Personalizing the customer experience: Driving differentiation in retail

Retail Practice

Personalizing the

customer experience:

Driving dierentiation

in retail

Today’s customers expect a personalized experience when they are

shopping. An effective personalization operating model, featuring

eight core elements, can help retailers and brands keep pace.

March 2020

by Erik Lindecrantz, Madeleine Tjon Pian Gi, and Stefano Zerbi

Today’s retail environment is challenging from

almost any perspective because of price pressure

from discounters, market disruption from online

players, and increased price transparency for

shoppers. Traditional differentiation approaches

in retail—such as a unique selection or strategic

pricing and promotions—are not as effective as

they once were, as competitors can easily imitate

them. But differentiation is still possible through

personalized approaches in which retailers create

unique experiences tailored to individual customers.

Highly personalized customer experiences, when

offered to millions of individual customers by using

proprietary data, are difficult for competitors to

imitate. When executed well, such experiences

enable businesses not only to differentiate

themselves but also to gain a sustainable

competitive advantage. Moreover, our research has

shown that personalized experiences drive up both

customer loyalty and the top line.

Meeting customers’ expectations for

a personalized experience

Thanks to online pioneers, such as Amazon,

customers have grown to expect and desire

personalized experiences: a survey of 1,000 US

adults by Epsilon and GBH Insights found that the

vast majority of respondents (80 percent) want

personalization from retailers.

Personalization can

even be called a “hygiene factor”: customers take it

for granted, but if a retailer gets it wrong, customers

may depart for a competitor.

Personalization, once limited mainly to targeted

offers, now extends to the entire customer

experience. This means that customers want

personalization throughout their interactions

with a retailer—with multiple, personalized

touchpoints that enable them to allocate their time

and money according to their preferences. In the

best personalized experiences, retailers make

the customer part of the dialogue and leverage

data to create one-to-one personalization.

Customers receive offers that are targeted not

just at customers like them, with brands targeting

at the segment level with broad-based offers, but

at them as individuals, with products, offers, and

communications that are uniquely relevant to them.

Understanding how

personalization pays off

Given customers’ expectations, retailers

must respond to the demand for personalized

experiences not only to differentiate themselves

but just to survive. When done right, though,

personalization allows retailers to do more

than merely survive: it enables them to thrive.

Personalization at scale (in which companies have

personal interactions with all or a large segment of

their customers) often delivers a 1 to 2 percent lift

in total sales for grocery companies and an even

higher lift for other retailers, typically by driving up

loyalty and share-of-wallet among already-loyal

customers (for whom data are more abundant and

response rates are higher). These programs can

also reduce marketing and sales costs by around

10 to 20 percent.

Not only that, successful personalization programs

yield more engaged customers and drive up the top

line. In general, a positive customer experience is

hugely meaningful to a retailer’s success: it yields

20 percent higher customer-satisfaction rates, a

10 to 15 percent boost in sales-conversion rates,

and an increase in employee engagement of 20

to 30 percent. Customer-experience leaders in

the retail space (retailers with consistently high

customer-satisfaction scores) have provided their

shareholders with returns that are three times

higher than the returns generated by retailers with

low customer-satisfaction scores.

To maximize the results of a personalization program,

we recommend focusing initially on the most loyal

customers, as programs targeting regular shoppers

“New Epsilon research indicates 80% of consumers are more likely to make a purchase when brands offer personalized experiences,” Epsilon,

January 9, 2018, us.epsilon.com.

For more information on customers’ expectations, see Julien Boudet, Brian Gregg, Gustavo Schüler, and Jane Wong, “What shoppers really

want from personalized marketing,” October 2017, McKinsey.com.

For more information on personalization at scale, see Julien Boudet and Kai Vollhardt, “Personalization at scale: First steps in a profitable

journey to growth,” August 2018, McKinsey.com.

Personalizing the customer experience: Driving differentiation in retail

yield a return on investment three times higher than

that of mass promotions. Moreover, building data on

the most loyal customers sets off a virtuous cycle

by generating ever-more-relevant data and higher

response rates that further boost data quality.

Learning from success stories

Retailers across many different categories have

managed to implement personalization at scale

effectively and have significant success to show

for the effort. Of course, Amazon has been a

pioneer in this field, but other companies—including

grocery companies, which make up for what they

lack in e-commerce data with loyalty data from

their physical stores—have moved into the top tier

in recent years with successful personalization

programs of their own.

Personalization pioneer: Amazon

As the ruler of large, pure-play, online retailers,

Amazon has used sophisticated analytics to shape

its personalization efforts. Over time, Amazon has

expanded its personalization program to show

customers products that are often purchased with

the item they are viewing, display items that can

be bundled with products in a customer’s cart, and

recommend additional products in the e-mails it

sends to confirm transactions.

Amazon continues to raise the personalization bar

with ever-more-granular, -innovative offerings

to individual customers. For example, Amazon

Prime Wardrobe has recently launched a personal

shopping service exclusively for Prime members.

Customers complete a survey about their styles

and fit preferences, and a team of stylists provides

personalized recommendations from more than half

a million items across brands. Amazon will probably

continue to lead innovation in personalization, but

other, smaller retailers—with far less sophisticated

systems—are setting new standards, too.

Dynamic personalization: European grocer

A large European grocery company has

successfully moved from one-size-fits-all

marketing to personalized experiences. This

shift began with research based on the retailer’s

macrosegmentation; the retailer was then able to

drill down a level further to create smaller segments

based on location, time of day, and other specifics.

From there, the grocer built a new transaction

engine so it could institute business rules. For

example, the engine does not offer discounts

to regular shoppers who buy coffee or lunch at

the store every day. Instead, it routes discounts

toward other segments and users of the grocer’s

smartphone app, who receive offers as they pass by

the store.

The rich data from this grocer’s transaction engine,

personalization engine, mobile app, and other tools

have allowed the company to track sales across its

entire network of locations—enabling the grocer to

optimize for weather, day of the week, time of day,

and similar data points that greatly enhance the

effectiveness of promotions.

Omnichannel experience: Sephora

Sephora, an international beauty-products retailer,

offers personalized experiences that are truly

omnichannel in their presentation to consumers.

The company’s digital channels—particularly its

mobile app—encourage customers to book in-store

makeovers and fashion consultations. The app’s

“in-store companion” feature enables users to find

a store, check to see if an item is in stock, and book

a reservation. When customers choose to have

their makeup done in stores, they receive a log-in

for the app so that the makeup artist can input each

product she or he used into the customer’s personal

profile. The app also allows customers to virtually try

on products and to receive recommendations based

on their personal beauty traits. When customers

visit a Sephora store, they can use the app to find

the products they have virtually sampled.

All of Sephora’s customer communications—no

matter the platform—display the customer’s loyalty

points. Sales associates can see these point totals,

too, and can access a customer’s profile in-store.

The profile includes data on the customer’s in-store

purchases, online browsing and purchasing

patterns, and interactions with in-store salespeople.

3Personalizing the customer experience: Driving differentiation in retail

Sephora’s program is notable for another reason,

too: it clearly demonstrates the effectiveness

of focusing on the most loyal customers. The

company’s tiered loyalty program, Beauty Insider,

offers its highest-level members early access

to new products, invitations to exclusive events,

free custom beauty services, and more. All

members receive customized recommendations

based on profiles they fill out online. Their profile

details—such as first name, buying habits, and quiz

responses—are deployed across channels. Store

associates can access a customer’s profile in the

store and track items that were sampled, making it

easy for customers to find and buy those items on

the website or app. Every communication from the

brand, on every platform, displays the customer’s

loyalty points, and offers are synchronized across

platforms.

The results of Sephora’s personalization efforts have

been striking. The loyalty program now has around

25 million members. In 2018, members accounted

for 80 percent of Sephora’s total transactions.

And

for the third year in a row, with a score of 79 out of

a possible 100, Sephora has claimed the top slot in

Sailthru’s Retail Personalization Index.

In-store personalization: Nike

Not to be outdone in the personalization game

is Nike, one of the largest athletic-footwear and

athleisure companies in the world. Nike has

taken personalization all the way to the individual

product by allowing customers to configure their

own clothes and shoes. The company recently

launched a 3D sneaker-customization platform that

allows shoppers to generate real-time, shareable

snapshots of finished footwear.

Personalization extends to Nike’s physical locations,

too. Nike’s flagship store in New York City offers

a compelling omnichannel shopping experience

driven by membership in NikePlus, the company’s

personalized loyalty program. Members receive

personalized, exclusive benefits, such as access

to Nike Speed Shop, which offers a data-driven,

locally tailored assortment of “NYC favorites.”

Members can also reserve items to be stored in

pickup lockers and retrieve them by scanning their

NikePlus member pass. With Nike Shop the Look,

members can use QR-code-scanning to determine

the availability of their preferred sizes and colors

and to request delivery to their selected pickup

location or dressing room. Using Instant Checkout,

members can skip the cash-register line and check

out directly from their own stored-payment device.

Other benefits include access to Nike Expert

Studio, where members can book personal, one-

on-one appointments with Nike experts, and the

opportunity to book appointments with Nike by You,

where members can view a selection of silhouettes

that are uniquely fitted to their specifications.

The necessary changes require a

signicant shift in the mindsets

of employees so that they become

comfortable with the experiments

personalization requires.

Pamela N. Danziger, “How to make a great loyalty program even better? Sephora has the answer,” Forbes, January 23, 2020, forbes.com; James

Stewart, “Sephora gets 80% of its sales from this,” Ragtrader, November 6, 2018, ragtrader.com.au.

“The 3rd annual Retail Personalization Index,” Sailthru, September 17, 2019, sailthru.com.

Personalizing the customer experience: Driving differentiation in retail

Identifying common challenges

for retailers

Given the success stories, it is little surprise that, in a

Periscope by McKinsey survey of retailers attending

World Retail Congress 2017, 95 percent of retail

CEOs say personalizing the customer experience

is a strategic priority for their companies. But

that same survey showed that only 23 percent of

consumers believe that retailers are doing a good

job in their personalization efforts. What is behind

this disparity?

First of all, most retailers are still in the early stages

of their personalization efforts. Our research

indicates that only 15 percent of retailers have fully

implemented personalization strategies. More

than 80 percent are still defining a personalization

strategy or have begun pilot initiatives. The

remaining retailers have decided to deprioritize

personalization for now, for various reasons.

Retailers seem to be facing four main tactical

challenges in getting personalization off the ground:

1. Data management. More than two-thirds

of survey respondents (67 percent) indicate

that their greatest personalization challenge

is the gathering, integration, and synthesis of

customer data.

2. Data analytics. Acquiring and maintaining

in-house expertise in analytics and data science

are proving to be major concerns for 48 percent

of surveyed retailers.

3. Alignment of retail organizations across

functions. For many retailers, siloed processes

and organizational models prevent the efficient

and prompt sharing of customer data and

promotion decisions (for example, difficulty

in aligning the marketing and merchandizing

teams). Of the survey group, 43 percent say

these silos “make life difficult,” and 25 percent

report that such silos make it difficult to get

vendor funding—as well as buy-in—from

suppliers for personalized offerings (especially

in the grocery category). In many cases, these

sorts of changes require a significant shift in

the mindsets of employees so that they become

comfortable with the test-and-learn and fast-fail

experiments that personalization requires.

4. Tools and technology enablement. Of the

survey participants, 67 percent admit that

they did not have the correct tools in place to

execute personalization at scale. An additional

41 percent say finding the right solution partner

was a struggle.

These challenges are further complicated by

the fact that many retailers still operate under

a hybrid, “bricks and clicks” strategy, making it

even more difficult to implement the right levels of

personalization in stores and online. Retailers with

an omnichannel setup, however, have their own

challenges, particularly in structuring offers and

executing across communication touchpoints.

Overcoming the obstacles

All is not lost, however. As our previous case

examples show, retailers across the spectrum have

managed to create truly personalized experiences

for both the online world and brick-and-mortar

channels. The results for both the affected

customers and the financial results are impressive.

So how do these retailers do this?

There is no single winning recipe, as the breadth of

our case examples shows. In our experience, though,

an effective personalization operating model has

four prongs: a data foundation, decisioning, design,

and distribution (exhibit).

Within this model are

eight core elements.

First, all of these retailers have started small. They

begin by testing and learning while building the

necessary capabilities and multidimensional

intelligence on customers over time. Data

management is crucial here: getting the right data

For more on the personalization operating model, see Julien Boudet, Brian Gregg, Kathryn Rathje, and Kai Vollhardt, “No customer left behind:

How to drive growth by putting personalization at the center of your marketing,” July 2018, McKinsey.com.

Personalizing the customer experience: Driving differentiation in retail

is much more important than gathering every last

scrap of data. The customer database needs to be

multidimensional, but it does not have to provide a

360-degree view of customers. Successful retailers

start by gathering the most important data before

scaling up to a broader understanding of each

individual customer.

A detailed customer segmentation and analysis

is the next common element. With the right data

management and analytics in place, retailers can

identify customers’ value triggers and then score

and rank customers to facilitate effective targeting

and personalization.

Developing a playbook of responses to certain

triggers—such as abandoning a shopping cart and

browsing of items that belong to a larger collection—

is the third element. The goal here is to build a library

of offers, with a few hundred as a good starting

point. Some companies eventually build a large

library of content that they can put together into a

personalized magazine for customers. The right mix

of triggers results in open and click-through rates

that outperform those of traditional mass marketing.

The fourth element is a robust decisioning engine

(campaign coordination) that plans experiences

across multiple channels and reduces the risk of

sending conflicting messages. It also allows retailers

to drive the value created by each touchpoint and to

maximize that value across the multichannel lineup.

An agile cross-functional team is the fifth element. A

team room should be staffed by a cross-functional

team—the engineers, merchandising professionals,

and marketing experts should all be in one room.

The team’s work should include weekly deployments

implemented with a test-and-learn spirit more

commonly found in the Internet software betas of

Google and other web giants. The goal of this cross-

functional room is to break down organizational

Exhibit

Insights 2020

Personalizing the customer experience: A true driver of differentiation in retail

Exhibit 1 of 1

In our experience, eight core elements are needed to succeed in personalization.

Data foundation Data management. Develop a multidimensional view of the customer to serve as the

backbone of analytics. Quality should take precedence over quantity; having the right

data is more important than having extensive data.

Decisioning

Customer segmentation and analytics. Segment customers, identify value

triggers, and score customers accordingly.

Playbook. Create a library of campaigns and content that can be matched

with customers.

Decisioning engine (campaign coordination). Develop a multichannel decision

engine to prevent conicting messages and drive maximum value per touchpoint.

Design

Cross-functional team. Assemble a cross-functional, co-located team to manage

weekly deployment in a test-and-learn culture for faster results.

Talents, capabilities, and culture. Secure the right capabilities and talent, often

begun by setting the right ambition in leadership.

Distribution Technology enablement. An optimized technology platform can be complex;

start with existing technology and squeeze value from it rst.

Test and learn. Don’t wait for perfection; get started and improve over time with analytics.

6 Personalizing the customer experience: Driving differentiation in retail

silos and to have mixed teams working together to

increase pace and quality.

The sixth element of a successful personalization

effort is securing the right talents, capabilities, and

culture to staff the team. The leadership needs to

set the right example at the outset, but from there,

the program will touch everyone from the HR team

to the marketing and merchandising staffs. The right

mix of data scientists and marketing-technology

experts is also necessary.

The right technology enablement can be complex to

implement, but it forms the core—and the seventh

element—of a successful personalization effort.

Getting the various systems to work together and

pull in the same direction can form the commercial

heart of an organization. Most retailers are not

maximizing the value that their existing technology

platforms can offer, so unifying the systems will

squeeze more value from them along the way.

Building a more flexible platform on top of legacy

systems is often beneficial, too.

Finally, retailers should undertake this effort with a

test-and-learn approach. There is no need to build

a vast, multivariable database as the first step. As

the exhibit notes, do not wait for perfection. Instead,

start small. Pick a straightforward experience

that will generate a positive impact and start with

that. Test the efficacy of that idea, generate useful

metrics, and then expand to a second idea. Repeat.

As the resulting impact is quantified, and the

insights generated by experiments are funneled

back to the team, the loop will be closed on the

analytics powering each deployment.

In some retail sectors (the grocery sector, for

example), collaboration with suppliers is important.

The goal here is to build a mutually beneficial

partnership with the supplier. To do so, shift funding

from mass promotions to personalized experiences

and give vendors full transparency into how their

products perform. Additionally, provide each vendor

with a point person who manages its relationship

with the retail network. This person will quickly

become a strategic partner who helps better align

the retailer and supplier.

All eight elements humming in unison will form an

effective personalized-experience engine that

differentiates the retailer, increases share of wallet

among the most loyal customers, and ultimately

boosts the retailer’s top and bottom lines.

Getting started

Given the potential impact of personalization, it

makes sense that retailers would be eager to begin

their personalization efforts. But how can they do

that thoughtfully?

The first step is to define a short list of high-impact

use cases that are relevant to the consumer but

not too complex to execute against. A skilled cross-

functional team can then be assembled to construct

an integrated database for those use cases. The

team should make sure that the data are both highly

available and targeted while also considering the

needs of future programs (including high-impact

use cases). This database does not need to be

perfect. Rather, it should be built through iteration,

testing, and learning.

To begin building a personalization program—and

to fuel its effective execution—retailers should

create a cross-functional team to test and learn

from experiments. Analytics and technology

professionals will be critical to the program,

especially when scaling it up. Finding the right

external partner to help develop the personalization

program is important, too, and will help accelerate

the retailer’s progress toward results: a more

personalized experience, greater customer loyalty,

marked differentiation, increased wallet share, and

substantially better top and bottom lines.

Erik Lindecrantz is a partner in McKinsey’s Tokyo office, Madeleine Tjon Pian Gi is a partner in the Amsterdam office, and

Stefano Zerbi is a senior partner in the Milan office.

7Personalizing the customer experience: Driving differentiation in retail