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9/14/2020 Use Personalization to Enrich Customer Experience and Drive Revenue
https://www.gartner.com/document/3839665?ref=authrightrec&refval=3902905 1/15
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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.
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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.
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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.
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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.
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Analyze and improve customer-facing processes and touchpoints to create a solid foundation for
starting your organization's personalization journey.
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Build or utilize a digital personalization engine for commerce to best personalize digital customer
experiences.
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Deploy and monitor metrics for personalization and work to continually improve customers'
experiences.
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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
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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
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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.
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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
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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.
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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
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Source: Gartner (December 2017)
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
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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
Source: Gartner (December 2017)
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-
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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.
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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.
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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.
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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
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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
Source: Gartner (December 2017)
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
Source: Gartner (December 2017)
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
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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■
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The Gartner Digital Commerce Vendor Guide, 2017
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