Gartner Hype Cycle for CRM 2019
CRM revenue in 2018 is comprised of software and services revenue from Customer Service and Support (36%), Sales (26%), Marketing (25%), and Digital Commerce (13%)- these 4 categories together comprise the customer experience and relationship management market, according to Gartner.
Global enterprise application software revenue totaled more than $194B in 2018, a 13% increase from 2017.
CRM made up nearly 25% of the entire enterprise software revenue market.
73% of CRM spending was on software as a service (SaaS) in 2018, which is expected to grow to 75% of total CRM software spending in 2019.
Global spending on customer experience and relationship management (CRM) software grew 16%, from $42B in 2017 to $48B in 2018, and is projected to reach $55B in 2019.
Salesforce dominated the worldwide CRM market with a 20% market share in 2018, over double its nearest rival, SAP, at 8% share.
Magic Quadrant for Field Service Management
Vendors’ positions in this Magic Quadrant reflect customers’ new expectations in areas such as digital technician support, outcome-based service business models, and AI-driven scheduling and decision support.
When assessing vendors, look for packaging of multiple technologies and proven results.
Gartner Hype Cycle For AI
Between 2018 and 2019, organizations that have deployed artificial intelligence (AI) grew from 4% to 14%, according to Gartner’s 2019 CIO Agenda survey
Conversational AI remains at the top of corporate agendas spurred by the worldwide success of Amazon Alexa, Google Assistant, and others
Enterprises are making progress with AI as it grows more widespread, and they’re also making more mistakes that contribute to their accelerating learning curve
KEY AI TRENDS
- Gartner research reveals that between 2018 and 2019, organizations that have deployed artificial intelligence (AI) grew from 4% to 14%
- Conversational AI remains at the top of corporate agendas
- Enterprises are making progress with AI and they’re also making more mistakes that contribute to their accelerating learning curve.
Gartner Magic Quadrant for CRM Lead Management
Lead augmentation sources
Predictive lead scoring and analytics solutions
Online meeting and event solutions
In-person trade event systems
Third-party customer or list data
Gartner Hype Cycle for CRM Sales
The Gartner Hype Cycle offers a graphical depiction of a common pattern that arises with each new technology or other innovation — from hyped excitement through a period of disillusionment to an eventual understanding of the innovation’s relevance and role in a market or domain.
A Hype Cycle can help executives gauge relative risk and timing of emerging technologies and evaluate trade-offs between risk and innovation.
The Gartner Hype Cycle for CRM Sales, 2018, shows two main areas on the verge of mainstream adoption, suggesting a near-term need for investment in those sales innovations — predictive and prescriptive technology and application programming interface (API).
Gartner Hype Cycle for Digital Marketing and Advertising
Gartner’s latest Hype Cycle for Digital Marketing and Advertising 2019 Provides Insights on Prioritizing Marketing Technology Investments
Artificial intelligence (AI) for marketing, customer data platforms (CDPs) and real-time marketing are some of the technologies at the Peak of Inflated Expectations in digital marketing and advertising, according to Gartner.
Among the 28 technologies represented in the Gartner Hype Cycle for Digital Marketing and Advertising 2019, four technologies have the capability to transform how marketers run their technology ecosystems and, ultimately, deliver meaningful customer experiences.
Gartner Magic Quadrant for Personalization Engines
Personalization engine vendors are adapting to better meet the needs of marketing leaders–focusing solutions on methods to increase customer success, deepening customer data management functionality and expanding support for personalized customer experience.
Personalization Engines are defined as software that applies context about individual users to select, tailor and deliver messaging such as content, offers and other interactions through digital channels in support of three use cases: marketing, digital commerce and customer experience (CX).
The personalization process creates a relevant, individualized interaction between a company and its audiences to enhance the recipient’s experience. It uses insight based on unique recipient behavioral data, as well as behavioral data of similar individuals, to deliver an experience to meet specific needs and preferences. Personalization capabilities can be found in stand-alone personalization engine software or embedded in applications such as web content management, content marketing, multichannel marketing hubs and digital commerce.
This Magic Quadrant focuses solely on vendors that offer personalization engines as stand-alone solutions.
Marketers use personalization engines to customize digital commerce experiences across digital sales channels (such as web and mobile).
These experiences can include content, on-site search and navigation, and product recommendations.
Personalization engines also render, preview and trigger HTML blocks to personalize content and campaigns on non-commerce websites, and marketing and advertising channels, such as email, mobile, paid search and digital ads.
Many personalization engines enable marketers to use their content-rendering functionality to personalize CX by deploying surveys to gather user feedback.
They analyze feedback to segment and target users based on response. Vendors are expanding native ability and integrations to trigger personalized interactions across touch-points such as digital kiosks, clienteling applications and nondigital channels like call centers.
They also integrate first- and third-party data to score, segment, target users, model intent and behavior, and trigger tailored content, such as real-time contextual data like location, historical data like past transactions, and business intelligence data like inventory availability.
Vendors balance personalization and privacy by supporting General Data Protection Regulation (GDPR) compliance.
However, only half of vendors offer detailed explanations and examples of support, like separate processing of personally identifiable information (PII), or a user interface for marketers or consumers to retrieve or delete consumer data.
Forrester New Wave Cloud Content Platforms
The Forrester New WaveTM: Cloud Content Platforms — Multi-tenant SaaS, Q3 2019
Forrester’s research uncovered a market in which Box and Microsoft are Leaders; Google, dropbox, GrM information Management, fabasoft, aodocs, and Laserfiche are strong Performers; Citrix, M-files, and nuxeo are Contenders; and egnyte and openText are Challengers.
App Design Tools, AI, And Governance Capabilities Are Key Differentiators
Customers want the flexibility to tailor their content apps with design and development tools. Cloud content platforms must also provide governance and security capabilities to protect information and serve as systems of record. ai is driving rapid innovation across the vendor stack.
Agility and speed drive The Cloud Content Platform Market
Two markets have collided. Traditional enterprise content management (eCM) vendors are rearchitecting their platforms to be cloud native, while vendors with heritage in cloud enterprise file sync and share have pivoted to broader content repository services.
This market overlap has resulted in a new segment: cloud content platforms. new vendors, with purpose-built content platforms, have also joined this growing, competitive space. The pace of cloud adoption for content management continues to rise, and we expect that 33% of overall eCM revenue will be software-as-a-service (SaaS) in 2019.
Only 22% of global software decision makers describe their content management deployment as only on-premises.
However, there are many delivery models for cloud content services — hosted, private, hybrid, single-, or multi-tenant — and each offers its own advantages.
The multi-tenant cloud model offers specific characteristics that customers value.
Global software decision makers report that when they adopted SaaS, they achieved benefits including better business agility, automated delivery of features and fixes, deployment speed, and cost reduction
Gartner Hype Cycle for Emerging Technologies, 2018`
Widespread artificial intelligence, biohacking, new platforms and immersive experiences dominate Gartner Hype Cycle for Emerging Technologies
5 Trends Emerge in the Gartner Hype Cycle for Emerging Technologies, 2018
Democratized artificial intelligence (AI), digitalized ecosystems, do-it-yourself biohacking, transparently immersive experiences and ubiquitous infrastructure
Trend #1: Democratized AI
AI, one of the most disruptive classes of technologies, will become more widely available due to cloud computing, open source and the “maker” community.
Trend #2: Digitalized ecosystems
Emerging technologies in general will require support from new technical foundations and more dynamic ecosystems.
Trend #3: Do-it-yourself biohacking
2018 is just the beginning of a “trans-human” age where hacking biology and “extending” humans will increase in popularity and availability.
Trend #4: Transparently immersive experiences
Technology, such as that seen in smart workspaces, is increasingly human-centric, blurring the lines between people, businesses and things, and extending and enabling a smarter living, work and life experience.
Trend #5: Ubiquitous infrastructure
In general, infrastructure is no longer the key to strategic business goals. The appearance and growing popularity of cloud computing and the always-on, always-available, limitless infrastructure environment have changed the infrastructure landscape.
Gartner Magic Quadrant – Configure, Price & Quote Application Suites 2018
Leaders – Aptus, Salesforce, Oracle
Gartner Magic Quadrant – Multichannel Marketing Hubs 2018
Leaders – Adobe, SAS, Oracle, IBM, Salesforce, Marketo, SAP
Gartner Magic Quadrant – Sales Performance Management Magic Quadrant 2018
Leaders – Adobe, SAS, Oracle, IBM, Salesforce, Marketo, SAP
Gartner Magic Quadrant – CRM Customer Engagement Center 2018
Gartner Magic Quadrant for Public Cloud Infrastructure Managed Service Providers
Gartner Magic Quadrant – Analytics & Business Intelligence Platforms
Gartner 2018 Magic Quadrant – Sales Force Automation
Gartner Magic Quadrant for Digital Experience Platforms 2018
Gartner 2017 Magic Quadrant – CRM Customer Engagement Center
Gartner estimates that by 2019, over 85% of new packaged customer service and support software will be delivered on a cloud-based model
Gartner believes SaaS will emerge as an essential selection factor for CRM customer engagement centers
Salesforce, Pegasystems, Microsoft, Oracle and Zendesk are in hte upper righthand quadrant exhibiting vision and the a leader in the category based on traction
Go to Market Gartner Hype Cycle – Sales Force Automation (SFA)
Gartner Magic Quadrant for Digital Marketing Hubs
Digital Marketing Hubs provide a system that can integrate and coordinate data and activities across channels, devices and contexts, continuously and in real time.
Digital marketing hubs addresses 4 main areas:
Master Audience Profile
- Combining first-party, second-party and third-party data across known and anonymous customers and prospects for precision targeting and tracking of offers and experiences.
- A consistent view of customers (including anonymous ones) across marketing programs and processes is the baseline for effective communication.
Workflow & Collaboration
- Supporting marketing programs with core services through ideation, planning and monitoring of customer journeys and experience designs, internally and with partners.
- Uniform collaboration and workflow are keys to breaking down operational silos that result in disjointed, incoherent customer experiences.
- Driving the sequencing and coordination of engagement across channels.
- Specialized channel-specific execution is sometimes prudent, but consumers are engaging on their own terms, freely switching among channels and devices. Multichannel marketing programs need shared intelligence and automation to optimize each interaction in real time.
- However, a DMH is not a campaign management platform, since it is not directly concerned with channel execution but, rather, with coordination of data and content across campaigns and channels.
Unified Measurement & Optimization
- Tying investments to outcomes to optimize decisions to the highest yield. Unless marketing programs are measured by a common set of rules, marketers will squander resources and lose out to more efficient competitors.
- This is an area where DMHs may overlap with digital marketing analytics, although the focus of DMHs is on real-time operational applications of data rather than advanced analysis.
Magic Quadrant for Cloud Strategic Corporate Performance Management Solutions 2017
Strategic corporate performance management solutions support the office of finance’s efforts to manage organizational performance and strategy.
By 2020, at least 25% of organizations will achieve more collaborative, continuous and consistent financial planning and performance management by closely linking key operational and financial planning processes.
The strategic corporate performance management (SCPM) market is shifting from mature on-premises offerings to cloud solutions as finance application leaders seek to reduce application support costs, increase application flexibility and shorten the time to value.
New solutions built, or significantly re-architected as, cloud services are typically easier to use and maintain than the previous generation of on-premises offerings.
Go to Market Gartner Magic Quadrant – Sales Force Automation (SFA)
Gartner Magic Quadrant for Data Integration Tools 2017
Data management is gaining attention due to Big Data, Cloud, social, mobile, and IoT technologies.
Gartner believes that an enterprise cloud data management platform powered by artificial intelligence (AI) is critical to integrating all types of data for a variety of use-cases from big data analytics to real-time operations.
To be a leading data integration vendor, Gartner suggests that vendors must be able to manage small and big, unstructured and structured data, batch and real-time streaming, on-premises and cloud or hybrid deployments, and deliver trusted data in a self-service fashion to everyone from business analysts to citizen integrators.
A successful data management strategy should include big data and cloud data integration, data quality, integration hubs, data cataloging, real-time streaming, B2B integration, master data management, data governance, and data security.
Go to Market Gartner Magic Quadrant – BI & Analytics
Built-in data governance that balances empowerment with control
A Hyper-speed data engine to enable faster analysis on larger data volumes
Self-service data prep that lets you quickly transform data for analysis
Advanced analytics for everyone
Flexible hybrid deployments
Gartner 2017 Magic Quadrant for Data Science Platforms
IBM, SAS, RapidMiner, KNIME
MathWorks (new), Quest (formerly Dell), Alteryx, Angoss
Microsoft, H2O.ai (new), Dataiku (new), Domino Data Lab (new), Alpine Data
Niche Players (3)
FICO, SAP, Teradata (new)
Go to Market Gartner Magic Quadrant – Digital File Systems
Gartner Magic Quadrant for Data Management Solutions for Analytics
Market Accelerators: more demand for broad solutions that address multiple data types and offer distributed processing and repository and cloud solutions gaining traction.
Data management solutions for analytics manage and process internal and external data of diverse types in diverse formats, in combination with data from traditional internal sources (IoT, sound, images, video, etc.).
Cloud is an alternative deployment option, because of its flexibility, agility and operational pricing models – cloud and on-premises hybrid are quickly becoming the norm, so organizations expect vendors to support them in enabling such deployments.
Traditional data warehouse inquiries are now fewer than those for the logical data warehouse, according to Gartner.
Gartner defines a data management solution for analytics (DMSA) is defined as a complete software system that supports and manages data in one or many file management systems (most commonly a database or multiple databases).
Gartner Magic Quadrant for Enterprise Integration Platform as a Service 2017
- An integration platform as a service (iPaaS) provides capabilities to enable subscribers to implement data, application, API and process integration projects spanning cloud-resident and on-premises endpoints.
- This is achieved by developing, deploying, executing, managing and monitoring “integration flows” (aka “integration interfaces”) — that is, integration applications bridging between multiple endpoints so that they can work together.
- An iPaaS is typically used for cloud service integration (CSI) and application to application (A2A) integration scenarios.
- Increasingly, iPaaS is also being used for business to business (B2B) integration, mobile application integration (MAI), API publishing and Internet of Things (IoT) integration scenarios.
- Is designed to support enterprise-class integration projects (that is, projects requiring high availability, disaster recovery, security, service-level agreements [SLAs] and technical support from the provider)
- Can support several of the use cases mentioned above
Go to Market Gartner Hype Cycle – Emerging Technologies
3 distinct mega trends that will enable businesses to survive and thrive in the digital economy over the next five to 10 years:
- Artificial intelligence (AI) everywhere
- Transparently immersive experiences
- Digital platforms
Gartner believes that AI technologies will be the most disruptive class of technologies over the next 10 years based on:
- Computational power
- Near-endless amounts of data
- Unprecedented advances in deep neural networks
Transparently Immersive Experiences
Gartner believes that technology will continue to become more human-centric blurring the line of transparency between people, businesses and things. Transparently immersive experiences are expected to be entwined as the evolution of technology becomes:
- More adaptive
- Fluid within the workplace, at home, and in interacting with businesses and other people
Gartner expects emerging technologies to revolutionize the enabling foundations that provide the volume of data needed, advanced compute power, and ubiquity-enabling ecosystems. The shift from compartmentalized technical infrastructure to ecosystem-enabling platforms is predicted to establish the foundation for entirely new business models that are forming the bridge between humans and technology.
Go to Market Gartner Hype Cycle – Data Science
Go to Market Gartner Hype Cycles – Digital Marketing & Advertising
Gartner’s 2016 Hype Cycle for Digital Marketing and Advertising identifies 4 forces that are driving a data-centric future for marketers
As marketing technologies (Martech) and advertising technology (Adtech) converge, there are 4 forces that point to a data-centric future for marketers:
- Real-time marketing techniques
- The use of contextual clues
Go to Market Gartner Hype Cycles – The Key Technology Forces
Gartner believes that the convergence of Martech and Adtech create a growing dependence on data-driven strategies and tactics.
From a strategic point of view, Gartner believes that the convergence is the result of a continuing focus on delivering compelling and valued customer experiences, regardless of the market or the product or service. gartner points out that technologies such as data management platforms, marketing analytics, marketing automation and predictive analytics are increasingly shared in Martech and Adtech stacks.
Event-Triggered and Real-Time Marketing Techniques
Gartner believes that the drive to be able to react in the moment and move the customer or prospect along the path to purchase and advocacy puts the focus on mobile marketing and predictive analytics. This is especially true in B2C, especially retail.
Gartner points out that personalization and “personification” technology profiles are maturing at a rapid rate. This is driven by marketers as they look to create 1:1 opportunities while balancing consumer concerns about privacy and security.
Gartner presumes that the use of the contextual cues signaled by consumer and prospect usage of mobile devices — cues such as traffic conditions, appointments, the local weather, their presence near a mall or retail district — is driving marketers’ overall interest in proximity marketing, the Internet of Things and wearables.
Go to Market Gartner Hype Cycles – Emerging Technologies
The Go to Market Gartner Hype Cycles Special Report Distills Insight From More Than 2K Technologies
Gartner’s 2016 Hype Cycle for Emerging Technologies identifies 3 key trends that companies should track and manage to establish a competitive advantage. Specifically, Gartner believes that these technology trends are significant for organizations facing rapidly accelerating digital business innovation.
Go to Market Gartner Hype Cycles – 3 Overarching Technology Trends
- Transparently immersive experiences
- The perceptual smart machine age
- The platform revolution
Gartner believes these trends will create new experiences that allow organizations to connect with new business ecosystems.
Go to Market Gartner Hype Cycles – Transparently Immersive Experiences
Gartner believes this technology will continue to become more human-centric (transparency between people, businesses and things). This relationship will become much more entwined as the evolution of technology becomes more adaptive, contextual and fluid within the workplace, at home, and interacting with businesses and other people.
Transparently Immersive Experiences requires a number of technologies: 4D Printing, Brain-Computer Interface, Human Augmentation, Volumetric Displays, Affective Computing, Connected Home, Nanotube Electronics, Augmented Reality, Virtual Reality and Gesture Control Devices.
Go to Market Gartner Hype Cycles – Perceptual Smart Machine Age
Gartner believes that Smart Machine Technologies will be the most disruptive class of technologies over the next ten years.
Radical computational power, near-endless amounts of data, and unprecedented advances in deep neural networks will enable organizations with smart machine technologies to harness data, adapt to new situations and solve problems that have not been encountered previously.
Relevant Technologies Include: Smart Dust, Machine Learning, Virtual Personal Assistants, Cognitive Expert Advisors, Smart Data Discovery, Smart Workspace, Conversational User Interfaces, Smart Robots, Commercial UAVs (Drones), Autonomous Vehicles, Natural-Language Question Answering, Personal Analytics, Enterprise Taxonomy and Ontology Management, Data Broker PaaS, and Context Brokering.
Go to Market Gartner Hype Cycles – The Platform Revolution
The shift from technical infrastructure to ecosystem-enabling platforms is creating a foundation for entirely new business models that are forming the bridge between humans and technology.
Organizations must proactively understand and redefine their strategies to create platform-based business models. And, it will be key to exploit internal and external algorithms in order to provide value.
Key Technologies Include: Neuromorphic Hardware, Quantum Computing, Blockchain, IoT Platform, Software-Defined Security and Software-Defined Anything .
Go to Market Gartner Hype Cycles – Internet of Things IoT
By 2019, 80% of new applications using IoT or machine data will analyze data in motion as well as collect this information for analysis of data at rest.
The McKinsey Global Institute report, The Internet of Things: Mapping the Value Beyond the Hype, estimates that IoT has a potential economic impact of $3.9T to $11.1T by 2025.