved

Manager Interaction scores

%81

Reduction in call

center volume

12 %

Key learning: Improving in-restaurant can lead to reduced call center volume


Connecting drive-thru timers + VisitView scores

Key learning: Getting it right is more important than getting it fast

Overall Satisfaction

SMG restaurant client – Drive-thru times by Accuracy and OSAT

Accuracy

31% 47% 57% 71%

27% 43% 53% 68%

25% 41% 51% 65%

18% 34% 45% 59%

Dri

ve-T

hru

Tim

es

Worst Poor Good Best

Fast

est

Fast

Slo

wS

low

est


Fitting room cleanliness saw the largest, most

sustainable improvement following a remodel

41%

50%

44%

40%

61%

50%

43%46%

41%

36%

43%

36%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Non-Remodel 1–2 Months

After

6+ Months

After

% T

op

Bo

x

Restroom Cleanliness Fitting Room Cleanliness Ease of Locating Depts Store Cleanliness

Key learning: Remodel data can be linked to VisitView data

SMG retail client – Fitting room remodel vs. non-remodel


The best method for your business


Take action

Determine which metrics are valued within your organization01

Identify data owners and location 02

03 Share with your SMG project team for analysis

© 2016 service management group | confidential | all ...info.smg.com/rs/331-pnv-274/images/prove...

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