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9/14/2020 Use Personalization to Enrich Customer Experience and Drive Revenue

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Use Personalization to Enrich Customer Experience andDrive RevenueRefreshed 2 April 2019, Published 20 December 2017 - ID G00331880 - 19 min read

FOUNDATIONAL This research is reviewed periodically for accuracy.

By Analysts Penny Gillespie, Guneet Bharaj

Personalization is a top priority for application leaders working on digital commerce andcustomer experience. An effective personalization strategy enhances customer experience,leading to reduced costs as well as increased revenue from greater customer satisfaction, loyaltyand advocacy.

More on This TopicThis is part of an in-depth collection of research. See the collection:

OverviewKey Challenges

Use Customer Data Management Technologies to Deliver Better Customer Experiences■

Customers expect a personalized experience wherever they engage with a brand, but mostorganizations cannot deliver one across all channels. Such organizations are often viewed asproviding an inferior experience.

■

Multiple ways exist to personalize a customer's experience in the physical and digital worlds. Thatthese two worlds are converging makes personalization even more challenging — and moredesirable for customers.

■

Most organizations have little knowledge or expertise on how to execute a successful digitalpersonalization strategy. They struggle with identifying the right set of metrics to measure positiveoutcomes.

■



Recommendations

Partnering with marketing, sales and customer service counterparts, application leaders responsible

for supporting customer experience and digital commerce technologies should lead the organization

to deliver more-personalized experiences to customers. They must:

IntroductionIn today's era of digital transformation, the methods of customer engagement have completely

changed. If organizations want to attract and retain their customers, they must first realize that they

can no longer compete on products or price — customers can now get the same or a similar product

at similar prices from multiple suppliers. The new competitive battlefield is the customer experience,

which translates into delivering a superior experience to those of your competitors (see "Customer

Experience Is the New Competitive Battlefield").

A crucial part of the overall customer life cycle is making the customer buying journey easier and

more fulfilling. This is done by recognizing customers across channels, knowing customers well and

identifying their needs as early as possible in their journey. Sellers must provide experiences tailored

to each individual customer by proactively identifying each customer's unique preferences, needs,

context and motivations, in order to serve content that resonates not only in digital stores but in other

channels (see Figures 1 and 2).

Personalization engines use multiple types of analytics and data in their analysis to identify content

or actions that will resonate with customers. (See Note 1 for an explanation of digital personalization

engines.)

Gartner Definitions

Personalization is a process that creates a relevant, individualized interaction between two parties

designed to enhance the experience of the recipient. It uses insight based on the recipient's personal

data, as well as behavioral data about the actions of similar individuals to deliver an experience to meet

specific needs and preferences.

Work toward incorporating Gartner's six mainstream approaches to personalization across the

different, appropriate channels.

■

Analyze and improve customer-facing processes and touchpoints to create a solid foundation for

starting your organization's personalization journey.

■

Build or utilize a digital personalization engine for commerce to best personalize digital customer

experiences.

■

Deploy and monitor metrics for personalization and work to continually improve customers'

experiences.

■



Personalization engines are technology solutions that identify the optimum experience for an individual

and will alter the online presentation layer, trigger an automated response, or pass analysis to the seller

or service personnel to act on as deemed fit.

Analysis

Incorporate Gartner's Six Mainstream Approaches to Personalization AcrossAppropriate Channels

There are six mainstream approaches to personalization that an organization can incorporate into its

customer experience portfolio. The approaches vary based on differing degrees of information that

the brand has about the buyer. In some cases, personalization can be delivered by digital platform

offerings, business rules, existing customer data and settings. In other instances, personalization is

based on what other customers have done.

Ideally, personalization is based on what a brand knows specifically about a customer. The greater that

knowledge, the more powerful the personalization becomes.

The six different personalization approaches are intertwined. Some also have more impact than

others. Figure 1 identifies the six types, indicates the relationship among them (indicated by

adjacency) and shows the estimated impact of the personalization on the customer (based on the

size of the box indicating the approach).

Figure 1. The Six Approaches to Personalization Are Intertwined and Vary in Impact



Source: Gartner (December 2017)

These six approaches have different degrees of complexity. In isolation, they represent stepping

stones to one-to-one personalization (see Figure 3 for the steps and progression of personalization).

Below we discuss them in more detail.

Six Approaches to Personalization

1. Digital commerce platform buyer preferences. Customers can express preferences in many ways

with an application. They can talk to a sales person about their sizes and color preferences, which

can then be entered into a clientelling application. They can set up preferences in a core banking or

billing system on preferred dates for a statement or when they wish to be billed. They can set up

preferences in supply chain applications for frequency of delivery and delivery dates.

With digital commerce platforms, customers can customize backgrounds and colors for their web

experiences as well as set alerts and notification preferences. Some of the most commonly used

personalization capacities allow customers to create wish lists, store commonly used data (payment

methods, shipping addresses, etc.) and select preferences for language, currency and click-and-

collect combinations. More specifically for business buyers, such platforms may include catalog



segmentation based on customer type, cost center and purchase hierarchy workflow, and the ability

to store templates for easy reordering.

Customers benefit from getting the customized user experience and improving their future user

experience by specifying preferences.

An extensive list of digital commerce platform providers can be found in "The Gartner Digital

Commerce Vendor Guide, 2017."

2. Channel and communication preferences. When given the choice, customers often explicitly

identify their channel and communication preferences for communicating with the seller or provider.

While traditionally used more for customer-service-oriented applications, these preferences are also

now being used for various types of digital commerce (e.g., order updates, new arrivals, sales) as well

as marketing applications (e.g., promotions).

The benefit to the customer is that they receive communications from sellers and providers only to

suit their interests, when they want them and in their preferred channel. In other cases, such as when

the customer is anonymous or no preferences have been identified, the seller or provider may infer

buyer preferences based on prior behavior, to improve the interaction experience. These settings may

reside in digital commerce platforms, contact center software, CRM systems and other customer-

facing applications.

An extensive list of digital commerce platform providers can be found in "The Gartner Digital

Commerce Vendor Guide, 2017."

3. Product affiliations. A more personalized experience can be delivered by identifying and tagging

products with dependencies, those commonly purchased together or those related to products

already purchased by the customer.

Products with dependencies: Sellers associate products that have a reliance on one another to

prevent issues that can be associated with purchase. Examples include showing batteries with a

child's toy that requires them or displaying a machine part along with the special tool required to

install it. In both of these cases, the buyer is looking to solve a problem — purchasing a gift for a

child that can be played with straightaway, or fixing a mechanical issue with the right piece of

machinery. By identifying product dependencies, the seller is preventing an unexpected problem

for the buyer (i.e., toy not working or inability to install the necessary part to fix the machinery).

Because a potential problem has been thwarted, the experience feels more personalized.

■

Products commonly purchased together: Use of analytics and especially AI can help to identify

items most commonly purchased together by past customers (often exemplified through the

familiar phrase, "Customers who purchased this also purchased…"). This capability may reside in

stand-alone analytics packages using AI or personalization engines, which package multiple types

of analytics for personalization purposes. By analyzing the behaviors of past shoppers, these

■



4. Location. Knowing the customer's location can have a large impact on personalization. Inferences

can be made from IP addresses, physical addresses, and the date and time. Geolocations are

especially useful in merchandise display and the personalization of marketing messages. For

example, if a customer is in the Midwest, where a snow storm is headed, snow boots and snow

shovels could be a good option for the top banner in the page. Mobile apps for in-store service are on

the rise. They are being used to improve the shopping experience while in-store, with beacons alerting

a store to a known customer's arrival. IP addresses are typically used for both known and anonymous

customers, whereas mobile apps are more typically used for known customers, because customers

have to sign in and authenticate information.

Customers benefit from being informed in real time about products more likely to appeal to them

based on their location, as tracked through the mobile app. They can receive offers of interest from

stores nearby.

5. Content. Signals from big data analysis, multiple types of analytics, past and present customer

behaviors, and data from other sources are used to analyze and segment customers. They can help

identify customers' intent as well as the content that will most resonate with them. They help shift the

seller-customer relationship of one-to-all to one-to-many or one-to-few — both offering greater

degrees of personalization. Content may be in the form of search results, landing pages, product

information, marketing offers, product promotions or other items of interest. Customers benefit from

being shown products, services or content that are most likely to resonate with them and that will

make them more efficient in their purchase journey.

6. Customer knowledge. While gaining a complete view of the customer is the most powerful source

of data for personalizing the customer experience, it is also the most complex due to the collection

and maintenance of the required data. It requires information well beyond typical descriptive data

technologies are able to identify correlations that may not be readily recognizable by the human

eye or intuitively obvious. For example, a search on "black dress" may actually mean a cocktail

dress, evidenced by such searches commonly resulting in purchases of black cocktail dresses. A

search on "gloves" may mean gloves for the whole family, because it most commonly results in a

purchase of gloves for men, women and children. Therefore, by extending the search results to

such items, the search experience could feel more personalized.

Products related to those already owned: Many B2B solutions are designed to be additive to other

third-party products that a customer has already purchased — for example, a product that extends

the capability of an existing product or a service providing long-term maintenance for ERP

software. In the case of technology products, this information can be identified through

technographic data sources. Other similar data sources exist for other industries. In addition to

personalizing the experience for add-on solutions, this approach can be used to run "competitive

take-out" campaigns to replace that solution.

■



such as demographics and transaction history. It requires knowing their preferences — favorite

brands, frequented events, most-liked sales associates, most-used products. It requires knowing their

interests and hobbies, family relationships, opinions, attitudes and social circle (though the latter

depends on their aptitude for social networks).

The Internet of Things (IoT) introduces new sources of data for both the customer and the

customer's product(s) being used. All this information can be captured in a CRM system, where a

detailed customer profile can be maintained to enable a complete 360-degree view. This profile can

be used for effective segmentation, loyalty management, campaigns and offers. Going beyond this

knowledge and doing more behavioral-based segmentation requires advanced analytics. This will

enable organizations to understand their customers' personas and motivators, which is also essential

for crafting effective personalization strategies (see "Powering Customer Experience With the

Trusted 360-Degree View").

Customer Engagement Channels

These six approaches are best used in combination to support an enterprisewide personalization

strategy, driving personalization across the different customer engagement channels. Organizations

should embark on this cross-channel journey only once they have laid a sound foundation of

delivering personalization by using a combination of the approaches. Figure 2 shows how an

organization can leverage the different customer engagement channels to drive personalization.

Figure 2. How to Use Different Channels to Drive Personalization




Figure 2 shows where an organization can deploy its cross-channel personalization, and what kind of

personalized content and offers can be presented to customers. It is highly recommended that an

organization explore cross-channel personalization options only after having augmented its

personalization strategy on its website. This is because website personalization will allow an

organization to understand online customer behavior and segment its customers based on the data

captured. Once the organization has augmented its customer segments based on analytics, it will be

easier to send personalized messages through emails, mobile messages and physical stores.

It is also of utmost importance to lay the groundwork for capturing cross-channel analytics. This will

help the organization to plan for the next phase of personalization strategy by measuring the



performance of each specific channel.

Improve Customer-Facing Processes and Touchpoints to Create a Solid Foundationfor Personalization

Personalization is a journey that requires organizations to have a customer-centric view. It begins by

giving due consideration to customer-facing processes and customer touchpoints (human and

technology-based) as well as understanding customer preferences.

Figure 3. Personalization Enriches Customer Experience by Knowing a Customer's Interests, Historyand Intent


Personalization must reside on a firm foundation of well-designed processes and navigation. These

must be consistently implemented across customer touchpoints and deliver a consistent, high-



quality experience to all recipients, regardless of channel. Incorporating personalization on poorly

designed processes without intuitive navigation or consistent customer experiences will not be nearly

as effective as personalization delivered on a solid foundation for the customer experience.

A best practice is to assess customer-facing process for efficiency, evaluate technology interfaces

for intuitiveness and ease of use, and establish standards for human engagement.

While many organizations may embark on a re-engineering exercise in order to streamline their

customer-facing processes, this does not mean that a large re-engineering exercise is always

required. Usually, re-engineering should be considered for only those processes that have a lot of

redundancy and inefficiency. Sometimes processes that receive a high number of customer

complaints can be good candidates for re-engineering as well.

Below are some examples of how the customer-facing process can be improved to drive

personalization:

Once your personalization strategy gains in maturity, your organization can also plan to include

specific calls to action on your websites as a part of the personalization strategy. This will ensure

that specific customer engagement can be built to enhance the customer experience.

Moreover, in a B2B scenario, an organization can build a persona of a buyer or a customer and then

can present specific content based on this persona. For example, if through firmographic information

A vacation resort could present a different customer-facing experience to different customer

segments. A vacation resort that has segmented its customers based on demographic and

behavioral information can provide different customer-facing experiences. The website for the

vacation resort would be the same, but the content and experience could be personalized based on

the segment to which any customer belongs. In this way, the resort can successfully position itself

as a destination of choice for a college student, a business traveler and a retired individual looking

for a luxury vacation, by surfacing the appropriate content and experience.

■

A software provider could present different products and services based on installed

technologies, industry or location. Many B2B companies have adopted account-based marketing

(ABM) as their primary go-to-market model. A software manufacturer mainly catering to the B2B

segments could provide a personalized experience to a prospect by using a range of different

information, including technographics (one to many), industry or location (one to few) or even at

the individual account level. For example, if a new prospect is coming from Germany, its website

should ask the prospect whether he would like to navigate in German or English. It could show only

the products and services available in that particular region. It could also provide information on

some local events scheduled in the region, which could be attended to gain more insights on the

product offerings. Personalization could also be achieved by knowing the prospect's industry,

related content to which could then be delivered.

■



a buyer specifies that she is a procurement manager in an IT organization, then content can be

tailored and personalized based on the role to match her needs whenever she visits the website.

By incorporating these aspects into reimagining the customer-facing processes and customer

journeys, an organization can build a strong foundation for building a successful personalization

strategy.

Build or Utilize a Digital Personalization Engine for Commerce

Application leaders must utilize a digital personalization engine for commerce, either acquired or

developed, to better personalize the customer experience.

Gartner Definition

Digital personalization engines for commerce integrate to one or more digital commerce platforms, or

to alternative technologies used for selling (web content management, portals, etc.). These engines

have moved beyond basic customer segmentation to continuous real-time session activity based on

customer interaction. They make presentation-layer changes for a specific customer with every

customer click stroke, based upon their persona or profile.

A personalization engine for commerce most commonly has the following attributes:

Data gathering at an individual level. It gathers detailed data about anonymous or known

customers from a variety of sources. These include on-site session data, explicit profile data,

historical transaction data, browsing data, geolocation data and external data. It serves as a data

hub for customer information.

■

Customer profile creation with real-time updates. It creates profiles for both anonymous visitors

and known customers. Each profile is managed within the personalization engine and is

continually updated in real time.

■

An assembled set of analytics. It prepackages multiple types of analytics. These include rule-

based (i.e., customer-defined) analytics, behavior-based segmentation, product-based

segmentation, predicted lifetime value, likelihood to engage/buy, collaborative filtering, text

analytics, machine learning or adaptive learning, and proprietary algorithms.

■

Identifies customer journeys and corresponds appropriately. It identifies where a customer in her

path to purchase and corresponds appropriately with personalization contingent based on the

journey.

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Ability to make real-time presentation-layer changes. It acts on the analysis and continually

changes the presentation layer content on a web or mobile site, providing the most relevant

■



Figure 4 is a graphical representation of a personalization engine.

Figure 4. What Constitutes a Personalization Engine

BPO = business process outsourcing; IoT = Internet of Things; IVR = interactive voice response; MDM = master data management; POS =point of sale


Deploy and Monitor Metrics for Personalization

Organizations that have already planned their holistic customer personalization strategy — and have

achieved positive results based on the initial testing — need to ensure that they carefully plan and

deploy successful metrics. These metrics will enable them to measure the response and success of

the personalization program. These metrics will help not only track the organization on how its

personalization strategy is paying off, but also determine what other personalization use cases and

channels the organization should plan to include in its strategy.

content based on its understanding of the customer's current intent and need. Presentation-layer

changes can occur in the following digital experiences: search results, landing pages, product

offers, product categories, facets and filters, and product recommendations. They include both

product and creative content changes

Capacity to attribute results. Many of today's engines measure and attribute revenue lift,

engagement lift (number of products viewed, time on site, etc.), conversion rate lift and size of

basket increases.

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Successful organizations clearly define these metrics during their initial stages of deployment of the

personalization strategy. As the organization starts developing a more holistic and cross-channel

approach toward personalization, it can introduce additional metrics to measure the outcomes and

fine-tune the execution strategy in case of any pitfalls. The application leaders responsible for

customer experience must closely align with their digital commerce and marketing counterparts in

order to plan and introduce these metrics. This cross-functional collaboration ensures that clear-cut

goals and benchmarks are set to measure the outcomes, and supports a more holistic cross-

departmental approach toward personalization.

Figure 5 shows four areas of key metrics that an organization can plan to deploy during the complete

implementation of the personalization strategy.

Figure 5. Clearly Define Metrics Across Four Areas During Initial Implementation


These are a list of sample metrics that an organization can consider to deploy. These could support

and measure KPIs in the four areas of call to action, trust, revenue and brand engagement. Once the

personalization strategy is extended to other customer engagement channels, more metrics can be



planned and deployed to measure the outcomes (see also "How to Manage Digital Commerce

Metrics" and "How to Manage Customer Experience Metrics").

It is also important to align the metrics of personalization with the business success metrics or KPIs.

This will enable the organization to measure whether personalization is increasing the effectiveness

of marketing and commerce toward achieving the desired business objectives. Ideally, this linkage

should be done when an organization is in a position to holistically drive personalization across the

appropriate channels.

Note 1Digital Personalization EnginesDigital personalization engines typically incorporate multiple types of analytics and data in their

analysis.

The most common analytics being used are:

Some vendors are starting to incorporate predictive analytics and adaptive learning or machine

learning analytics as well. Other types of analytics that may be used include but are not limited to

anomaly detection, decision tree, attribution, correlations, margin optimizing routines, offer

optimization, customer life cycle review, content life cycle, channel aggregation and churn propensity.

All engines incorporate implicit, explicit, profile and session data. In addition to the most commonly

used data types (i.e., customer and transactional), most vendors are starting to incorporate other

types such as social, geolocation, third-party (i.e., Speedeon, Experian, BlueKai, Axcion), government

(citizen and business), weather and economic data.

Recommended by the Authors

Rule-based (i.e., customer-defined) analytics■

Behavior-based segmentation■

Product-based segmentation■

Predicted lifetime value■

Likelihood to engage■

Likelihood to buy■

Collaborative filtering■

Text analytics■



The Gartner Digital Commerce Vendor Guide, 2017

The Gartner CRM Vendor Guide, 2017

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