Use Cases for Digital Compliance Management in the Pharmaceutical Industry | Market Insights™
March 16, 2023
Digital Compliance
Digital Compliance
The property and casualty insurance industry has become a significant adopter of Software as a Solution (SaaS) technology and continues to see a massive influx of SaaS applications embedded across organizations’ business operations.
“If you stack all of these SaaS solutions together, the spend becomes quite sizable. And what we’re starting to see is it’s not just the spend that is becoming sizable. We are also seeing duplication of solutions because these solutions, over a period of time, have evolved to do more.” says Ronak Doshi, Partner at Everest Group.
Balancing experience with data and trust is essential to delivering engaging personalized experiences for customers and driving business success. Developing a robust and scalable automated process for data-driven personalization is critical for enterprises to win in the evolving personalization and interactive experience segment. Read on to learn more.
Customer experiences have become increasingly prevalent with the democratization of the internet, coupled with significant technological and data processing advancements over the past few years. Enterprises are now realizing the value of prioritizing the people side of business. Creating positive personalized experiences for customers can foster loyalty, increase customer satisfaction, and drive repeat business. On the other hand, negative experiences can damage a reputation and reduce customer loyalty. Let’s explore the importance of personalization.
Personalization is not a new concept. It has existed for decades. Enterprises must capture users’ attention and stand out to thrive. According to Everest Group estimates, more than 70% of consumers interact with a personalized promotional message.
Personalization, more commonly known as “persona-based personalization,” mostly involves grouping users into segments or personas based on common characteristics or behaviors. This approach can be effective in delivering relevant content or offers to a large group of users with similar interests or needs, based on demographics, purchase history, or browsing behavior.
Today, technological advancements have changed the landscape. Categorizing consumers is difficult because they don’t have just one interest area. The plethora of information available online has shifted the power to consumers who determine their preferences, disrupting brands that are no longer in charge.
As a result, brands now are also adopting “person-based personalization,” a form of personalization that considers the individual’s unique needs and habits instead of categorizing the user into specific buckets. Personality-based personalization is a 1:1 approach, where enterprises focus just on the customer as an individual. Everything revolves around the individual as a person, ranging from interactive experiences to advanced personalized marketing strategies. While persona-based personalization involves a large sample size, person-based personalization involves a sample size of just the individual.
Because person-based personalization has the potential to deliver high returns on investment (ROI) to enterprises, deploying an industrialized process for real-time person-based personalization is essential.
While most brands have invested in personalization, some remain reluctant to fully embrace real-time data-driven personalization at scale, which involves personalizing every touchpoint in the customer’s journey based on real-time context. This method requires a unique interplay of data, intelligence, and omnichannel strategies. Developing an industrialized process for delivering individual personalization beyond the required data analysis is essential for enterprises.
Data is the most critical requirement for delivering effective personalization. Personalization is driven by insights into individual preferences, behaviors, and needs that only can be obtained by collecting and analyzing data. Data collection needs to be well-thought-out. Enterprises require large volumes of data collected from multiple sources, and this data needs to be of good quality, accurate, and relevant because poor-quality data can lead to incorrect insights. Collecting diverse and up-to-date information is another important aspect.
The scope of data gathering has increased too. In the past, customer data was mainly collected via offline surveys, point-of-sales, and telecommunication, just to name a few. But the increased digitization supplemented with advancements in data and analytics has greatly impacted personalization by also allowing for collecting and analyzing vast amounts of data through digital channels. This has led to more seamless personalized experiences for users and has helped companies build deeper relationships with their customers.
An Everest Group study suggests that 78% of startups in the customer experience (CX) space leverage Artificial Intelligence (AI) to develop more relevant and engaging solutions for customer conversion, engagement, and retention. With the rise of AI, personalization has become even more precise and can consider a wider range of factors such as emotions, mood, and context.
However, significant investments are required if enterprises want to set up in-house industrialized data collection and analysis. This is where data platforms come into the picture. Data platforms can be thought of as purpose-built systems or infrastructures to collect, manage, and process large data amounts. It typically includes technologies and tools for data storage, data processing, data integration, data security, and data governance.
Data Experience Platforms (DXPs) offer a collection of tools such as Digital Asset Management (DAM), Customer Relationship Management (CRM), Customer Data Platforms (CDP), and personalization tools that can meet the needs of enterprises, as illustrated below.
Exhibit 1. Data collection tools for aiding personalization efforts
As discussed, data is essential to personalization. Clearly, the more data enterprises have, the better insights they can gain, and the better experiences they can provide. However, in today’s digital environment, user safety and trust are crucial. Consumer awareness is on the rise, with people growing increasingly skeptical about sharing their data. Concerns over how personal data is handled and safeguarded by enterprises are growing.
According to the United Nations Conference on Trade and Development (UNCTAD), 71% of countries today have some legislation around data protection and privacy, while 9% have draft legislation. Stringent data regulations such as the General Data Protection Regulation (GDPR) in the European Union, Nigeria’s Data Protection Regulation (NDPR), The California Consumer Privacy Act (CCPA), etc., have provisions to heavily penalize enterprises misusing consumer data.
Adding to this is the increasing push to eliminate third-party cookies. While browsers such as Apple Safari and Mozilla Firefox have already taken the step, market leader Google Chrome also has announced its intention to phase out third-party cookies by 2024, extending its earlier deadline. This has brought into focus the collection of voluntary data from users (Zero-party data) and first-party sources (1P data).
Zero-party data is a valuable information source for enterprises as it provides the best clarity to individual preferences. Developing a trust-based relationship with users and having total transparency about the use cases of zero-party data is essential for enterprises. Establishing a trust-based relationship might lead users to voluntarily provide more insights.
First-party data collection also needs to be transparent and strong security measures should be implemented to protect personal data. Sensitive data must be encrypted, security regularly audited, and effective access control measures adopted. Brands need to consider the needs of empowered users by honoring their “right to forget” and “untraceable” requirements.
As enterprises possess an enormous amount of users’ personal data, they also need to take the moral responsibility to protect that data. Customers who provide their data to enterprises understandably want their data to be protected and not misused without their knowledge. According to Everest Group estimates, more than 50% of customers are willing to share their personal data with companies but only with a clear understanding of how it will be used.
Winning user trust and gaining access to more voluntarily provided data is no doubt essential to achieving better person-based personalization. But this data needs to be utilized in the best manner by making use of tools (such as personalization engines and marketing automation tools) to set up an industrialized workflow for large-scale 1:1 person-based personalization. Without a robust and scalable automated process for large-scale person-based personalization, enterprises tend to lose.
Exhibit 2. The industrialized workflow for achieving data-driven 1:1 personalization
Personalization starts from a persona-based mechanism and, with an ever-increasing user base, shifts to person-based personalization. User data is the only way to go forward. User data and trust need to go hand in hand. To win customer attention, trust, and loyalty, enterprises need to know how to use the right data at the right time and how to go ahead with individual personalization without breaching the intrusion barrier.
Exhibit 3. Relationship between Trust and Personalization
Overall, the personalization and interactive experience landscape has become more complex and diverse, requiring brands to constantly adapt and stay up to date on the latest trends and technologies to reach and engage customers. However, even with increasing investments, the ROI might decline due to the heightened competition making it more challenging to stand out and generate returns, technical limitations, and privacy concerns, just to name a few.
Enterprises need to break down their user base into smaller, more targeted segments to achieve 1:1 person-based personalization and tailor products, services, and experiences to each individual user’s specific needs and preferences. The smaller the segments, the better enterprises can tailor their personalization efforts and achieve a more effective 1:1 experience.
In addition to the investment level, the strategy and implementation of personalization and experience efforts also needs to be considered. A well-designed and executed strategy can generate returns even with increasing investments. By balancing experience with data and trust, companies can deliver engaging personalized experiences that build strong relationships with users and drive business success.
If you have questions about selecting the right data platform or want to know more about personalization, interactive experiences, or discuss developments in this space, reach out to our analysts at the Adobe Summit, or get in touch with the Everest Group team at [email protected], or [email protected].
To learn about the comprehensive roadmap for enterprises to achieve business outcomes and mitigate challenges in their journey to accomplish truly industrialized 1:1 person-based personalization, see our report Emergence of CDPs: Charting the Path to Data-driven Personalization.
Check out our webinar, Strategies for Customer Experience (CX) Success in an Uncertain World, to learn key trends and hear recommendations on what to prioritize to deliver exceptional CX.
Data analytics and automation are becoming an integral part of business process management (BPM) offerings. BPM firms are bagging more cost-saving deals as clients prioritize on cost-cutting and beating inflation.
Budgets in most industrial sectors are up slightly over 2022, but many firms have been unable to spend their full budgets last year. “Hence, we expect to see a growth of 5-7% for the industry over last year. This is down from the 12% of 2022 but still healthy,” said Peter Bendor-Samuel, CEO of research firm Everest Group.
We’ve had ten years of digital transformation initiatives. Companies that have reached a maturity level now invest in software-defined operating platforms. These platforms are tech stacks that evolve and become very intimate with company operations. Companies need to think about these platforms holistically and develop a road map for the platform and operations together. Consequently, the core versus non-core aspect of technology services is no longer a useful construct for selecting third-party service providers or vendors. That old model is changing.
The proliferation of payment options doesn’t only make things more challenging for customers. The growth in digital wallets, and the number of payment choices out there, are making things more complex for merchants too.
“The rise in Web 3.0 and metaverse adoption will expand the number of channels and the payment methods that come along with them,” said Ronak Doshi, Partner at Everest Group. “At the same time, the rise of real-time payment schemes is poised to add more competition and players in the payment ecosystem. This will simplify the payment processes but increase the number of choices for e-commerce firms and their customers.”
Humans have a one-in-a-trillion chance of having a doppelgänger in the world—that is, someone who looks exactly like them down to their eyes, lips, and bone structure. But in an avatar-driven digital environment like the metaverse, another individual running around with your (digital) face is much more probable.
As reported by Everest Group in their “Taming the Hydra: Trust and Safety in the Metaverse” report, 55% of respondents in the US were concerned about the tracking and misuse of their personal data in the metaverse.
Three of the companies — Infosys, HCLTech, and L&T Technology Services — ended the December quarter with a higher net headcount, but the employee additions were at a slower rate than the previous quarters. Market leaders Tata Consultancy Services, Wipro, Tech Mahindra, and LTIMindtree all posted a fall in headcount.
“Though the demand-supply gap for talent is reducing, we expect the gap to continue in the range of 8-20% based on specific segments within tech services,” said Yugal Joshi, Partner at Everest Group.
Everest Group recently helped a low code no code (LCNC) product company evolve its product and pricing strategy by assessing the market standing of its platform features and commercials. Read on to learn about the approach, assessment dimensions, and outcomes in this case study.
As part of the engagement, we provided the following services to the client:
Everest Group analyzed the platform from two broad perspectives: application development capabilities (declarative tooling to accelerate application development and delivery) and process orchestration capabilities (ability to design, execute, and monitor business processes). In this blog, we’ll focus on the application development capabilities.
Everest Group gathered insights about the platform capabilities from the provider using a comprehensive RFI that collected more than 190 data points across 17 categories, followed by a briefing and demo showcasing the platform’s capabilities. Inputs from these sources were used in conjunction with our existing low-code research and ongoing conversations with ecosystem players to inform the final review across the below assessment dimensions.
Based on our research of low-code platforms published earlier this year, we identified the following five key areas where LCNC platforms can drive competitive differentiation through strategic investments:
Source: Everest Group
Now let’s take a closer look at each of the assessment dimensions and the features/components evaluated in each of these areas.
One of the foundational elements of an enterprise-ready low-code platform, this dimension takes into account the availability of out-of-the-box templates for common user interface components, widgets, and functional libraries, as well as reusability of user-built templates, availability of industry-specific out-of-the-box solutions, and a robust marketplace supported by multiple partners.
Before incorporating any new technology tool into its ecosystem, enterprise IT teams prioritize its ease of integration with the existing tech stack during the evaluation process. This dimension assesses the availability of pre-built connectors to common tools in the enterprise technology stack, the low code option to include further integrations, and the ability for developers to use custom scripting to call external application programming interfaces (APIs) where required.
As low-code platforms scale in importance from building departmental workflow applications to business-critical enterprise-grade applications, the extent of AI-powered abilities offered is proving to be a key win theme. Through in-house capabilities or integration with external AI providers, low-code platforms aspire to provide AI-powered development assistance, AI-based application management services, AI-based automated testing, AI-powered code quality alerts, and AI-augmented portfolio analysis.
Business users play an increasingly important role in the application lifecycle, collaborating with professional developers to reduce the gap between their requirements and the final product’s functionalities. Therefore, a platform should offer capabilities that facilitate effective collaboration, such as role-based access, project management capabilities, document sharing capabilities, and notifications on app updates, among others.
This dimension considers the support provided to UI components like lists and tables, the ability to support different devices and operating systems, language options, integrations with design tools, reusable screen templates, customizable themes, and navigation ease. UI/UX capabilities are a key swaying factor in enterprise low code buying decisions, especially when building customer-facing applications.
The subscription-based pricing model experienced higher adoption than perpetual licensing in 2021 because it results in lower upfront investments and greater flexibility to scale deployments. Of the eight different pricing models uncovered in our research, the user-based licensing model was the most widely adopted. On-premise deployment of low-code and no-code platforms was found to be 25-50% more costly than cloud-based deployment.
Source: Everest Group
Gap identification – Everest Group helped the client identify key market differentiators, strengths, and limitations across dimensions, as well as the key features for each of these elements
Fine-tuning product vision and roadmap – The insights helped the client prioritize its feature pipeline and advance its messaging to have a greater impact
Product and pricing strategy – The trend analysis helped the client understand the pricing strategies adopted by their competitors and how these vary based on factors like hosting environment and buyer geography
For more information about this LCNC project or to discuss our research on low-code and no-code platforms, please reach out to Manukrishnan SR, Alisha Mittal, or Yugal Joshi.
Also, learn about the top five demand themes – data and AI, cloud, experience, platforms, and security – driving growth for IT service providers in our webinar, IT Service Provider 2023 Forecast: The Top 5 Themes for Growth and Wallet Share.
The technology and services market this year experienced strong growth. But we have a slight deceleration at the end of this year as the prospect of a potentially deep recession grows. There is now a slowdown in consulting, particularly strategic consulting, and a slowdown in discretionary spending. Will that continue? Here is an overview of what I predict for the coming year.
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