Nearly all customer experience (CX) measurement and voice-of-the-customer (VoC) efforts use customer surveys. But your surveys are costlier than you think. Obvious costs include the budget for a tech vendor you use to send and analyze surveys or incentives for customers. Hidden costs are more problematic because we don’t consider them enough. They arise when surveys: Squander customers’ attention, time, and goodwill. Deplete stakeholders’ time and ability to make customer-focused good decisions. Waste your own time on reporting data that people don’t act on. In this blog, I’ll focus on the first issue. If you prefer to listen rather than read, check out our CX Cast Episode, “Feedback Is A Touchpoint, Too.” Surveys Squander Customers’ Attention, Time, And Goodwill Consider these three major problems with surveys as they are today: Surveys Consume Customer Attention Your business can only survive if customers read, consider, and respond to your marketing emails, offers, campaigns, information, etc. You also need customers to take part in research so you can understand their future needs. Using some of that limited attention on a survey is absolutely worth it if the survey is good and brings you valuable data. But are most surveys? No. Growing efforts to collect zero-party data to feed firms’ personalization efforts and the wider martech stack will make this even worse: More firms will reach out to customers, asking them about their preferences and wishes. Surveys Undermine Customer Relationships You risk seeming like you don’t know customers and don’t care about them. My bank asked me in a CX survey which credit card I own and how often I use it. The credit card provider knows both of those things — maybe the CX team cannot connect the data, but asking me these questions undermines my trust in my bank. Surveys Add A Negative Touchpoint To Customer Journeys In addition to the problem of making customers feel unseen, firms optimize surveys for easy analysis and for which questions various departments want to ask. As a result, they usually are a longish interrogation that doesn’t flow well and includes selfish questions or questions that customers don’t care about. And in many current surveys, the design still resembles a web form from the 2000s. If you have read your Kahneman (and I know many of you have), you will also realize that the survey touchpoint comes toward the end of the broader customer experience that the survey is about. So a bad survey is doubly problematic because the peak end rule tells us the end of an experience matters a lot to how customers remember the experience. If they like the branch visit but hated the survey, that will worsen memories of the overall experience! We need to follow six principles, all under the motto of “design feedback collection as a touchpoint,” if we want to strengthen relationships, be able to capture customer attention, and create good experiences rather than bad ones. 1. Rethink Surveys As Conversations Surveys should be designed to mimic natural, engaging conversations rather than interrogations. This approach involves creating a flow where questions are logically ordered and relevant to the customer’s experience. If you have conversational design experts at your company, get their recommendations on how to make the survey feel more like an engaging dialogue. If you do nothing else, read the survey aloud to someone who matters to you (your boss, wife, first date). This simple exercise can reveal issues with wording and flow that may not be apparent on paper. If the survey is embarrassing or feels tedious to you, it’s likely your customers will feel the same. Don’t expose your customers to it. 2. Don’t Just Say You Value Customers’ Feedback — Prove It If customers gift you their time to give feedback, you are now responsible! You must make sure to give back. Customers want to know their input is valued and acted upon. Share examples of tangible changes made based on previous feedback. You can do that in one-to-many conversations or even in your next survey invite, as you see in this example. This not only encourages participation but also enhances the customer experience by reinforcing their importance in shaping the brand’s direction. As discussed, organizations often have internal pressures to include numerous questions in a survey, which can overwhelm customers. Highlight the opportunity cost of using customers’ time for unnecessary questions to streamline surveys and respect customers’ input and time. 3. Pre-Test To Avoid Confusion And Ambiguity Pre-test the survey with real customers or employees outside the project team. Many organizations think of A/B tests, and while those are important, you need to do more. You also cannot just ask respondents if they understand the questions. Instead, ask them to restate the questions in their own words. This practice helps uncover potential misunderstandings and ensures clarity. For example, when asking a question like, “Was our communication good?” respondents restating it tells you if they interpret this as the effectiveness of language, the overall communication process, or something else. Only if you identify these variances early on can you avoid confusion and gather more accurate and useful data. 4. Match Survey Content And Timing I was recently invited to a radio interview on surveys by Marketplace, a US public radio broadcast covering business and the economy. The host Dan told the story of how he bought tomato seeds at Home Depot and got a survey about the purchase before he was even able to sow them, much less eat the fruits of his labor. Check out Dan’s interview with Fred Reichheld, two other experts, and me. You can still send a survey right away, but limit yourself to things the customer can judge — like how easy it was to buy the tomatoes. And focus on things you want to change in that moment. In addition, collect feedback after the customer achieves the goal of their journey. Only then will you get customers to reflect. These insights form the customers’ “remembering self” which influences

This one is different. Not only is it the penultimate CRM Watchlist – the 19th – but the winners were actually announced on a CRM Playaz Awards Show on Thursday, February 24, taking the suspense out of the blog post. If you want to watch the show, here it is on YouTube. Our primary channel is LinkedIn and then Twitter and some on Facebook. But YouTube is where you can see the uncut unexpurgated edition – Henry Miller watch out. Because this isn’t a Big Reveal post and instead is a post to recognize the already publicly announced winners of the Watchlist this year, it will be abbreviated (my idea of abbreviation though).  They’ll be some repurposing of content because it still applies, needs to be reiterated and why would I want to rewrite it since it’s more details than anything else. I’ll tweak it though.  I’ll cover the following in the post. The Watchlist context & criteria How I score The differences between the CRM Watchlist 2022 and the CRM Watchlist 2020 The data Observations The winners The CRM Watchlist 2023 A big thank you The Watchlist awards context and criteria Given that what I’m writing about here has been generally similar for 19 years, I bear the risk of repeating myself. Or as the saying that would date me goes, this might repeat like a broken record (does anyone under 60 know what I mean when I say a “record”?) The CRM Watchlist is an impact award. It is not focused on the financial success of the company though that is a criterion considered. It isn’t designed to analyze how good or bad the strategy is – it is focused on the level of successful execution and clarity of that strategy. What that means is that as an analyst, I might judge your strategy and publicly or privately express my opinion on it and perhaps an alternate strategy or a tweak that I might think would improve your company’s chances of success.  That is NOT what I’m doing as a judge. I’m taking your strategy, whether I agree with it or not, and seeing how well you executed it and what the impact in the market is as a result of that strategy. To win the award you have to show that in the year immediately before submission (same year) you had a significant impact on the market – and that you have the corporate infrastructure, strategy, and resources to sustain that impact over the next three years. What do I mean when I say “impact?” That means significant influence in the market that you participate in. It doesn’t have to be global. It can be specific – e.g., a vertical market, a sized (small, midsized, enterprise) or a geographical market. It can be a market specific to your offering.  For example. The Big 5(Salesforce, SAP, Microsoft, Oracle, and Adobe) are in global markets. Thunderhead was focused on Customer Journey Orchestration and Real-Time Interaction Management. A few years ago, when consulting companies were still part of the competition – Solvis Consulting won because of their impact in Latin America.  Veeva won for their incredible dominance in the Life Sciences market.  It can be specific.  There is no winning by category though. You meet the brutal criteria for winning and you win – no distinction or preference for which markets you address. The only data when it comes to the actual winners that get revealed is who was the #1 scorer. Additionally, though it’s been called the CRM Watchlist for the last 14 years of its 19 – year existence, it is open to all that provide customer-facing technologies. There are 53 categories to choose from on the registration and the questionnaire and something called “Other” in case you are doing something that doesn’t fall under the 53 other choices. For your impact to be sustainable, the company must be a complete company that has been doing this long enough to have established a rhythm. The company has to be well-rounded: it has financial stability, solid management, excellent products and services, superb culture, and a strong partner ecosystem to help sustain its efforts. It has to have a clear vision and mission and also clear-cut strategies for outreach to get external forces – customers, analysts, journalists, prospects, influencers, etc. – engaged. That takes a complete (and complex) set of tools and activities, which could include marketing, analyst relations and public relations programs, the subject matter expertise via the content produced and distributed for consumption, and the “theatrical” activities that establish the corporate identity necessary to stay top of mind, as well as capture share of wallet. And, because this is the first Watchlist that occurred during the pandemic, not only your immediate response to the pandemic but your long-term planning and creation of infrastructure to support the changing world we live in, now is part of what all those who submit have to prove. How I score The key to this WHOLE thing is that the entrants to the competition have to prove that they had an impact in the immediately preceding year to the Watchlist named year. So this year, that means the impact the company had in 2021 for the CRM Watchlist 2022. Next year will be the impact the company had this year – 2022 – for the final CRM Watchlist 2023.  But what I’m NOT interested in is just that. To win the CRM Watchlist or even have a chance you have to show me that you not only had an impact in the year at hand but had the infrastructure and the foresighted strategic thinking to be prepared to sustain that impact for the following three years. If you only had the impact of the year, that isn’t enough. You could be a one-hit wonder. But show me both – and you have to in order to win – and you have a real shot at winning. Another thing: While I do independent

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Accenture has formed an Nvidia business group with 30,000 professionals to receive training to help enterprises scale up for the AI era. The aim is to train Accenture’s team to help clients reinvent processes and scale enterprise AI adoption with AI agents, said Lan Guan, chief AI officer at Accenture, in a press briefing. “We are living in the future we are envisioning, starting with our own company,” Guan said. “We are reinventing this business.” Accenture is tapping its existing workforce for the talent, but it is also training current employees and hiring new people to meet the 30,000-person goal for the new group, Guan said. She did not disclose how many new hires there would be. She also did not say how much each company will invest in the partnership. “Demand for GenAI is not slowing down,” Guan said. “We are coming together to increase adoption so they can use generative AI as a competitive advantage.” Justin Boitano, Nvidia’s vice president of enterprise AI software, said in a press call, “Every job function can benefit. There are a lot of great early successes. Customers are not always AI experts. The Accenture team has invested a lot” in this expertise. The new group amounts to an expanded partnership between Accenture and Nvidia. With generative AI demand driving $3 billion in Accenture bookings in its recently-closed fiscal year, the new group will help clients lay the foundation for agentic AI functionality using Accenture’s AI Refinery, which usesthe full Nvidia AI stack—including Nvidia AI Foundry, Nvidia AI Enterprise and Nvidia Omniverse—toadvance areas such as process reinvention, AI-powered simulation and sovereign AI. This software foundation will help Nvidia sell more of its AI processors. Guan said the Accenture AI Refinery will be available on all public and private cloud platforms and will integrate seamlessly with other Accenture Business Groups to accelerate AI across the SaaS and Cloud AI ecosystem. “We are breaking significant new ground with our partnership with NVIDIA and enabling our clients to be at the forefront of using generative AI as a catalyst for reinvention,” said Julie Sweet, chair and CEO at Accenture, in a statement. “Accenture AI Refinery will create opportunities for companies to reimagine their processes and operations, discover new ways of working, and scale AI solutions across the enterprise to help drive continuous change and create value.” I asked if the group was a division of Accenture. The company replied The Accenture Nvidia Business Group is wholly owned by Accenture. Accenture has business groups with its largest and most strategic ecosystem partners. The groups bring together the leading technology from partners with Accenture’s innovation and industry experience to help joint clients reinvent their businesses. The Accenture Nvidia Business Group will leverage Accenture’s AI Refinery and Nvidia’s technology to help enterprises rapidly deploy and scale AI-driven solutions. “AI will supercharge enterprises to scale innovation at greater speed,” said Jensen Huang, Nvidia CEO, said in a statement. “Nvidia’s platform, Accenture’s AI Refinery and our combined expertise will help businesses and nations accelerate this transformation to drive unprecedented productivity and growth.” Scaling agentic AI for enterprises The new Accenture Nvidia Business Group will accelerate momentum with generative AI and help clients scale agentic AI systems — the next frontier of gen AI — to drive new levels of productivity and growth. This significant investment will be supported by over 30,000 professionals receiving training globally to help clients reinvent processes and scale enterprise AI adoption. Agentic AI systems represent a leap forward for generative AI, the companies said. Instead of a human typing in a prompt or automating pre-existing business steps, agentic AI systems can act on the intent of the user, create new workflows and take appropriate actions based on their environment that can reinvent entire processes or functions. Accenture and Nvidia are already helping clients adopt and scale agentic AI systems. For example, IndosatGroup announced the first sovereign AI in Indonesia that enables businesses to securely deploy AI while ensuring data governance and adhering to regulations. It is collaborating with Accenture to build industry-specific solutions on top of Indosat’s data center, which includes Nvidia AI software and accelerated computing, to support local enterprises. With an initial focus on the financial services sector, the new solutions, powered by the AI Refinery platform, will help Indonesian banks harness AI to drive profitability, operational efficiency and sustainable growth in a highly competitive market. Accenture will also debut a new Nvidia NIM Agent Blueprint for virtual facility robot fleet simulation, which integrates Nvidia Omniverse, Isaac and Metropolis software, to enable industrial companies to build autonomous, robot-operated software-defined factories and facilities. Accenture will use these new capabilities at Eclipse Automation, an Accenture-owned manufacturing automation company, to deliver as much as 50% faster designs and 30% reduction in cycle time on behalf of its clients. Network of AI engineering hubs As part of its Center for Advanced AI, Accenture is introducing a network of hubs with deep engineering skills and the technical capacity for using agentic AI systems to transform large-scale operations. These hubs will focus on the selection, fine-tuning and large-scale inferencing of foundation models, all of which pose significant accuracy, cost, latency and compliance challenges when development is scaled. Building on existing hubs in Mountain View, California, and Bangalore, Accenture is adding AI Refinery Engineering Hubs in Singapore, Tokyo, Malaga and London. In addition to its use of agentic AI at Eclipse Automation, Accenture’s marketing function is integrating the AI Refinery platform with autonomous agents to help create and run smarter campaigns faster. This will result in a 25% to 35% reduction in manual steps, 6% cost savings and is expected to achieve a 25% to 55% increase in speed to market. source

ABOUT PEW RESEARCH CENTER Pew Research Center is a nonpartisan, nonadvocacy fact tank that informs the public about the issues, attitudes and trends shaping the world. It does not take policy positions. The Center conducts public opinion polling, demographic research, computational social science research and other data-driven research. Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. source

Commvault announced that it is acquiring Clumio for $47 million on September 24. On its surface, the acquisition doesn’t bring a significant number of customers, and it doesn’t expand Commvault’s overall data protection coverage significantly. So what does this acquisition mean to one of the leaders in the enterprise data resilience market? Commvault And Clumio Users: What It Means To You Commvault can abstract data protection across multiple cloud environments, and it relies on traditional architecture that uses compute and data movers. Clumio dedicated itself to the protection of AWS services. Its architecture takes advantage of native cloud infrastructure like AWS serverless Lambda functions for ephemeral compute needs. The acquisition gives Commvault additional depth and expertise on AWS and should be viewed alongside its relatively recent purchase of Appranix, a cloud resilience and recovery company. Commvault customers leverage Clumio’s efficient, cloud-native data protection with Appranix’s runbook capabilities to build a high-performance cloud resilience platform that handles fast rebuild of application and infrastructure and then automatically attaches it to protected data in a way that scales to meet almost any resilience RTO (recovery time objective). For enterprise clients, this acquisition should improve their overall resilience. Is This New? Commvault is not the first company to pursue the strategy of building deep data protection and recovery capacity in the public cloud. It is emulating a playbook from Druva in terms of exploiting the functionality of AWS to accelerate cloud resilience, though Druva’s capabilities are less pronounced in recovery runbook management. In the greater data resilience market, almost all long-standing players are expanding their capabilities for backing up and restoring hyperscaler offerings but not just cloud VMs — storage, database, Kubernetes, and other services are part of this, as well. Single hyperscaler-focused companies like Clumio have found it harder to compete as traditional players add more cloud capabilities. We expect that every enterprise backup player will make similar moves to address enterprise needs, especially as hybrid cloud adoption continues to expand. Expect Increasing Cloud Usage And Little Repatriation We can learn a lot about the enterprise tech stack by observing the actions and the portfolio of the backup companies that support them. Many vendors claim a resurgence of repatriation, but the actions of both the hyperscalers and the data protection companies like Commvault tell us that enterprises are learning to use cloud environments more effectively and that they are moving beyond cloud VMs, like EC2, into serverless and container-based compute. Additionally, these businesses are separating application infrastructure from data to allow for new resilience patterns such as those enumerated in the report, How To Design Your Cloud-Native Patterns For Resilience. And although many companies have repatriated an app or two, the general trend is increased cloud usage both in terms of percentage of your infrastructure and in sophistication of its usage. source

Hyper-experimentation with Generative AI (GenAI) dominated the conversations of business and technology leaders in organizations of all sizes, across all industries, and in all countries for the past 18 months. Checking in with CIOs and business leaders 18 months later, we can report that a typical enterprise identified hundreds of GenAI use cases. They launched dozens of Proofs of Concept (POCs), but they put less than six into production, so far. This GenAI scramble is not sustainable for enterprises, or for technology providers who care about converting POCs into sustainable, long-term business. Is it time to write off GenAI as just another over-hyped tech story that generates lots of bubbles, but doesn’t have a lasting impact? Uh…no. Doing so would also be a big mistake. The focus on GenAI experimentation obscures the reality that most organizations are already invested in AI across their business. We surveyed 889 IT leaders in May 2024, and 84% believed (42% strongly) that AI/GenAI is the next strategic corporate workload like ERP or ecommerce was before. AI is already embedded into how they engage with customers, how they monitor activities in their factories and warehouses, and how they automate tasks such as “procure to pay”.  They also know that securing employees’ devices and their critical systems depends upon aggressive use of AI by security product and services providers. The casting of a wide net when it comes to GenAI experimentation increases your CIOs’ awareness of the extent of overall AI use, but also shows how fragmented and even duplicative that use is. Your business and IT leaders setting 2025 tech investment plans need to develop an enterprise wide-AI strategy, building on the “lessons learned” while doubling down on the demonstrated benefits of GenAI for boosting business outcomes. 2025 will be the year of the AI Pivot. How effectively you set priorities, make decisions, and address barriers will decide if you are ready to fuel business growth on an AI foundation or will still be racing to catch up a couple years from now. Where should you start? IDC’s AI Adoption Model How severely were your GenAI experimentation efforts limited in the following areas? Strategy: Depth of relationship between business and tech teams in PoC prioritization, development, and execution is a key success factor. Poor coordination between IT and lines of business (LOBs) is one of the most often cited factors contributing to low success rates. My colleague Ewa Zborowska has some good suggestions on how to reduce Pilotitis. The critical next step? Building a use case prioritization roadmap. Governance: GenAI experimentation across functions and with ties to multiple data sets overwhelms narrow, siloed IT governance processes. Organizations with high success rates noted their ability to quickly integrate responsible AI into strong, comprehensive governance practices. Especially important, they have solid, cross-functional data-sharing governance practices. People: Most early POCs focus on individual actions or basic process improvements, exposing significant if under-appreciated bottlenecks. What is most exposed, however? Disconnects between senior executives and employees on the consequences. IT teams are caught in the middle as promised productivity gains fall short due to lack of training or fear of consequences. Apps: “Now (or Coming Soon) with GenAI” is a recurring theme for technology providers. The infusion of GenAI into business, IT Ops, data management, and developer apps affects decisions on which POCs to pursue and raises the stakes in “build versus buy” decisions for production launches. The biggest ask? “Please, help us show quantifiable value!” AI Platforms: Companies are already using diverse AI platform components across a wide range of individual AI efforts. The GenAI scramble increases the use of disparate and nascent tools and technologies across AI and GenAI specific lifecycles strains resources. What’s missing? Reusability and scale. Data: The GenAI scramble highlights the importance and exposes weakness when it comes to identifying, quality assuring, and integrating data sets for production launches. Access to high quality data contributes to high rates of success. Past decisions to treat data during app development as a byproduct or waste product, with no thought about the importance of metadata, however, means too much “dark data”. Infrastructure: Despite the hype about lack of access to infrastructure (extremely expensive GPUs), most enterprises do not see this as a major issue. Currently, siloed infrastructure solutions and existing as-a-Service funding models support hyper-experimentation. Where they fall short is scaling for production. Excessive costs “at scale” break ROI calculations. What’s Next? Prioritizing goals and investments will vary depending upon how significantly you were affected in all 7 areas. The AI pivot is about reaching the end states you need to succeed in each. You are ready to accelerate business growth and competitive success with an AI-fueled business operating plan covering organization, culture, resources and operations. AI, not just GenAI, is fully integrated into your enterprise business strategy. It includes a targeted set of AI/GenAI super use cases that deliver maximum business impact across multiple processes and domains. You are also setting up a multi-stakeholder, unified AI governance model that aligns with your AI-fueled strategy. Most importantly, you are ensuring that effective use of AI assistants, advisors, and agents is at the core of AI-aware workforce planning and training. Of course, setting up an AI-fueled business model is irrelevant if you aren’t shifting to an AI-ready technology operating model, ensuring that you can cost effectively and securely scale the use of AI capabilities anywhere. You are confident that you can track the costs and benefits associated with AI-infused processes & apps. You are moving towards adoption of a unified AI platform that improves data and model use as well as app dev/deployment. You are addressing the “dark data”  with AI-Ready Data based on the adoption of a “managing data as a product” strategy, ensuring that quality, accessibility, and governance of data isn’t an afterthought. Finally, infrastructure is no longer siloed, and scaling costs are no longer an impossibly high barrier to innovation. Your tech operating model is built on infrastructure that is interoperable, fit-for-purpose, and intelligently optimizable

Gen AI is Transforming Experiences In this era of AI everywhere, one thing is clear: GenAI is not just another technological advancement. It is significantly impacting many aspects of enterprises – and experiences are a huge component of this. GenAI is truly becoming a game changer in terms of the unprecedented level of hyper personalization it brings to the table. Imagine a situation where you, as a customer, are ordering groceries online. A GenAI -enabled agent can anticipate ahead of time what items you tend to put in your cart and provide you with multiple alternatives of those out of stock, depending on your desired delivery date and time. Further, it can share with you active promos on items you tend to purchase without you having to look or search for them one by one. This would make my day to day tasks so much easier. The value discussion is evolving – moving away from traditional methods of measuring success of CX initiatives, where it is customer metrics such as customer satisfaction, or financial metrics such as revenue, and profitability. Organizations are looking to connect the value of their CX efforts to the impact on all the stakeholders in this experience ecosystem – internal and external. APJ organizations are recognizing this opportunity and moving fast to act on it. According to IDC’s FERS Wave 3 2024 Survey, 49.6% of APJ organizations are in initial testing stage, while 40.3% are investing significantly in GenAI. However, 55.2% organizations are still struggling to connect AI-powered applications and technology projects to business outcomes, according to IDC’s FERS Wave 1 2024 survey results. There is still a long path to traverse to realize value from potential of these modern technologies. Enter the Experience-Orchestrated Business (X-OB) Model To design experiences that span processes, applications, channels, and intelligent exchanges between the entire ecosystem of stakeholders, IDC has put forth the construct of the experience-orchestrated (X-O) business. An X-O business thrives due to its ability to deliver shared experience value powered by intelligence. To compete in an AI everywhere world, digital businesses must orchestrate a meaningful value exchange between the organization and their key stakeholders. Data is vital to intelligent applications embedded in daily operations and decision-making. Insights help align actions with desired outcomes and ensure that investments deliver the desired results for the experience-orchestrated business. Using AI-enabled technology to optimize journeys and automate workstream tasks, organizations can break down organizational silos and foster connectedness across the experience ecosystem. Where Does X-O Fit into the CX World This model provides a way for all the CX stakeholders to evaluate their capabilities across the four key pillars – connections, intelligence, culture, and actions. 1. Connections: This means transforming the environment we are working in towards more cross-functional collaboration, real-time data sharing, and integration. For customer service/support teams, this means they would be able to maintain context across interactions, reduce customer effort, provide more proactive customer engagement, and enhance their overall service quality. For marketing and sales teams, this means a unified brand voice, consistent communication, seamless transfer of leads from marketing to sales, and so on. When all three collaborate effectively, it can help unlock cross-selling/up-selling opportunities, integrated customer support, and consistency across channels and touchpoints. 2. Intelligence: Intelligence from automated processes can be used to optimize experiences further. Any new technology comes with risks – brand, data privacy, and compliance to name a few when it comes to GenAI. Building trust is critical – customers are becoming increasingly conscious and cautious about how and what data they are sharing across different apps and brands. Being able to do this effectively means customer support teams have automation in place to streamline customer service processes and speed up time to resolution. Further, AI is at the driver’s seat guiding them with context-aware prompts to reply to customers, or directly being able to address customer queries. Marketing teams can automate a greater number of manual tasks ranging from SEO, end-to-end campaign management, predicting future engagement trends, and identifying opportunity areas for improvement. There is also the element of being able to generate more relevant content, which includes hyper personalized campaigns, towards improved engagement and conversion rates. Sales teams would be empowered with the relevant customer context before calls, higher quality leads, and so on. 3. Culture: Culture, often ignored, forms a critical part of attracting, skilling, and retaining the right talent within an organization. More often than not, organizations tend to focus on output as a measure of success. This needs to change and become more outcome-oriented. For example, customer satisfaction from closed cases should be prioritized over number of cases (effective case resolution) closed in a given time interval (productivity). There is a need to establish joint and consistent metrics across CX, marketing, and sales. Service quality and the experience provided to the customer take precedence over productivity. CX, marketing, and sales teams gain incentives based on customer impact – how seamless they made the experience for the customer, continuous improvement based on predictive insights, recognizing sales reps who go the extra mile to resolve customer pain points over just those who bring in the most opportunities. 4. Actions: This refers to being able to engage stakeholders in a context-aware manner. This is a result of having the right tools and technologies in place to actively listen to the various cues (sentiment, intent, behavior, etc.), and convert into actionable insights. GenAI is great at consuming large amounts of structured and unstructured data. This large amount of data should be filtered to identify that of value. Once CX, marketing, and sales teams are armed with these insights – they can more effectively respond to customer needs ahead of the customer asking for it and in real time. All the customer micro-moments are opportunities to act fast, if you are slow, you lose out to many others in the market. Assessing where organizations are in their ability to have all these pillars in place, will help them identify the opportunity gaps

In the realm of experience research and design, achieving organizational maturity is an ongoing process of evolution and refinement. Leaders must transcend reactive, ad hoc management of their teams to embrace a systematic, data-informed approach that emphasizes responsible, strategic scale. Learn how seasoned leaders manage their organizations through the lenses of five pillars: purpose, people, practice, process, and performance. Forrester’s new report introduces the Forrester Maturity Progression Model, offering research and design leaders a management framework to guide their efforts as leaders and an accompanying assessment to evaluate their organization’s maturity. These pillars act as the cornerstone for building a successful, impact-driven research and design organization: Purpose. Defining organizational purpose is a leader’s primary mandate. Purpose is akin to an organization’s identity and should be managed with care. People. People are an organization’s primary means of success. With a defined purpose in place, leaders can align expertise and skills to goals. Practice. Practice enables organizations to consistently apply discipline expertise (e.g., service design, visual design, user experience research) to discovering, defining, creating, evaluating, developing, and monitoring solutions for customer, employee, and business challenges. Process. Process leverages tools and collaboration to create, organize, and govern work in partnership with others. Performance. Performance evaluation and communication are essential to maturity progression. Leaders who fail to benchmark, monitor, measure, and communicate impact to key audiences risk losing the support of senior leaders, peers, and partners. For leaders at the helm of research and/or design organizations, this report is an essential resource and call to reframe your perspective on maturity from a destination to a journey of continual progression, as well as think deeply about the conditions you create for your teams, the systematic approaches you adopt, and how you measure and communicate your impact. Let’s Connect Read the full report for more insights and to begin your journey toward organizational maturity. If you’re a Forrester client and would like to discuss this topic further, set up a conversation with us here. You can also follow or connect with us — Senem Biyikli and AJ Joplin — on LinkedIn. source

70% of organizations struggle to provide completely connected user experiences across all channels. And almost three-quarters (72%) of organizations’ customer interactions are now digital.  MuleSoft 2022 Connectivity Benchmark Report MuleSoft’s 2022 Connectivity Benchmark Report found that 70% of organizations struggle to provide completely connected user experiences across all channels. At the same time, the report noted that almost three-quarters (72%) of organizations’ customer interactions are now digital.  Digitalization is accelerating, and organizations could lose on average nearly $7 million in revenue if they fail to complete digital transformation initiatives successfully. MuleSoft’s 2022 Connectivity Benchmark Report, in partnership with Vanson Bourne and Deloitte Digital, was produced from interviews with 1,050 IT leaders across the globe.  Here’s an executive summary of the report:  Organizations could lose on average $7m if they fail to successfully complete digital transformation initiatives. While companies have more applications than ever, they’re becoming less successful at integrating them. Legacy code and systems, siloed data, and skills shortages abound. Data silos are a persistent challenge for 90% of organizations. Integration demands are increasingly cited for more data scientists, business analysts, and customer support staff. The biggest challenges lie with incorporating dataderived insight into user-facing apps. Over half (52%*) of IT projects weren’t delivered on time last year (2021). The number of projects IT is being asked to deliver has increased by 40%* in the last year. Yet existing infrastructure continues to slow down project delivery speed, turning the department into an innovation bottleneck. Over half (55%) of organizations say it is difficult to integrate user experiences. This is a 7% increase from last year, driven by security and governance challenges, outdated infrastructure, and an inability to keep up with changing processes, tools, and systems. More than a quarter (26%) of business leaders now demand a company-wide API strategy. That’s almost double the figure from 12 months previous, although the number using APIs to build integrations has not changed in the intervening period. On average, over a third (35%) of organizations’ revenue is now generated by APIs and related implementations. In addition, they are recognizing how the combination of API-led connectivity and automation can deliver better employee and customer experiences.  Here are 13 powerful takeaways from the 2022 Connectivity Benchmark Report: Digital takes center stage: Nearly three-quarters (72%) of organizations’ customer interactions are now digital, and 93% say the speed at which projects take place is faster than it used to be 5 years ago. Digital takes center stage 2. The financial cost of slow digital transformation is significant: It’s calculated that they could lose on average nearly $7 million ($6,846,979) if they fail to successfully complete digital transformation initiatives. The business cost of slow digital transformation is significant  3. Adoption of apps is accelerating, but integration is falling behind: The average number an organization had this year was 976, a large increase from the figure a year ago (843). This could be an indication of growing shadow IT deployments in organizations during the pandemic. But more importantly, only 28% of these apps on average are integrated, down slightly from 29% in the 2021 report. The average lifetime for a typical application has also grown slightly to 4.1 years. Apps are on the rise, but integration is not 4. Firms are spending too much on custom integration: On average, companies spent $3.65 million in custom integration labor in 2021 versus $3.5 million in the previous 12 months. Firms are spending too much on custom integration: $9.5M in 2022 5. Data silos are persistent: Some 90% of respondents cite silos as a challenge, the same number as in the 2021 report, showing that little progress has been made in this crucial area. Data silos are causing significant business problems for most enterprises  6. Integration demands grow across the enterprise: Data scientists are most likely to have requirements for unlocking and integrating data (49%), followed by business analysts (44%), then customer support (42%). Integration demands grow across the enterprise The most pronounced integration challenges were: Incorporating data-derived insights into user-facing applications (75%) Reusing data sources across different user-facing applications (73%) Correlating data in the warehouse to derive insights (71%) Moving data from source systems into the data warehouse (70%) Also: Global research: 3 out of 4 professionals do not feel ready to work in a digital-first world 7. IT budgets continue to rise: 85% of responding organizations said this was true versus 77% in the 2021 report and 75% in the 2020 report. The number of projects IT is asked to deliver has increased by 40% in 2022, a jump from 30% in 2021. Over half (52%) of projects weren’t delivered on time last year. IT budgets are up, but so is demand 8. IT is struggling to deliver on time: On average, 52% of projects weren’t delivered on time over the past 12 months. However, the good news is that IT is more likely to be completing all the projects asked of them than in the period covered by the 2021 report: 44% versus 37%. IT is struggling to deliver on time  9. Organizations find it harder to integrate user experiences: Over half (55%) of organizations are finding it difficult to integrate user experiences. Nearly a third (30%) of organizations are able to provide completely connected user experiences across all channels. Connected experiences are more common today 10. Security and governance top integration challenges: Over half (55%) of organizations say it’s difficult to integrate user experiences, up from 48% a year ago. The biggest challenges are:  Security and governance (54%) Outdated IT infrastructure (46%) An inability to keep up with ever-changing processes, tools, and systems (42%) Data silos (42%) 11. Leadership now mandates a company-wide API strategy: The vast majority (98%) of organizations now use APIs. The number who mandate a company-wide API integration strategy has surged to 26% from 15% just a year ago. Nearly half (46%) of internal software assets are available for reuse, and 55% of organizations have a mature or very mature strategy for non-technical users.  APIs are virtually