Forrester

In November 2023, LeanIX was absorbed by SAP; in September 2024, Ardoq acquired ShiftX; and most recently, on December 11, 2024, Orbus Software announced its acquisition of Capsifi. All these acquisitions point to a significant shift in the enterprise architecture management suite space. Orbus Software, recognized as one of the leading vendors in The Forrester Wave™: Enterprise Architecture Management Suites, Q4 2024, has demonstrated exceptional proficiency in both its offerings and strategy. Notably, its vision stands out due to its integration with the digital twin of organizations (DTO). With the acquisition of Capsifi, the firm will move significantly closer to achieving this vision. But what exactly is a DTO? For the newly combined entity, it can be broken down into three components: Enterprise and solution architecture (traditionally, Orbus’ core strength) Business operating model and strategy (traditionally, Capsifi’s core strength) Business process analysis and mining (both players still need to evolve here) These three components will interact and enhance each other using AI features based on integration-platform-as-a-service technology, creating a comprehensive digital twin of the entire company. This digital twin allows for simulations, positioning, and using the different components as a strategic enabling tool for CEOs, business directors, and enterprise architects. The success of this merger will further showcase the power of enterprise architecture as a crucial element of a company strategy. source

AI-powered assistants are firmly embedded in B2B technologies and workflows, engaging prospects and customers in conversations across channels and automating back-end tasks to improve marketing and sales productivity. They’ve facilitated and learned from billions of interactions with prospects, customers, and go-to-market teams. Now they’re smarter, capable of functioning at a higher level, and gaining autonomy as adoption increases and agentic AI capabilities evolve. While most AI “agents” on the market now are not truly agentic, today’s AI assistants are rapidly evolving into tomorrow’s agents, with increasing levels of autonomy and adaptability. Specialized AI agents will further enhance digital experiences and support the work of human teams across functions. Within three years, agentic AI will impact every area of the business for both buyer and seller, transforming human and nonhuman interactions throughout the purchasing journey and post-sale customer experience. AI coworkers such as virtual assistants, agents, copilots, and autonomous workplace assistants continuously learn to analyze, interpret, and take action on data in context of the systems and processes used to communicate and get work done. Already, 83% of automation decision-makers at B2B and B2B2C organizations expecting to accelerate their investment in AI agents or digital coworker technologies in the next 12 months say that genAI capabilities would have a greater impact on their investment decision, according to Forrester’s Automation Survey, 2024. B2B organizations that embrace AI agents and agentic processes to create better experiences for their buyers, customers, and partners — and their internal teams —will outperform their competitors and create long-term, sustainable growth, because they can: Improve marketing’s ability to remove friction for buyers and customers. Prospect- and customer-facing AI agents play a crucial role in meeting modern B2B buyers where they are in the complex purchasing journey and enabling the next step. These AI coworkers empower self-directed buying, acting as a personalized concierge that understands, guides, and supports buyers and customers across delivery channels and modalities. In some scenarios, the AI agent itself will act as the customer. Increase efficiency and effectiveness in sales prospecting and opportunity management. AI agents act as an extension of revenue teams, automating outreach while working in the background to coordinate and schedule meetings, provide feedback and coaching through role-play, and forecast deals. Agentic process automation will enable B2B organizations to sense and respond to more nuanced buying signals from natural language interactions to help progress opportunities and increase win rates. Elevate product innovation and guided experiences. With computer use capabilities, AI agents will become the new digital experience and software product end users, accessing and using interfaces just as a human would. You should already be considering the agent UX in addition to the opportunity for product-led growth companies to deliver more personalized, self-serve experiences in their products. AI agents will be instrumental in monitoring and influencing product value recognition. With multiple AI agents in play across marketing, product, and sales, orchestration will be critical: They need to cooperate with one another to plan and take action on multistep processes, choreograph their sequences of steps within those processes, share data and generated outputs in real time, and resolve any conflicting next-action recommendations. Learn what it takes to create lasting value with AI agents at our upcoming B2B Summit North America event in Phoenix, March 31–April 3. Join us on Wednesday, April 2, for the session and panel discussion, Agency, Adaptability, And Authenticity: What An Agentic Future Means For B2B. source

Generative AI (genAI) has the potential to radically elevate customer experiences and streamline operations, delivering transformative impact across the enterprise, yet businesses encounter a significant challenge: the inherent limitations of foundational models. These models often struggle with delivering accurate and relevant outputs, primarily due to their constrained training datasets. Our latest Forrester report introduces retrieval-augmented generation (RAG) as a solution, integrating data indexing and knowledge retrieval with generative processes to overcome these challenges. This technology plays a crucial role in advancing genAI, supported by a growing ecosystem of software platforms. The RAG Revolution: From Engine To Ecosystem Leading technology vendors and forward-thinking enterprises are evolving their RAG engines — enhanced with essential core capabilities — into comprehensive, four-layer platforms designed to meet a broad range of real-world business needs. Infrastructure support streamlines integration with existing cloud and data infrastructure. Development enablement facilitates RAG-based application development, especially AI agents; platform operations provide manageability and observability for RAG adoption; and RAG governance offers guardrails for security, privacy, and regulatory compliance. Navigating The Software Ecosystem The ecosystem supporting RAG platforms is diverse, encompassing RAG platform builders, enablers, and service providers. Each plays a crucial role in the development and deployment of RAG technologies. From public cloud providers offering essential building blocks for RAG adoption to AI/ML platform vendors enriching RAG features, the landscape is rich and varied. Our report offers a comprehensive analysis of these players, providing businesses with the knowledge to choose the right partners for their RAG journey. Practical Steps For Business Leaders Adopting RAG isn’t just about leveraging new technology; it’s about transforming business operations to be more efficient, responsive, and intelligent. To this end, our report outlines four pragmatic steps for integrating RAG solutions: Data preparation. Ensuring that your data is AI-ready is foundational. Clean, structured, and ethically sourced data enhances RAG system performance. Optimization. Fine-tuning retrieval algorithms and prompt engineering can significantly improve the quality of generated outputs. Integration. Seamlessly integrating RAG systems with existing workflows and technologies is crucial for maximizing their utility. Human-centric design. Designing RAG systems with the end user in mind ensures that they meet real business needs and gain wider acceptance. For business leaders, understanding and implementing RAG technologies is not just about staying ahead in the tech curve — it’s about redefining what’s possible with AI. RAG platforms offer the promise of intelligent automation, sophisticated data analysis, and enhanced customer interactions, among other benefits. Embarking On Your RAG Journey Our report, Forrester’s Guide To Retrieval-Augmented Generation, Part Two, serves as a roadmap for businesses looking to explore the vast potential of RAG. It provides not only an in-depth analysis of the current state of RAG technology but also practical advice for implementation and optimization. Looking to further delve into how RAG can transform your business capabilities? Check out part one of this report series! Forrester clients can also schedule an inquiry with me for a tailored discussion on your RAG journey. source

In an era marked by rapid digital transformation, HSBC has boldly stepped into the future of finance with the introduction of its Gold Token in Hong Kong. In our latest case study, we dive deep into the key components of HSBC’s Gold Token journey, sharing the strategic insights that have helped the bank advance in the financial services sector.  HSBC’s Strategic Leap Into Tokenized Gold  Many firms pursued blockchain or distributed ledger technology for the sake of innovation or publicity, often resulting in products that failed to address real needs, and eventually faded away. HSBC avoided the trap of innovating for innovation’s sake. Instead, its priority was to address customers’ needs and deliver tangible business value.  At the heart of this Gold Token initiative were three primary motivators:  Market demand and cultural resonance: Recognizing gold’s cultural significance and its role as a safe haven asset, HSBC identified a substantial opportunity in Hong Kong’s market. The bank aimed to democratize access to gold investments, catering to the region’s growing appetite for digital asset solutions.  Innovation meets tradition: With a rich history as one of the world’s leading gold clearing firms, HSBC leveraged its traditional strengths, employing distributed ledger technology to enhance accessibility, efficiency, and the overall customer experience in gold trading.  Strategic differentiation and value creation: Facing competition from traditional and emerging digital financial products, HSBC set out to differentiate its Gold Token by emphasizing convenience, trust, transparency, and regulatory compliance. This approach not only positioned the Gold Token as a pioneering product but also reinforced HSBC’s role as a global bank with customer trust built through a long history.  The 3 Pillars Of HSBC’s Success  HSBC’s journey was underscored by meticulous strategy and execution across several domains:  Customer-centric innovation: Through in-depth market research and customer engagement, HSBC tailored the Gold Token to meet the explicit needs and preferences of its customers, ensuring a seamless and accessible investment experience.  Regulatory navigation and compliance: Proactive engagement with Hong Kong’s regulatory bodies allowed HSBC to align the Gold Token with existing laws and regulations, ensuring trust and security for its customers.  Technological excellence: Utilizing a proven distributed ledger platform for the Gold Token, HSBC capitalized on distributed ledger technology’s potential to offer instant settlements, fractional ownership, and 24/7 trading capabilities, setting new standards in the digital asset space.  Transformative Results And Broader Implications  The Gold Token initiative has not only achieved early success in terms of customer satisfaction and market penetration but has also sparked a conversation about the future of banking and investment in the digital age. HSBC’s experience offers valuable lessons for financial institutions worldwide, highlighting the importance of innovation, customer focus, and regulatory engagement in crafting successful digital asset strategies. Asset tokenization holds a significant potential to reshape the investment landscape going forward. In fact, Forrester predicts that the number of major banks issuing tokenized assets on blockchain will double in 2025. Explore this and more predictions in our latest investment and wealth management prediction report for 2025.  Forrester clients can read the full case study report here, or schedule a guidance session to chat more.  source

Face it — companies must navigate a perfect storm of ballooning customer inquiries, talent shortages, hybrid operations, and a rising tide of customer expectations. To succeed, customer service organizations must curate a set of technologies that underpin their operations. To discover the most important ones, we surveyed technology decision-makers, suppliers, and other subject matter experts for their opinions about which ones really mattered. We narrowed our search to technologies that are: 1) the most critical to customer operations; 2) commercially available at enterprise scale; and 3) solve key challenges for self-service and digital engagement, inquiry routing, agent operations, collaboration, and workforce management. We published our findings in our report, The Forrester Tech Tide™: Contact Centers For Customer Service, Q4 2024. Key Findings From Forrester’s Tech Tide Here are some highlights from our report: Technology stalwarts now work better together. Contact center as a service (CCaaS), workforce management, and ticketing form the backbone of customer operations. Even though they’ve been around for decades, vendors continue to make them relevant today. Vendors also realize that these technologies must work together to deliver the most value. They offer guidance and reference architectures to do just that. Generative AI increases the value of a broad swath of technologies. Knowledge management, agent augmentation, and automated quality monitoring have been in the market for years. Yet they haven’t generated their expected value because they’re just too hard to use. Generative AI’s personalization and summarization capabilities have breathed new life into them, making their ROI potential finally achievable. It’s a fine balance between risk and reward for newer technologies. There are many exciting ones out there today. Examples include agent augmentation technologies, which offload repetitive work from agents; conversational AI, which simulates human conversation; and digital adoption platforms, which guide agents through onboarding flows and complex processes. They often show great potential in pilots but don’t always deliver results when scaled because organizations don’t pay enough attention to their adoption, change management, and governance. Some long-established technologies are finally put to rest. AI — coupled with the focus on fluid, ongoing, and personal customer engagement — has killed off some categories. For example, there are no standalone options for touch-tone and directed dialogue IVRs as they are now part of more comprehensive CCaaS solutions. Nowadays, sophisticated conversational experiences driven by large language models replace these basic solutions. This puts an end to one of the longest-standing technologies in the customer service space. We feature 20 of the top technologies for customer service in our report, highlighting their maturity and business value and giving guidance on whether you should experiment, invest in, maintain, or divest from these technologies. Let us know what you think, and connect with me or one of my colleagues via inquiry to discuss further. source

Omnicom Group and Interpublic Group (IPG) announced their intention to merge to form the largest global agency holding company. Executives indicate that they anticipate closing the deal in the second half of 2025. This would reshape the marketing services category by consolidating the media scale of two global holding companies, accelerating the role of technology and AI in marketing delivery, and setting the industry on a path toward a hybrid services and SaaS model. Both Omnicom and IPG executives held a joint conference call earlier today. What we know and can infer about the proposed deal thus far is: This is an acquisition, not a merger. Omnicom is acquiring IPG — this is not a merger of equals. Omnicom would be acquiring a slightly distressed IPG that has reported relatively flat growth for the last five quarters. This shows in the proposed leadership of the new company. In a joint conference call this morning, the two companies announced that John Wren will remain chairman and CEO of Omnicom; Phil Angelastro will remain EVP and CFO of Omnicom; and Philippe Krakowsky and Daryl Simm will serve as co-presidents and COOs of Omnicom. We assume a similar dynamic for the eventual structure of the new company. The benefit of this acquisition is scale. The new company would enjoy significant scale of technology, data, media clout, and the ability to produce content at the velocity and volume of media impressions. We anticipate that IPG Mediabrands will likely roll up to Omnicom Media Group, IPG’s growing commerce practice will likely be aligned with Omnicom’s Flywheel Digital unit, and Acxiom will likely be aligned with the technology group managing Omni, the holding company’s suite of proprietary technology. The combination of the Omni marketing operating system, Flywheel Digital, and Acxiom capabilities is a potent one, enabling Omnicom to better compete with Publicis Groupe, its Epsilon PeopleCloud, and recent commerce acquisition of Mars United. The new company would concentrate a culture of creativity. The Omnicom and IPG acquisition would place some of Madison Avenue’s most iconic creative agencies, such as McCann, FCB, The Martin Agency, Mullen, TBWA, BBDO, DDB, Goodby, and GSD&M, under single ownership. Both Omnicom and Interpublic Group leverage agency-first go-to-market models, rather than an integrated, holding-company-first model like that of Publicis Groupe or Dentsu. Omnicom and IPG’s like-minded approach to agency brands makes for a stronger likelihood of successful integration and enables the new company to focus on client and talent retention. Executives from both holding companies acknowledge that details regarding future leadership and structure remain undecided and that the deal is subject to regulatory review. Nonetheless, the larger industry and client implications are beginning to come into focus. For clients of either Omnicom Group or IPG, this acquisition means: Fewer enterprise choices will facilitate more independent options. The “big six” holding cos. may soon be the “big five,” creating some concern with having fewer options. Yet consolidation at the global level makes for opportunities in the independent marketplace. PE-backed, independent agencies like Horizon Media, PMG, DEPT, Tinuiti, Wpromote, and others have grown to capture scale in buying while delivering performance and tech skill. These companies must and will react to a shifting competitive landscape. Anticipate more growth in independents’ innovation investments and more focus in their proposition to compete with the global consolidation of marketing scale at Omnicom, Publicis, and WPP. Technology and innovation investments will accelerate AI’s role in marketing services. Omnicom and IPG executives point out that the combined resources will boost their technology investments. This will accelerate the already-underway AI arms race among the holding cos. and independents: 61% of agencies already use generative AI in marketing, the most mature group compared to IT, marketing orgs, and in-house agencies. Marketers should anticipate the proliferation of AI marketing in production, creative development, and media activation. As agencies race to build competing AI marketing platforms, the combination of SaaS and services will change not only how marketing is created but also how it’s paid for. Principal media solutions will proliferate and grow to account for nearly 10% global billings. Until recently, IPG was the last major holding company not to take an interest in media. While principal media practices are controversial, our research suggests that they represent less than 10% of total global media dollars under agency management. Yet with Omnicom’s existing principal media framework, marketers should expect a percentage of the IPG Mediabrands/MAGNA dollars to transact in principal media solutions, advancing the practice as more mainstream within the industry and within a combined Omnicon Media Group and IPG Mediabrands. If you are a Forrester client working with Omnicom or IPG and want to understand what this acquisition could mean for your business/brand, feel free to book an inquiry or guidance session with me. Some additional Forrester resources include: The Forrester Wave™: Media Management Services, Q4 2024 The Marketing Creative And Content Services Landscape, Q4 2024 Predictions 2025: Marketing Agencies Brand AI Models Will Reinvent How Marketing Creates Business Value source

Amazon Web Services (AWS) may have been caught off guard by the sudden rise of generative AI (genAI), but now it’s coming for the competition from every possible angle. That was the message from the opening moments of CEO Matt Garman’s keynote at AWS re:Invent 2024, which reminded the audience of AWS’s breadth of services, with a security-centric pitch that set the stage for everything that came after. There was the usual blizzard of announcements, big and small (more on those below). The team of Forrester analysts onsite and beyond identified these key takeaways: The second round of cloud AI competition has begun. As genAI early adopters contemplate scale-out strategies, AWS has a message for both long-standing customers and prospects reeling from VMware price increases: We can make genAI work with the data and juiced-up versions of services that customers already have. Amazon CEO and ex-AWS boss Andy Jassy took the keynote stage to announce Nova, a new set of models. For sheer power, AWS is building a new super cluster for AI training for its AI partner, Anthropic, the recent recipient of $4 billion in AWS investment, using AWS’s proprietary Trainium chips as a work-around for NVIDIA’s GPU dominance. Meanwhile, the Bedrock managed AI service will serve as a marketplace for AI models. Mainstream AI service adoption will be abstracted and serverless. The keynote by Swami Sivasubramanian, vice president of AI and data at AWS, rolled out a series of closely intertwined enhancements to existing services like SageMaker and Kendra to tackle genAI challenges such as retrieval-augmented generation (RAG), a counter to Microsoft and Google’s top-to-bottom AI cloud solutions. AWS also pushed Amazon Q as an all-purpose generative AI assistant, with more third-party integrations, expanded development language support, and natural language automation for everything from data AI readiness to modernizing workflows. AWS doubles down on data and storage for enterprise AI. AWS understands that its customers’ data has gravity — and wants to entice them to add more. The company showcased table buckets and queryable metadata updates to S3 that make it an ideal platform for data lakehouse architectures, especially with SageMaker for AI application development. Other updates include FSx for Lustre intelligent tiering and new storage-focused instances with high-speed Nitro SSDs for modern AI applications. Related announcements included federated data strategy with AWS Clean Rooms and a physical data transfer terminal service. Here’s our take on key news from AWS re:Invent by category: AI. AWS continues to augment its AI services across the full lifecycle of genAI. The new Nova foundation model series includes four for languages and two for computer vision. As Forrester predicted in its Predictions 2025 report for cloud computing, AWS announced RAG capabilities, including structured data retrieval, GraphRAG, and Kendra GenAI Index for enterprise data. This broad-spectrum approach includes multiagent collaboration, Bedrock model distillation, automated reasoning, intelligent prompt routing, and multimodal toxicity detection. Data and analytics. AWS pushed the boundaries of data infrastructure with Aurora DSQL, a distributed and scalable SQL database. SageMaker got a boost with Unified Studio for integrated environments and HyperPod for orchestration and governance of model training, fine-tuning, and inferencing. Partners play a role via SageMaker third-party apps and Bedrock Marketplace. Infrastructure. The common theme here is enablement for AI, HPC, and database workloads, with AWS Trainium2 and NVIDIA H200 GPU options and storage optimization in the spotlight. The announced P5en instances with NVIDIA H200 GPUs include third-generation Elastic Fabric Adapters to reduce latency. New storage services include optimizations for analytics and autotiered file storage plus support for Pure and NetApp storage, apparently aimed at VMware migration. Application development. AWS continues to push its “well-architected” philosophy into its stack of cloud-native development and integration capabilities. Enterprises modernizing applications will be able to use services such as Step Functions and EventBridge to orchestrate workflows and connect resources across VPC and AWS account boundaries, easing integration of on-premises legacy apps. Security. AWS initially focused on the security of the cloud, relying on partners to provide the security in the cloud. Today, the AWS security portfolio is much broader. The newly enhanced GuardDuty will help users walk through the MITRE ATT&CK chain, while various AI-oriented security announcements focused on data lineages. AWS made further accommodations for securing multicloud environments, too. Sovereign cloud. AWS emphasized the launch of the European Sovereign Cloud, planned for Q4 2025 and backed by €7.8 billion in investment. This allows AWS to offer a single-provider multicloud environment in Europe. All cloud regions are powered by the secure Nitro hardware; pricing was not disclosed. Cloud sustainability. Power usage effectiveness (PUE) value of AWS data centers has been decreasing, and the announced new data center design is aimed at bringing data centers’ PUE below the market current average. AWS expects the new data center design to translate into a 14% reduction in carbon intensity, a 46% reduction in mechanical energy used, and 35% less embodied carbon. From a silicon standpoint, Inferentia2 now delivers up to 50% better performance per watt than its previous generation while Trainium2 is three times more energy-efficient than Trainium1. Cloud cost management/FinOps. AWS announced a slew of new capabilities, including adding genAI-enabled cost search function with Amazon Q Developer for chatbot-powered cost analysis, deeper anomaly detection with root-cause analysis, and a more accurate AWS Pricing Calculator that can ingest commitment purchases. AWS continues to lead the market in native cloud cost management, though competitor Microsoft Azure is close behind. SAP deployment. AWS and SAP announced GROW with SAP on AWS, enabling rapid deployment of SAP’s ERP solution with AWS’s cloud benefits. This collaboration simplifies the adoption of SAP S/4HANA Cloud Public Edition and introduces new AI-assisted innovations. Customers will benefit from unified billing, existing AWS credits, and enhanced performance with AWS Nitro and Graviton ARM chips. Network performance observability. A long-standing item on many network engineers’ wish lists is finally here: a holistic correlation of cloud networking performance and end-user experience. The CloudWatch Network Monitor solution will monitor network performance between AWS compute instances using flow

Let’s brace ourselves for a hard truth. Trust in marketing measurement is already poor, and left unchecked, it’s poised to get 20% worse. The pain that your organization feels surrounding B2B marketing measurement problems is real. Forrester’s Marketing Survey, 2024, revealed that 64% of B2B marketing leaders feel that their organization doesn’t trust measurement for decision-making. This hurts because marketing is a discipline with credibility that depends on data, facts, and insights, yet many marketing leaders don’t have faith in their company’s measurement when it matters the most. Not having trusted measurement hinders marketing’s ability to get its job done. Optimization of marketing efforts requires data to inform adjustments. That can’t happen when the metrics used to describe performance aren’t trusted. And without measurement to clearly depict marketing’s contribution, securing the budget and resources necessary to drive business impact becomes a losing battle. None of this is new, nor are the well-known contributors to the current state of marketing measurement (they include data quality, technology gaps, and the skills of measurement producers and consumers). All are aspects that B2B organizations continue to work to improve, but unfortunately, many B2B marketers will lose ground in these battles over the coming year. Why Is Measurement About To Get Tougher? We’re predicting that marketing measurement is about to get more difficult because of these compounding market forces: Buying complexity obscures so much. B2B sellers tell us that deal cycles have grown longer. Buyers tell us of the large quantities of individuals now involved in purchasing decisions. Persistent time-lag issues in detecting business impact grow more difficult with lengthened selling cycles. More people interacting with sales and marketing more times places more pressure on measurement systems already struggling to capture and make sense of their behaviors. Until vendor organizations recalibrate their business systems and processes, they will detect a limited portion of total buying interactions and will have to wait longer to understand results. Technology sprawl yields fractured data. The volume of technologies that make up the go-to-market technology stack results in disconnected data sources, and in turn, disconnected data is now a leading analytics challenge. Stitching together a cohesive picture of buyer behavior across these technologies is stretching the resources and skills of analytics teams — and this shows little signs of being alleviated. AI-inflated hope drives an expectation gap. AI has the potential to power meaningful improvements throughout B2B. This promise carries into widespread expectations that better measurement is possible by using AI to make sense of large volumes of data at speeds that humans will never replicate. But the distance between that vision and the current state of B2B marketing measurement should be counted in years, not months. B2B planning, processes and data aren’t yet in shape to meet AI’s potential. Stakeholders of all types will struggle for the foreseeable future to make sense of and develop faith in AI-driven views of performance. Expect a prolonged period of experimentation, missteps, and resets before B2B marketing analytics teams come anywhere close to cracking this code. Measurement can’t keep up with a renewed emphasis on reputation investment. B2B marketing investments have traditionally skewed toward capturing and advancing demand and so, too, has the focus of marketing measurement. But there’s growing recognition that demand efforts are not enough, and selling organizations must do more to influence buyers before they enter active buying cycles. Reputation spend now represents nearly one-quarter of marketing program investments, but we’re not seeing similar prioritization among what marketing leaders measure. Measurement analytics teams currently fall short in the skills and capabilities to measure this area that they’ve traditionally deprioritized. What’s To Be Done? Each of these market forces are larger than measurement, and there’s little that your analytics team can do to hold any of them at bay. What will separate the winning organizations from the rest is how they respond. In the face of these forces, here are a few actions that you can take to enhance your organization’s trust in marketing measurement: Tune your processes to buying complexity. Do the work to make it easier to link buyers to opportunity records, and work to capture not only self-guided interactions but personal ones, as well. Economize the B2B tech stack. Squeeze out duplicative capabilities found in best-in-breed solutions in favor of the broader solutions of platform providers. A more consolidated set of technologies will carry less overhead when it comes to data preparation and consolidation. Set clear reputation objectives. It’ll take time and resources to create comprehensive approaches to measuring reputation. In the meantime, start small by working with stakeholders to be sharp about setting reputation objectives and select a handful of available indicators that can show progress. Pair AI efforts with insight activation. Marketers are right to be excited by the potential of AI. At the same time, there’s a clear need to enable them to work more productively with the analytics already available. Marketing analytics teams need to redirect more of their time toward enabling their stakeholders to drive better results using existing resources. Doing so will better prepare them for the potential that AI is bound to unlock. Read our full Predictions 2025: B2B Marketing, Sales, And Product report to get more detail about how to get ahead in 2025. Set up a Forrester guidance session to discuss these predictions or plan out your 2025 B2B strategy. If you aren’t yet a client, you can download our complimentary B2B Predictions guide, which covers more of our top predictions for 2025. Find additional complimentary resources, including webinars, on the Predictions 2025 hub. Reserve your seat for the upcoming B2B Predictions webinars to hear more insights from Forrester analysts: source

Last year, when Silicon Valley, Signature, and First Republic failed, four out of five US online consumers knew about it. This year, major bank failures have been small, so I had to search for the “Mary Poppins moment.” Still, consumer attitudes about bank failures haven’t changed. Our September 2024 Consumer Pulse Survey revealed this. This year, less than one in five consumers knew about the recent failures of Citizens Bank – Iowa, Heartland Tri-State Bank – Kansas, and Republic First Bank – Pennsylvania. That’s what changed. What’s stayed the same, however, is that: People will line up for their money. The ways people will ask for their deposits back in a run have remained stable. Nearly 45% of US online consumers will appear in person at a branch to withdraw their money. Some will use digital channels, and mobile edged up versus online as a channel this year. That comes as little surprise, as usage of mobile apps has increased over the years. Big still doesn’t necessarily mean better. Even though fewer consumers knew about bank failures, the percentage of them agreeing with the statement that “Larger banks are inherently safer than smaller/regional banks” stayed remarkably steady. The absence of a crisis doesn’t win consumers over to the “too big to fail” argument any more than the presence of one does. Deposit insurance won’t keep the lines from forming. Despite decades of FDIC insurance, consumers still want to get their money back fast. Over two-fifths agree that they’d withdraw all funds if news reports indicated their bank was having difficulties. They fear inconvenience from the FDIC resolving a failure. Like young Michael Banks in “Mary Poppins,” they’d arrive before things worsen and demand their money back. Banks plan to avoid failure. That’s core to their business. As we saw last year, however, rapid shifts in consumer attitudes can quickly put a bank on the ropes. The good news is that bank failures were hard to find (so much so that we couldn’t find one in Europe this year). Will there be more bank failures? Yes. Consumers think traditionally about them. Some will use their app to transfer money, but most will act like we’re in Victorian England: Read the news, line up, and demand their money back. Despite our advances, last year’s lessons remain true: A run on an adjacent bank affects even sound institutions; customers are ambivalent about deposit safeguards; and calming mechanisms may not maintain the status quo. Should you wish to discuss our findings further and you’re a client, schedule a guidance session or inquiry with me. Not a Forrester client? Contact your Forrester account team and tell them, “I want Forrester Decisions!” source

There’s a school of thought that writes most sustainability efforts off as annoying virtue signaling: Consumers with time and disposable income choose to pay a green premium for products that make them feel good, and companies plant trees and recycle coffee cups to make those customers like them. As costs rise, belts tighten, and we grapple with immediate geopolitical threats, it’s hardly surprising that this discretionary veneer of sustainability may be slipping out of favor with consumers, companies, and governments around the world. But those same pressures make the right sustainability initiatives more important than ever. Forrester’s original framing of the green market opportunity explicitly made the point that sustainability can be good business: A combination of macroforces will create a tipping point, after which companies will no longer view environmental sustainability as primarily an ethical responsibility with added benefits to brand and modest cost savings, but as a financial and regulatory obligation they can’t ignore, and more importantly, an unprecedented business opportunity. A truly sustainable business requires two forms of sustainability: the green stuff that sustains the planet and the operational stuff that sustains the business. Forrester predicts that 2025 will be the tipping point, where economic and operational considerations become more significant drivers of corporate sustainability initiatives than regulations and customer sentiment. Prioritize Projects That Help Your Business And Also Happen To Help The Planet Even if your environmental sustainability plans are moving full steam ahead, shift the emphasis of your messaging to employees, customers, and the market to explicitly lead with clear operational benefits: A machine vision system that spots defects in parts moving along an assembly line cuts the cost to your business of expensive scrap or rework. That also reduces consumption of raw materials. Internet-of-things sensors on power-hungry equipment reduce energy consumption and support predictive maintenance models that may extend the useful life of that equipment, lowering energy bills and equipment budgets. That also reduces emissions. Bloomberg calculates that an EV in the US becomes a greener choice than its internal-combustion-engine equivalent after driving about 25,000 miles. It can also be cheaper to operate, with any higher up-front cost amortized over all those miles. So focus electrification efforts on fleets of smaller vehicles (cars and vans) to reduce operating costs. This also reduces emissions. German pump manufacturer Wilo uses excess electricity from rooftop solar panels to power electrolyzers that turn water into green hydrogen. The hydrogen is stored onsite, with fuel cells converting it into electrical energy at times of peak demand. This reduces the load that Wilo places on the German energy grid while also cutting the company’s electricity bill. Virginia-based construction company Basic Construction buys pellets of waste toner from printer-maker Canon’s local factory, using them as a colorant and binding agent for the asphalt it lays on the state’s roads. Canon generates new revenue from its toner recycling operation, and Basic reduces its material costs. The road surface is apparently more durable than before, and the circular economy business model pays for a reduction in consumption of raw materials and emissions at both firms. In late 2022, BASF announced plans to “as quickly as possible and also permanently” downsize operations in Europe. Rising energy prices played a key part in this decisionz and in the company’s increased investment in the renewables-powered Zhanjiang Verbund facility in Guangdong province. Energy costs often matter more than labor costs in modern manufacturing, but business and technology leaders must also consider the cost of moving raw materials and finished goods throughout their supply chain. Emerging technologies play their part in helping manufacturers settle on a multinational Goldilocks model that is neither just in time nor just in case but just right. The need to reduce emissions and wasteful consumption of resources has not gone away, but the “green” debate might be seen as polarizing for your customers. If this is the case, don’t lose sight of the green market revolution’s promise of bettering planet and business. Most companies would be wise to lower the volume on their virtue signaling while quietly getting on with the projects that benefit both their shareholders and (whisper it) the planet. source