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Analytics And Automation
Anchor A Future Fit
Experience Architecture
Vision: The Digital Experience Delivery Playbook
February 12, 2021
By Nick Barber, Allen Bonde with Stephen Powers, Ted Schadler, Kara Wilson, Madison
Bakalar
Summary
Creating high-impact, scalable digital experiences is a key milestone to digital
transformation. Yet, doing it more efficiently separates winning strategies from the
manually intensive. Time-to-market is even more important as firms return to growth postCOVID-19. This report outlines our vision for the growing role of digital experience (DX)
delivery teams and tech and explains why building around a standard architecture is
imperative and how analytics and automation (and data) are core to delivering everyday
value when fully harnessed by application development and delivery (AD&D) pros and
creatives. This is an update of a previously published report; Forrester reviews and
updates it periodically for continued relevance and accuracy.
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A STANDARD ARCHITECTURE DRIVES SPEED AND SCALE
We've promoted the value of building around standard, yet flexible, DX architecture for
several years. Until COVID-19 created a sense of urgency and clarity for many firms, this
platform vision was elusive for many enterprises. (see endnote 1) Finding a balance
between scale (supporting a large volume of customers, new market segments, etc.)
and impact (driving personal connections with each to build a brand connection, word
of mouth, loyalty, etc.) is one of the classic challenges of digital business. The best way
to stand up to these challenges remains a federated approach to centralize strategy
and architecture, but also distributed contextual engagement. (see endnote 2)
With the desire to move faster and adapt to new market opportunities and challenges,
the importance of building around platforms, shared practices, and reimagined
partnerships has moved to the forefront. (see endnote 3) And while digital needs vary
widely (e.g., by business unit or digital maturity), the scale of experiences demands
more content to boost engagement, more customer data for relevance, and more
transactions to enable self-service and unlock value. Enterprises need a common way
to express the foundations, building blocks, and services to deliver the right mix of
experiences to the right channel and the right audience. They need a model like our
"DX stack" to build around and spread the vision to techies and creatives alike (see
Figure 1). This approach also requires AD&D leaders to create new alliances and be
comfortable with:
• Relinquishing some digital operational control. By design, this architecture must
enable new (or currently separate) teams that don't yet share this vision to step in
and operate channels, campaigns, and even some aspects of development. While
some teams saw DX delivery as the opportunity to "bring everything onto a
common platform," we now know this doesn't scale. The new vision is to "align
against a common operating model built on shared services." Specifically, DX as a
discipline will be the steward of shared experience services: customer data,
content, and transactions.
• Evangelizing the benefits of lighter governance and standards. Some DX teams
have already forgone much of the daily operations, which is arguably a mature
approach, but this can leave them to mentor the broader organization on good
practices and the benefits of shared accountability. Instead of managing down to
the nth level of detail, a DX governance model should be outcomes based and built
on shared goals (and trust!). And by also leaving the door open to evolve, this
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reference model approach will fold distributed learnings back into the core model.
This is digital innovation by another name.
Figure 1: The DX Stack Provides A Blueprint For Assembling Experiences
Start Small; Grow From Project To Program
To move fast, you must focus. Forrester is seeing increasing evidence that digital
experience initiatives must start small in scope but broad in endorsement (e.g.,
executive sponsorship and nontechnical practitioners). Success will breed confidence
and unlock budgets, which means that DX teams may have the chance to remake the
broader organization. A North American wireless carrier created a 30-person digital lab,
which scaled to over 500 people in three years. Now this organization can help its
entire 8,000-person technology organization shift to a new, agile architectural strategy
by supporting a small number of reference patterns:
"Our digital platform is the core, but we recognize that it doesn't suit every scenario as
we scale out to support more of the business. We're going to use it to build four types
of software (with starter kits) across: 1) static websites — great for standards,
performance, accessibility, SEO — we'll use these for ‘research and learn, or campaign
pages'; 2) dynamic web applications — those that ingest multiple APIs (e.g., billing data);
3) mobile apps; and 4) APIs and integrations and microservices." (Head of product,
North American wireless carrier)
TO BE ADAPTIVE, DATA MUST BE CORE TO THE DX STACK
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We see this approach being adopted by a widening circle of teams, from marketing to
agencies and even customer support functions. (see endnote 4) With more experiences
and more diversity in users and creators, data becomes the by-product and the fuel to
move faster. As firms look to build less and create economies of scale through shared
services and innovation through ecosystems, there's a ready audience for modern,
customer-facing platforms that not only deliver and orchestrate all types of
experiences, but also work in tandem with back-office digital operations platforms. (see
endnote 5) Our definition of a DX platform is:
A digital experience platform provides the architectural foundation for flexible, agnostic
core services to maximize scale, quality, and insights across channels and systems,
while delivering context-specific tooling for practitioners to build, manage, and
optimize digital journeys on "owned" channels (web, mobile, messaging) and
orchestrate third-party experiences (e.g., social, retail marketplaces).
Data Is Core To How We Understand And (Ultimately) Respond To Customer Needs
Digital interactions leave a trail of data artifacts, and the opportunity to turn big and
small data sets into nuggets of knowledge is the modern-day alchemy. Blending
different data types and sources drives new insights — and increasingly paves the path
to automation as well. Four data "flavors" are transforming the way software vendors
and enterprise customers are investing in the DX vision:
1. Customer data to engage contextually. An enriched customer profile that includes
behavior, transaction history, and preferences from omnichannel experiences is the
new North Star. By cross-referencing this profile with contextual data, brands and
enterprises aim to unlock real one-to-one engagement. We continue to see platform
providers investing in both core customer data platforms and new personalization
capabilities given this potential (see the Salesforce-Evergage and SAP-Emarsys deals
for two examples), solidifying the role of profiles at the core of DX models. (see
endnote 6) However, the issues of data quality, governance, and compliance continue
to demand attention, especially as privacy regulation remains a hot topic. (see endnote
7)
2. Content metadata to create a 360-degree view of relevant assets. Brands tend to
know a lot about their customers, but less about their content. (see endnote 8)
Unstructured content (e.g., images, video, PDFs, app content) is often managed as a
static file. But running text, images, and video through AI surfaces additional
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understanding about the content, user sentiment, and even face and product
identifications. Many digital asset management (DAM), content management systems
(CMS), and product information management (PIM) systems have embedded
AI/machine learning (ML) capabilities to shine a light on this "dark" data and allow it to
be discovered (e.g., search) and tracked (e.g., analytics). (see endnote 9)
3. Transactional data to serve as the path to self-service and thus loyalty. Tracking
purchases, orders, trades, claims, and service tickets are essential to growing your
customers' ability to self-serve, which is tied to loyalty. (see endnote 10) Connecting,
analyzing, and correlating transactions across channels and functions inside the
business can reduce friction and help with upsell and cross-sell, increasing the lifetime
value of a customer. As newer channels like marketplaces account for a growing share
of consumer and even B2B transactions, we see new ways to collect and monetize this
transaction insight. (see endnote 11)
4. Real-time triggers to automate the next step in the journey. Event-driven
integration was common back in the days of mainframes, but in a heavily distributed
computing world, it becomes orders of magnitude harder. Enabled by new
technologies like Kafka data processing, event listening — triggered by a state change
— can kick off the next-best experience with no manual intervention. With open source
now mainstream, we see the goal of processing real-time inputs and generating realtime responses across nearly any channel or audience becoming a reality. (see
endnote 12)
AI FILLS OPERATIONAL GAPS WITH A SENSE-ADAPT PARADIGM OF
AUTOMATION
AI and ML will allow organizations to harness these newfound data assets and start to
automate experiences. Even if your organization is not ready to turn on experience
"autopilot" due to inherent brand risk, it's wise to understand the primary dynamic of AI
approaches as the ability to pair "sense" and "adapt" capabilities (see Figure 2). This
paradigm animates the analytics and automation pillars that bookend our DX stack and
is core to scaling up the adoption and economic impact of DX investments. Forrester
believes four AI/ML use cases will be transformative for the future of digital experience
delivery:
1. Embedded AI to automate operational tasks. These bots improve practitioners' daily
tasks through AI-enabled capabilities or attended robotic process automation (RPA)
typically delivered in the form of embedded functions with an app. The time-to-value is
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typically quick by accelerating and improving the quality of highly repetitive operational
tasks. One large retailer we spoke with told us how these AI "helper bots" within Adobe
Creative Cloud software saves his team a few minutes here and there, but when they
scale across thousands of operations and hundreds of team members, the efficiency
and ROI begins to add up quickly.
2. AI to automate engagement decisions. Whole new subcategories of a traditional
offering have sprung up around engagement automation (e.g., testing and targeting
into a recommendation engine). These modules or products promise to boost DX
performance metrics within a domain (e.g., average order value for e-commerce). Timeto-value is typically on the order of a few weeks or months when machine learning is
involved, as the system must collect enough data to feed the algorithm.
3. AI at scale to automate cross-domain journeys. Multichannel and multiphase
customer journeys are inherently challenging to automate. However, within a vertical,
there are opportunities to leverage best practices that guide a broader value
proposition (e.g., lifetime value of a customer). Simulation and modeling approaches
along with AI may be used to create, in effect, a digital twin for a particular buyer's
journey and set of personas. Time-to-value is drawn out by the extent of the number of
processes and business units that must change, commonly running into multiple
quarters.
4. Machine learning to detect patterns and feed operational insights. Customer,
content, and transactional data sets are massive by themselves. Taken together, it's
simply impossible for humans to curate the data, analyze the patterns, and determine
the optimal response. Data science techniques like machine learning have long been
touted as a means to sift through this data, and so the value promise is extremely high.
Yet even as tools have become widely available, these approaches often require
extensive training and even the hiring of high-cost data scientists, thus limiting quick
time-to-value.
Figure 2: Automation Requires Both The "Sense" And The "Adapt" Phases Of
Technology
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RECOMMENDATIONS
Look To Innovate At The Intersection Of Experiences And Operations
If your enterprise moved quickly to solve for a narrow slice of DX (e.g., all public-facing
marketing websites) then you may have invested in a new stack and a new operating
model. However, needs change. If you were now asked to support outbound
messaging, the operating model may break. Therefore, AD&D leaders must establish a
path to a future fit strategy and:
• Unlock insights by blending content, customer, and transactional data sets.
Migrating all data into a single repository is an old-world approach. However,
metadata standardization combined with improved search and visualization should
provide the means to stitch the data services together. This new data fabric will
begin to support faster, better, and cheaper experiences through reuse, error
reduction, and streamlined effort.
• Start to pave the path to automation. AD&D leaders must partner with creative
practitioners to look for opportunities to "get smarter" in their everyday work.
Embedded AI and smart bots can help by streamlining frequent activities that digital
designers, content creators, and merchandisers perform, as well as providing
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guidance for tagging, targeting, and even message testing. The good news is that
top vendors are baking more helper bots into their digital experience platforms and
popular add-ons.
WHAT IT MEANS
You're Not Going To Win With DX, But You Can't Compete Without It
To understand where digital experience is going, look to the retail sector. For nearly
two decades, online commerce has been the test bed for experimenting with ways to
deliver smarter search or targeted offers. However, in the past five years, online
marketplaces like Alibaba and Amazon have focused on delivering a massive
assortment of products through simple interfaces and rapid delivery. Yet other specialty
retailers thrive by delivering compelling digital-meets-physical experiences and
cultivating brand loyalists. Leaders across all industries should understand three new
realties impacting this phenomenon that will determine their own fate:
• AI accelerates digital sameness. When you build around a common model, add on
the know-how from the worlds of advertising technology and database marketing to
the mix and blend in the full potential of AI, and core DX efforts are likely to move
far beyond operational improvement into all aspects of design and omnichannel
customer experience (CX). This is where some top vendors are already headed,
when you review the strategies and recent forums hosted by top vendors like
Adobe, Episerver, Oracle, and SAP. As a result, more know-how is baked into
software. And everyone gets those benefits.
• Platforms democratize algorithms, apps, and skills. Data-driven optimization will
upset the balance of "suite" versus independent vendors. Suite vendors will gain
new ammunition in their skirmishes with (headless) upstarts even as headless
providers join forces through efforts like MACH Alliance. (see endnote 13) Standard
architectures mean that upstarts have more ways to pivot and find new places to
plug in. More importantly, as adoption across enterprises spreads, AI-powered
processes will become table stakes instead of differentiators, and brand and loyalty
will reenter the picture as the means to avoid the fate of digital sameness. (see
endnote 14)
• DX success metrics will pivot to operational objectives. Forrester's Customer
Experience Index (CX Index™) research shows that digital experiences don't
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correlate with loyalty, but bad experiences do hurt loyalty. (see endnote 15) This
leaves DX leaders looking for new success metrics to latch onto. The motivation to
"prevent brand injury and keep operations efficient" should be a good fit for many
digital leaders, but it's a poor label! Instead, we propose that DX leaders embrace
measurement frameworks like objectives and key results (OKRs) to tie into wellunderstood company-level goals, while optimizing how their experience efforts
support them. (see endnote 16)
SUPPLEMENTAL MATERIAL
Companies Interviewed For This Report
We would like to thank the individuals from the following companies who generously
gave their time during the research for this report.
• Adobe
• Epsilon
• Evergage
• GroupBy
• HUGE
• IBM
• Naehas
• OpenText
• Publicis Sapient
• Salesforce
• TCS
Related Research Documents
• Assess Your Digital Experience Delivery Maturity
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• The Forrester Wave™: Digital Experience Platforms, Q3 2019
• Speak The Same Language To Harmonize Martech And Digital Experience
Initiatives
Endnotes
1. See the Forrester report "The Pandemic Recession Demands A Digital Response."
2. See the Forrester report "How Federated Digital Teams Drive Pace At Scale."
3. See the Forrester report "Your Future Fit Technology Strategy: Adaptive, Creative,
And Resilient."
4. See the Forrester report "Speak The Same Language To Harmonize Martech And
Digital Experience Initiatives."
5. See the Forrester report "Look Beyond ERP: Introducing The DOP."
6. Source: "Salesforce Acquires Evergage, Will Use Personalization to Enhance
Customer Data and Deliver More Relevant Experiences," PR Newswire, February 7,
2020 (https://www.prnewswire.com/news-releases/salesforce-acquires-evergagewill-use-personalization-to-enhance-customer-data-and-deliver-more-relevantexperiences-301000691.html) and "SAP to Acquire Omnichannel Customer
Engagement Leader Emarsys," SAP Press Release, October 1, 2020
(https://news.sap.com/2020/10/sap-to-acquire-emarsys/).
7. Source: "Privacy Regulation Is (Still) Hot," Forrester
(https://www.forrester.com/fn/2ShI5j352V6qsISo8Jl8nk).
8. See the Forrester report "There's No Personalization Without Content
Intelligence."
9. See the Forrester report "PIM And DAM Are The Power Couple For Your Content
Strategy."
10. Ease and effectiveness are two of the three elements that correlate growth with
loyalty. See the Forrester report "Advance Your Approach To Customer Loyalty."
11. See the Forrester report "Research Overview: Online Marketplaces."
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12. See the Forrester report "DataOps For The Intelligent Edge Of Business."
13. Source: "Digital Experience FAQ: Do I Need To Move To Headless Commerce?"
Forrester (https://www.forrester.com/fn/dvrYIEoIAOVLWSYgpsON4).
14. See the Forrester report "Desperate For Differentiation: Creativity Galvanizes The
Total Brand Experience."
15. Source: Harley Manning, "Change The Game: Leading Radical CX Innovation,"
Forrester's CX Forum 2019 (https://go.forrester.com/event/cx-nyc/forum-materials/).
16. Source: "Visualize Your Transformation Scenarios And The Objectives And Key
Results (OKRs) Behind Them," Forrester
(https://www.forrester.com/fn/66zcwKOPHheHCFUX1qnRV5).
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