Thomson Reuters  is a global AI and technology company that provides trusted data and information/business intelligence to professionals across 3 different industries: (1) Legal; (2) Tax and Accounting; and (3) News & Media. In business since 1851, the company currently has over 25,000 employees worldwide. In 2023, Thomson Reuters (TR) and Sojourn Solutions (Sojourn) began an ambitious project to optimize the Thomson Reuters marketing technology stack, seeking to create an effective, efficient, and centralized operating model for long-term stack management.  The roots of the change go back to 2021, when TR recognized the need to build a consolidated marketing operations group. Prior to that, TR’s marketing operations were embedded within each of its different business units, which led to a fragmented martech stack that nobody had centralized management and control over.  A Difficult-to-Manage Martech Stack   The legacy TR martech ecosystem was complex, vast, and difficult to manage and/or map. It was made up of 125 + apps and platforms, and was managed via 4 databases across multiple teams, preventing visibility into TR’s complete stack and stack investment.  TR had different silos of people, processes, and martech tools across its three main business units, with each having martech specialists embedded within them. TR’s different teams were using its primary marketing automation platform (MAP) in very different ways and for different use cases. Besides challenges around stack scale and visibility, other major martech stack challenges included: 1. Lack of detailed, centralized reporting,  especially re: data flows, integrations, and technology performance, meaning that gaining necessary visibility into stack capabilities and costs was difficult-to-near-impossible. 2. Limited visibility into stack-related costs.  A fragmented tech stack made it difficult for TR to determine ROI and track software costs as business units funded platforms from their own (separate) budgets. 3. Manual updates of the ecosystem were time-consuming and prone to errors,  causing problems around data quality that often went unrecognized/unreported for long periods of time, negatively impacting stack performance and costs.  4. Lack of comprehensive integration maps for the entire martech ecosystem,  making it harder to recommend new martech because redundancies and/or gaps in capabilities and tools might go unrecognized. Defining Success TR knew it had to eliminate its siloes and different reporting structures in order to get on the same page. Related to that, it had to have standardized tools that would also be flexible enough to accommodate differing needs and use cases.  After evaluating the challenges, TR and Sojourn developed some key goals for the transformation project. including: 1. A Need to Gain Greater Visibility:  TR wanted to construct an accessible, shared directory of martech capabilities, applications, integrations, spend and renewals to support stakeholders across the Thomson Reuters organization. The objective here was to introduce transparency and efficiency into a process of martech acquisition, implementation, and management that had previously been fragmented. 2. A Need to Streamline its Stack:  TR wanted to better assess platform performance and leverage those assessments to streamline and optimize the number of martech products/tools it was using, thus helping to better manage costs and drive stack capabilities. 3. A Need to Develop New Approaches to Workflows and Resource Allocations:  TR wanted to find a new way to objectively assess the martech it was using, and rethink internal workflows and resource allocations to optimize its stack. Defining the Solution Sojourn collaborated with the TR team to design and implement a solution to the challenges above. The major components of that solution were: Deploying an organizing platform.  TR and Sojourn decided to deploy CabinetM , a user friendly, automated martech management platform. In implementing the solution, Sojourn supplied strategic support and its expertise around marketing operations in order to develop a Platform Performance Scorecard and martech governance recommendations (more specifics on those below). The CabinetM platform organized TR’s stack and apps/tools in one place, increased organizational visibility, and documented their entire martech ecosystem, as well as clearly defining and delineating technology owners, integrations, and contracts. These assets had previously been spread out across multiple spreadsheets and in different databases.  Creating cross-functional alignment around the stack.  To make the newly-organized structure work effectively, TR collaborated across multiple departments and functions to track, optimize, and report on TR’s martech infrastructure, expense, renewals, adoption, and strategy.  Gaining visibility and streamlining its martech stack.  In the end, this collaborative process pulled together martech tools (CabinetM), people, and new processes/workflows. TR gained the ability to strategically streamline its martech, while developing new methods and tools to understand and track tech capability/functionality. Working across its 125+ technologies, and 5+ stakeholders, TR was able to create a one-stop shop for their martech assets within CabinetM. They gained full visibility across the organization to support better decision-making around martech stack performance and investments. Results of the Project 1. TR built a visual directory of martech capabilities, applications, integrations, spend and renewals.  This martech directory listed over 175 martech platforms that were either active, under consideration, or retired. In addition, TR:  Established its stack mechanics, architecture and martech landscape layer categories. Determined and established baseline product attributes and incorporated pertinent information. Captured integration connections and details. Captured and created details as they’re forming to capture its capability models. Built a historical record of all platforms and activities regardless of status for future use. 2. TR shifted to a capability model.  TR moved from managing its martech tools under the umbrella of its separate business units to a model that now assigns managers based on the capabilities that a particular platform might support. For example, it has a manager who supports the Web Operations team and the tools they need. TR has another manager who supports the demand generation team and the tools they need. So in theory, two people are managing one platform, but they're managing it to drive optimal value for the stakeholders who use it and for the specific use cases of those stakeholders.  3. TR and Sojourn developed a Platform Performance Scorecard  to enable TR’s central team to support their technology review process across all its platforms.  The Performance Scorecard described the top business use cases each tool addressed, as well as ratings for how well the tool was actually addressing those specific use cases. The Scorecard also provides relevant information about the vendor, levels of user support, contract/renewal information, as well as the vendor’s future roadmap for the tool/platform.  The Platform Performance Scorecard helps fuel better, more informed discussions within TR when decisions need to be made about its  martech stack. 4. Sojourn recommended an improved Martech Request structure  for TR including a consolidated, automated new martech request / renewal request process using Workfront, an existing tool in their stack. The existing request process was scattered across teams and sources, and Sojourn saw an opportunity to improve it using an existing tool to centralize the net new requests, pilots, and renewals as applicable. In addition to workflow effectiveness, a centralized model provides better reporting and actionable insights for improved decision-making.  Reaction from Thomson Reuters Here’s some final words on the project from Thomson Reuters: The solutions and the new, consolidated structure we’ve built is going to allow us to expand, grow, and keep infusing other areas like AI, where Thomson Reuters is currently putting lots of emphasis. – Kim Kraetzner, Thomson Reuters’ Marketing Operations & Technology Manager. It's great to now see our Martech SMEs having the time to concept TR's “tomorrow position.” Because of our streamlined management model and process, they can focus on higher value activities – and we can pivot a lot easier than we used to. – Carol Mendenhall, Thomson Reuters’ Senior Director of Marketing Operations P.S. The Project described above has been submitted as a presentation topic at The Martech Weekly’s World Martech Forum  this August in San Francisco. (Fingers-crossed!) In addition, the Project was submitted for a The Stackies 2024: Marketing Tech Stack Awards . See TR’s submission here , and explore TR’s martech stack  yourself!  Last, but certainly not least, TR’s Carol Mendenhall  shared her expertise at the 2024 Martech Conference  in a session titled “How MOps should prepare their stacks and teams for customer experience-based AI. Watch it on-demand now . Learn more  about how Sojourn Solutions can help take your Marketing Operations team martech management and performance to the next level. Questions? Contact us  today.

Citeline , the world’s leading provider of business intelligence in the pharmaceutical and medtech industry, had to set up a completely new Martech infrastructure/Tech stack which involved a new Eloqua marketing automation platform (MAP). What catalyzed the change was Citeline’s being sold by its parent company Informa in 2022. Citeline, formerly Pharma Intelligence, was ultimately acquired by business intelligence giant Norstella, forming a $5 billion global firm. Citeline had to rebrand, becoming one of five brands under the Norstella umbrella. Citeline needed to rapidly de-couple its infrastructure away from Informa. During the transition phase, the Citeline team quickly understood that if it moved forward with both Eloqua and Salesforce Marketing Cloud (SFMC), its legacy platforms, it would incur substantial implementation and maintenance costs, hindering the firm’s progress moving forward. The Big Question The big question Citeline confronted, and which Sojourn helped them answer in the affirmative, was: “Could Citeline manage its operations and continue to effectively run its business without the license costs and complexity associated with SFMC, by leveraging Eloqua alone?” Citeline decided to sunset its SFMC license and migrate to a single instance of Eloqua, migrating all its data, assets, configurations, processes, etc. to the new instance. With new tech being implemented across the Citeline corporate structure and across Citeline’s customer/CX journey, the pressure for Marketing to rapidly launch a new Eloqua instance and seamlessly migrate from its existing/legacy systems was high. Citeline wanted the entire Eloqua migration project completed within an aggressive timeline of 6 months, with the overarching goal of ensuring minimal business impact/revenue disruption. Timing was also important because Citeline faced contractual penalties that would get triggered if it continued to depend upon its legacy infrastructure from Informa. Challenges to Project Success This Eloqua migration initiative marked a significant shift in Citeline's tech architecture, encompassing a new Sales CRM, MAP instance (Eloqua), and Website.  Some challenges Citeline faced in migrating to the new Eloqua instance included: No flexibility on program milestones due to the entire Citeline technology stack being switched at the same time. Failure to switch on time would have resulted in massive costs. Implementing new technology, including a single instance of Eloqua, involved extensive data migration and integration of third-party apps/platforms. All legacy processes and workflows needed to be brought into alignment with the capabilities of the new Eloqua instance. Complex (highly scripted) email campaigns needed to run without disruption to either customers/subscribers or business revenues. Removing SFMC meant replacing workflows and processes, and connecting a new App (Instant Marketing) to Eloqua. Ensuring that all agencies/partners worked well together in order to minimize internal disruption for the Citeline team, which needed to: (1) continue performing their day jobs and (2) prove to their new Norstella investors that they could still generate revenue as this massive transformation was happening. The Citeline team needed to be rapidly trained and enabled to work in the new Eloqua framework, ensuring seamless operational continuity. First Steps: Designing a Customized Eloqua/MAP Solution Citeline brought in Sojourn Solutions as a project partner. In collaboration with the Citeline team, Sojourn swiftly organized and facilitated discovery sessions to create a streamlined blueprint/project framework for an Eloqua roll-out, crafting related timelines and project priorities. High among the project priorities was ensuring flexibility within any planned martech solution in order to accommodate potential new requirements in a fast-moving, rapidly-evolving program. Sojourn, for example, provided deep technical expertise around architecting new ways of delivering Citeline campaigns and integrating with the new CRM and website.   Implementing the Solution The Citeline-Sojourn partnership successfully implemented the new Eloqua instance. In order to minimize disruption to Citeline’s revenue-generating Insights email product, the project team worked successfully to eliminate email deliverability challenges. This ensured email reach and customer engagement, not to mention business/revenue continuity for the critically-important Insights email product.  Citeline’s Insight email was driven by customized content preferences pre-defined by email subscribers. So, the project team collaborated with a development agency to ensure Salesforce Marketing Cloud emails could be created and run within the new Eloqua instance using RSS-type functionality. This would now be delivered through the Instant Marketing app/add-on. Sojourn also provided additional development support to standardize data and support field value updates. Project Deliverables Project deliverables were focused on data migration, asset migration, app/platform integration, new processes and templates launched, as well as user enablement. Here’s a brief summary: 1. All relevant data was migrated from Citeline’s legacy systems into the new Eloqua instance in a timely and accurate fashion.  2. The following Citeline assets were migrated into a new Eloqua framework: 8 ‘always on’ forms including Landing Pages 14 ‘always on’ Campaign Canvases and approximately 35 inflight Campaign Canvases 100 ‘always on’ Emails and approximately 95 inflight Emails 3. The following processes were built: Forms and Lead Score to Salesforce Bi-directional syncs Cleansing processes 4. The following templates were created: 4 key Form templates 12 Campaign Canvas templates 50 Email templates 5. Other deliverables: Users were trained and enabled (see details below) IP warming was completed to ensure quality and business continuity + Preference Center for email subscribers to personalize content Documentation was provided Enabling People and Processes In order to ensure project success and maintain the new platform after its go-live date, Sojourn trained the internal Citeline team on new processes and workflows. It also supported Citeline’s Product Marketing and Campaign teams after go-live by providing hypercare. This included daily platform monitoring to proactively manage any potential problems/issues that might arise and potentially disrupt business continuity. Hypercare also involved daily calls with the project team, including Citeline’s internal people as well as relevant external agencies. Even after the go-live date and in order to support Citeline’s full operational continuity, Sojourn helped support ongoing Eloqua technical and integration requirements. It also delivered hands-on campaign reporting and analysis to Citeline as a way to ease the pressure on Marketing during go-live. KPIs of Project Success: Outcomes The success of the Eloqua migration project was indicated by the following: 1. A single instance of Eloqua was successfully put in place by early July 2023, less than 6 months after the March project kick-off and well within Citeline’s desired timeline. Significant costs (related to licenses and development needs) related to continuing with the legacy SFMC platform were avoided, including an 88% savings on licensing-related costs, as SFMC was sunsetted. 2. Existing SFMC data, journeys and campaigns were successfully migrated and running 'as is’ in Eloqua by June 28, 2023, including 1.6 million emails per month with up to 20 pieces of content each (dynamic content where each recipient can receive different news articles direct from the website). 3.The project developed a Citeline-owned Eloqua instance and migrated it from Informa business systems so Citeline could transition its corporate structure from Informa to Norstella. 4. The project team coordinated the migration with Salesforce workstreams to successfully minimize disruption for Citeline’s commercial team and customers. 5. Because of the low code and no code nature of the solution, software complexity was reduced and Citeline no longer needed a dedicated developer. Marketers saved about half of their time and were able to manage the work with user-friendly functions such as “drag-and-drop.” A Word from Citeline Chris Fowles, Citeline’s Sr Director Technology, Sales & Marketing Business Partner, explained the benefits of the Eloqua migration project this way:   The project goals were achieved, which included getting Citeline away from Informa as well as having us be in control of our own infrastructure and destiny. The initiative was about keeping our business up and running at a time of rapid change. We wanted to avoid having any operational downtime, keeping leads and revenue flowing. We were also hoping not to take a hit to our revenues as we moved our infrastructure away from Informa. Delays would have cost us. Commercially, we actually grew our revenues last year as the project happened, and our number of leads generated have only continued to grow. Regarding the process of working with Sojourn, Fowles said:  Where Sojourn stands above the rest of our partners is in their flexibility. When the project requirements and timelines shifted, Sojourn never made managing these new requirements seem inconvenient to them, although we knew it was indeed inconvenient. At the end of the day, I still don’t know how we managed to do it all in time and within budget, but Sojourn was a big part of that success.  Learn more about how Sojourn Solutions can help improve your Marketing Automation - as well as your Marketing Operations - or feel free to reach out to us today.

Since the joint venture between Virgin Media and O2 in 2021, the combined company, VMO2, has been on a transformative journey. At Sojourn Solutions, we have had the privilege of working alongside their Marketing Operations team to support this transformation - helping to streamline operations, optimise costs, and strengthen in-house capabilities. The result? A high-performing, data-driven digital marketing engine that’s helping VMO2 Business deliver measurable results and drive continuous improvement. From the outset, the focus was clear: create a unified brand and marketing strategy across the combined Virgin Media and O2 business customer base. Central to this was the consolidation of marketing operations, bringing together disparate systems, teams, and technologies. Working closely with VMO2, we helped define a target operating model that would enable the business to shift from reliance on external agencies, to an in-house team with deep expertise across paid media, SEO, and data analytics. As Pedro Da Silva, Head of Digital Media & Marketing Operations at VMO2 , noted: “ By in-housing these key capabilities, we’ve not only reduced costs but gained greater control over our digital marketing efforts. We can now act with agility, responding in real-time to insights and delivering more targeted, efficient campaigns .” A critical aspect of this transformation was ensuring the right MarTech foundation. The consolidation of customer and prospect data, alongside the integration of CRM, MAP, and analytics systems, laid the groundwork for a robust and scalable marketing operation. With the support of Sojourn Solutions, VMO2 implemented a comprehensive tagging and tracking strategy, enabling the team to capture and leverage data across channels more effectively. “ Getting the right foundations in place was key, ” said Da Silva. “ 2023 was about consolidating and optimising our data and processes. Now, in 2024, we’re seeing the impact of that work come to life, with integrated, data-driven strategies that allow us to engage more meaningfully with our audience. ” In addition to optimising digital media and marketing technology, VMO2 introduced new tools such as Rev.Up for business intelligence and Visitor Intelligence for lead tracking. This enabled deeper insights into customer behaviour and allowed for more precise targeting. The shift from a campaign-specific approach to a holistic, always-on strategy has made a significant difference. “ We are building a performance marketing team that is not only data-informed but data-driven. This shift has moved us from being seen as a support function to a strategic partner within the organisation, ” Da Silva added. “ And the work never stops—continuous optimisation and improvement are now part of our DNA. ” At Sojourn Solutions, we are proud to have supported VMO2 Business on this journey, helping them to consolidate, standardise, and elevate their digital marketing and MOPs capabilities. The results speak for themselves: improved cost efficiency, reduced reliance on external agencies, and a performance marketing team that is driving significant business impact.

AI has shaken the marketing world, changing the way businesses connect with customers, optimize campaigns, and drive growth. But while the buzz around AI is everywhere, the real question is - are your Marketing Operations actually ready to use it effectively? AI isn’t just another shiny new tool you can plug in and expect magic. It requires strong processes, clean data, and a team that knows how to work with it. So, is your Marketing Operations team set up for success with AI? Let’s break down what it really takes to be AI-ready, the common roadblocks businesses face, and how you can set yourself up to embrace AI. How AI is changing Marketing Operations AI isn’t just a trend - it’s becoming a must-have in modern Marketing Operations. It’s changing how teams work by automating tasks, providing deep insights, and delivering hyper-personalized customer experiences. Here’s how AI is already making an impact: Personalization at scale  – AI helps you understand your customers better, predicting what they need before they even know it. Smarter decision-making  – AI analyzes massive amounts of data instantly, helping marketers make better, data-driven choices. Efficiency boost  – Say goodbye to repetitive tasks. AI automates them so your team can focus on strategy and creativity. Better insights  – AI doesn’t just track metrics; it finds patterns and trends that humans might miss. AI-Powered chatbots & assistants  – These tools can answer customer questions, generate leads, and even guide prospects through the sales funnel. While all of this sounds great, AI isn’t a plug-and-play solution. It needs the right foundation to work effectively. Are you AI-ready? Key areas to assess Before diving into AI, take a step back and assess whether your Marketing Operations are actually ready. Here are the major areas to consider: 1. How structured are your marketing processes? AI thrives in organized environments. If your marketing workflows are all over the place, AI won’t be able to do its job properly. Ask yourself: Are your campaigns well-documented and structured? Do you have a clear lead management process? Is customer journey mapping already a part of your strategy? How are you measuring performance? 2. Is your tech stack AI-friendly? AI works best when it integrates seamlessly with your existing marketing tools. If your tech stack is outdated or fragmented, AI won’t be able to deliver its full potential. Consider: Are your current tools compatible with AI-driven features? Can your systems integrate with AI-powered analytics and automation platforms? Are you already using AI capabilities within your martech tools? 3. Is your data clean and well-managed? AI runs on data - but if your data is messy, you’ll get messy results. Many businesses struggle with outdated, inaccurate, or siloed data. To get AI-ready, you need: Clean, well-organized customer and marketing data Clear data governance policies Compliance with data privacy regulations (GDPR, CCPA, etc.) 4. Does your team have the right skills? AI doesn’t replace people - it enhances their work. But your team needs to understand how to use it effectively. Ask: Do your marketers have basic AI and data analytics skills? Have they been trained on AI-powered tools? Is there a culture of data-driven decision-making? 5. Are you already leveraging automation? AI isn’t a replacement for marketing automation - it builds on it. If you’re still handling things manually, AI will be harder to implement. Consider: Are your email, ad, and content workflows automated? Do you use predictive analytics for lead scoring? Is customer journey automation already in place? The common challenges in adopting AI Even if you tick all the boxes above, integrating AI into your Marketing Operations comes with its own challenges. Here are a few common ones: 1. No clear AI strategy Many businesses jump into AI without a roadmap. AI needs to be aligned with your marketing goals - otherwise, it’s just an expensive experiment. 2. Bad data Data silos, duplicate records, and poor labelling can render AI useless. AI can’t make good decisions if the data feeding it is flawed. 3. Resistance to change Let’s be honest - AI can feel intimidating. Some team members may fear job loss, while others may struggle to adapt to AI-driven workflows. Change management is key. 4. Unrealistic expectations AI isn’t a silver bullet. It takes time to implement, fine-tune, and optimize. Companies that expect immediate results are getting frustrated and giving up too soon. How to get your Marketing Operations AI-ready If your Marketing Operations aren’t quite ready for AI yet, don’t panic. There are concrete steps you can take to get there: 1. Run an AI readiness audit Before diving in, take stock of where you stand. Evaluate: Your Marketing Operational maturity Your marketing processes and workflows The quality of your data Your existing tech stack Your team’s AI skillset 2. Clean and unify your data Make sure your data is structured, accessible, and free of duplicates. This will be crucial for AI-powered insights. 3. Invest in training AI is only as good as the people using it. Provide your team with training on AI tools, data literacy, and automation best practices. 4. Start small with pilot projects Rather than trying to overhaul everything at once, test AI with a small project first. Track its impact, refine your approach, and scale up from there. 5. Align AI with business goals AI should enhance your existing strategies, not replace them. Make sure your AI initiatives support your broader marketing objectives. Our AI Readiness Assessment: Your roadmap to AI success Not sure if your Marketing Operations are ready for AI? That’s where our AI Readiness Assessment Service  comes in. We help businesses assess their AI readiness by evaluating: Your marketing processes and operational maturity The strength of your existing tech stack Your team’s AI skillset and overall readiness The quality and structure of your data Your current automation capabilities With our AI Readiness Assessment, you’ll get clear insights to prepare your business for AI-powered marketing success and we can work with to develop a roadmap for platform selection and implementation. Ready to take the next step? Let’s assess your AI readiness and build a strategy for smarter, more efficient marketing. Discover our AI in Marketing Operations Services Download our FREE whitepaper

Smurfit Westrock , which operates in 40 countries with 100,000+ employees, is a global leader in sustainable paper and packaging solutions. The B2B company has grown over the years both organically and by acquisition. While Sojourn Solutions has been helping Smurfit Westrock transform its marketing operations since 2017, a primary focus of the last 3 years has been on lead management. We recently spoke with Hee Suk Ko , Director of Enterprise Marketing for Smurfit Westrock, about the company’s lead management challenges, and how they were tackled. What follows is an excerpted version of that conversation:  What were the biggest challenges Smurfit Westrock faced around lead management? Ko: Our primary challenge was limited visibility into lead progression through the funnel. Previously, leads would be handed off to sales without a unified process for follow-up or optimization of the lead-to-conversion process. While certain divisions and teams may have had more mature processes, holisitically, we lacked comprehensive visibility to share learnings and improve our lead quality, lead velocity and closed/won deals.  What was the impact of that previous lead management process on (1) the relationship between marketing and sales, and (2) the customer experience?  Ko: The lack of visibility resulted in inconsistency in both the relationship between marketing and sales and in the customer experience. Some sales team members were eager to receive leads regardless of quality, while others might disregard leads they deemed insufficient. This disparity created misalignment in the customer experience where marketing communications often failed to align with the actual buyer journey and sales interactions. What needed to change?  Ko: We needed to standardize our approach and definitions regarding lead quality and scoring across the organization. Despite having a unified CRM, its usage and data quality were inconsistent. We had to develop a formal framework for lead quality and scoring and streamline the process for sales to follow up on leads, ensuring we – both marketing and sales – could track whether leads were accepted or not as well as their dispositions.  How did you go about working with Sojourn to gain more visibility into the customer journey? Ko: We began by consolidating data from our CRM and marketing automation platform to create initial enterprise marketing attribution dashboards. We then focused on standardizing the definition of a marketing qualified lead (MQL) and tracking key metrics such as MQL acceptance rates, contact rates, and conversion opportunities with each business unit and corresponding sales leaders.  This process evolved into a more holistic approach, incorporating data from additional sources like our web analytics platform and internal financial systems to enrich our understanding of our prospects and customers.  Note from Sojourn:   Smurfit Westrock’s Eloqua-Salesforce integration was updated to match its current business needs (each campaign response would create a new Lead (MQL) in Salesforce.).  The work included changing the lead model, lead assignments, and adding new fields for Lead/Opportunity objects to the integration, and adjusting the sync'd campaign fields.  Overall, these changes meant giving Sales greater context into Leads, and more rich data being available for Marketing to use in segmentation and scoring.  How did these changes impact how marketing and sales worked together? Ko: The improved visibility has fostered a more collaborative approach between marketing and sales. We’re now more intentional and data-driven in our resource allocation for external activities such as trade shows and campaigns. Collectively, we have a better understanding of our customers’ buying journeys, which allows us to identify gaps, improve channel performance, and optimize our targeting. This improved visibility ultimately drives better orchestration, engagement, and conversion rates.  What changes were made with your technology infrastructure and data? Ko: We enhanced our existing CRM-marketing automation platform integration to provide sales with more comprehensive and up-to-date lead information relevant to their division and end market segments. We implemented a contact validation tool and a thorough data cleanup process. Additionally, we optimized our form fields to ensure sales had sufficient information to effectively evaluate and follow up on leads. While we have made great improvements, we recognize that this is an iterative process as we introduce new data sources, technologies, and teams.  Note from Sojourn:  We created dashboards to analyze marketing's influence on revenue, while allowing analysis of channel, buyer role, and buyer journey.  All analysis is split by division giving insight into regional/solution and product differences. Sojourn's recommendations have covered:  (1) optimization of targeting by buyer role in the buying group, (2) optimization of segmentation, including earlier identification of contacts and increasing use of automation to manage contacts across the buying group, (3) optimization of channels, including which channels to prioritize because of their impact on pipeline and revenue. What have been the main benefits of the transformation? Ko: Tangibly, we’ve achieved significant cost and time savings that will compound over time. We now have greater visibility into the buyer journey and marketing influence, all while tracking conversion rates by division to have more informed decision-making conversations with our sales leaders. This improved visibility has also built trust in our data as well as within marketing and sales relationships, both of which were previously lacking and/or inconsistent across teams.  Marketing and sales teams now engage in data-informed conversations about lead prioritization and lead allocation. There’s been a cultural shift, with a heightened appreciation for lead management and tracking capabilities. The ability to have a 360-degree view of customers has become increasingly valuable, especially as we continue our focus on first-party data and consider factors beyond just closing deals, such as payment behavior and cross-selling opportunities. Note from Sojourn: $250K cost savings in FY24 when compared to implementing a productized attribution tool. 85% reduction in event data processing time (7 days reduced to 24 hours), thus speeding up follow-up emails and sending more timely, relevant communications. Open and click through rates improved 14.78% and 17.80% respectively, showing a positive trend in email engagement. What capabilities has Sojourn contributed to Smurfit Westrock? Ko: Sojourn brings two critical areas of expertise: 1. technical knowledge of our tools, integrations, and backend systems and 2. a strategic partnership that understands the nuances of our organization. Our day-to-day partners at Sojourn have been able to adapt to our needs, provide best practices, and offer insights from their consultative experiences while recognizing our unique challenges and requirements at Smurfit Westrock to build authentic relationships internally with sales and externally with our customers.  Learn more about how Sojourn Solutions can help improve your   Marketing Operations  - or feel free to   reach out  to us today.

Understanding how marketing efforts influence buyer behavior is critical in today’s complex B2B landscape. For Smurfit Westrock, a global packaging leader, the challenge lay in accurately tracking marketing performance and justifying budget allocations. Historical decisions and anecdotal feedback drove marketing investments, leaving significant gaps in data-driven decision-making. This article covers how Sojourn’s tailored marketing attribution solution transformed their approach. The challenge: Bridging the attribution gap Smurfit Westrock faced several hurdles in their marketing attribution journey. A significant issue was the inability to validate the impact of marketing campaigns on revenue generation. Without robust tools and processes, the marketing team struggled to connect specific campaigns and channels to tangible business outcomes. This lack of visibility made it difficult to allocate budgets effectively or prioritize initiatives. Additionally, siloed and inefficient systems exacerbated the problem. Salesforce, for instance, was underutilized, with poor contact role usage against opportunities. Meanwhile, Eloqua’s Contact-Level Reporting (CLR) introduced blind spots in data, further limiting insights into channel performance. These systemic issues resulted in marketing strategies that relied heavily on anecdotal evidence rather than data-driven insights. To make matters even more challenging, the sales and marketing teams were not operating in harmony. The large, decentralized sales organization functioned independently - limiting marketing’s ability to influence outcomes and optimize strategies. The absence of actionable insights compounded the difficulty, leaving key metrics like channel ROI and campaign influence unmeasured and unoptimized. Our solution: A tailored marketing attribution framework To address these challenges, Sojourn developed and implemented a comprehensive marketing attribution solution tailored specifically to Smurfit Westrock’s needs. The first step was integrating data from multiple sources, including website tracking, offline events, marketing automation identity resolution, and CRM order data. This integration created a unified attribution database that provided a more complete view of the buying journey and marketing performance. Custom channel definitions were established to ensure accurate tracking and reporting. UTM parameters had been optimized for some time and now were categorized to align with Smurfit Westrock’s unique requirements. This customization allowed for greater precision in measuring the performance of individual channels and subchannels. In addition to these technical solutions, Sojourn introduced advanced analytics and delivered a monthly service to analyze marketing performance across various buying stages for each division. These insights informed strategic recommendations, enabling Smurfit Westrock to focus on high-impact areas and implement a roadmap for continuous improvement. Visualization was a critical component of the solution, with dashboards built in Looker Studio. These dashboards provided an accessible way for teams to interpret data, identify performance gaps, and take targeted action. Example dashboards Key results and outcomes The impact of this tailored solution was significant: Identified marketing gaps by division : Insights revealed opportunities to improve channel performance, target buying group members earlier in their journeys, and refine segmentation strategies. Cost savings : Smurfit Westrock realized savings of $250,000 in FY24. This was achieved by implementing a customized attribution solution rather than investing in a productized tool, which would have required additional implementation costs and a dedicated data analyst. Enhanced buyer journey understanding : The solution provided a deeper understanding of the buyer journey, allowing Smurfit Westrock to align marketing strategies with revenue goals more effectively. Actionable dashboards : The introduction of accessible dashboards empowered various marketing teams to collaborate more closely, fostering a shared understanding of performance metrics and strategic priorities. Insights for continuous improvement Throughout the project, several key learnings emerged. One critical insight was the importance of evolving attribution reporting to address blind spots and meet changing business needs. Regular engagement with stakeholders was essential in ensuring that the solution remained relevant and actionable. Another lesson was the necessity of pairing attribution solutions with ongoing analytics support. Attribution alone cannot drive results; it must be complemented by expert analysis to translate data into strategic actions. Cultural and understanding challenges also had to be addressed. Establishing a shared understanding of key metrics, such as the distinction between lead-level and touchpoint reporting, required consistent communication and education. The project also highlighted the value of visualization in gaining stakeholder buy-in. Visual representations of the buyer journey proved instrumental in helping both strategic and operational stakeholders understand and support the attribution solution. For detail-oriented team members, an architecture diagram and glossary were essential tools for clarity and alignment. Future enhancements: A path forward While the solution delivered significant improvements, opportunities for further refinement remain. Funnel optimization dashboards could provide deeper insights into conversion rates, equipping sales and marketing teams with tools to collaborate on improving performance. Advanced forecasting tools could help predict the impact of customer journey gaps on future pipeline and revenue metrics. Updating end-market dashboards to track engagement and audience growth is another potential enhancement. These updates would ensure that the solution continues to evolve alongside Smurfit Westrock’s needs, delivering sustained value over time. A collaborative success story This Smurfit Westrock case exemplifies the transformative power of a tailored marketing attribution solution. By addressing specific challenges and integrating data across systems, Sojourn enabled the company to transition from anecdotal decision-making to a data-driven strategy. The cost savings, improved insights, and enhanced collaboration between divisional marketing teams underscore the solution’s effectiveness. For businesses looking to optimize their marketing efforts and align strategies with measurable outcomes, a customized attribution framework is a game-changer. Smurfit Westrock’s success story serves as a compelling example of what’s possible with the right approach to marketing attribution. The benefits of integrating AI with your Marketing Operations

The Challenge A national telecomms client that we've worked with for a number of years and provide deliverability services to, were proactively alerted by ourselves to a significant decline in their "Sender Score" - a critical metric for email reputation. This drop started to lead to increased email rejections, adversely affecting their communication with customers and overall business operations. Our Approach To address these issues, we implemented a comprehensive strategy: DMARC implementation on subdomains : We extended DMARC policies to all relevant subdomains to enhance email authentication. DNS best practices alignment : Identified and implemented additional DNS adjustments to align their infrastructure with current best practices. Legacy configuration resolution : Addressed the outdated practice of using the same domain for both their sending IP and secure microsite, providing guidance to modernize this setup. IP rewarming & monitoring : Established a daily monitoring process to manage and rewarm their IP, stabilizing their Sender Score. Database health & sending strategy : Engaged in discussions about database hygiene and batch email sending, leading to improvements in their email marketing strategy. The Results Sender score restored : Returned to the upper 90s and has remained stable. Reduced rejection rates : Emails are now consistently reaching inboxes with minimal rejection. Improved deliverability : Overall email performance has significantly improved, increasing customer engagement and response rates. Future-proofed infrastructure : Updates have ensured their email system is aligned with current best practices, reducing future risks. Client Sender Score Conclusion By addressing technical gaps and refining the clients email infrastructure, we successfully restored and stabilized their email deliverability. This project also facilitated ongoing improvements in database management and sending practices, ensuring long-term success. Need to improve your email deliverability? Let’s talk.

Let’s face it: the traditional way we’ve been handling leads in B2B marketing, specifically Marketing Qualified Leads (MQLs), is starting to drastically show its age. For years, MQLs were the Holy Grail, the go-to metric to determine which leads were "sales-ready." But as buyer behavior evolved and new technologies have emerged, it’s become clear that MQLs are no longer the best way to measure lead quality. So, why the shift? Todays buyers are smarter, more self-sufficient, and don’t always follow the neat, predictable paths that MQLs were based on. The rise and popularity of MQLs Before we get into why MQLs are falling out of favour, let’s quickly rewind to when they were first introduced. MQLs were once the magic ticket for B2B marketing teams. An MQL was essentially a lead that had shown interest in your brand, whether by downloading an eBook, attending a webinar, or clicking on a CTA. The theory was simple: the more a lead engaged with your content, the closer they were to making a purchase , right? In theory, MQLs were great. They provided a clear, data-backed way to tell marketing and sales teams, "Hey, this lead is worth pursuing." Sales teams could focus their energy on people who seemed interested, and marketing teams could measure their success based on the number of MQLs they generated. This alignment was golden for streamlining B2B sales cycles. But here’s the catch: the way MQLs were defined and used was often too simplistic, and they didn't always mean a lead was ready to talk to sales. While marketers celebrated their ability to generate a ton of MQLs, the quality of those leads was sometimes questionable. Over time, teams began to realize that simply counting MQLs wasn't the best indicator of future sales. Why MQLs are no longer effective The evolution of buyer behavior Let’s start with the obvious: buyer behavior has drastically changed. In the past, prospects would land in your lap after a few clicks on your website or a webinar sign-up. Today, they’re researching solutions, comparing competitors, and reading reviews long before they even think about talking to a salesperson. This shift has fundamentally changed how companies should approach lead qualification. MQLs are no longer an accurate reflection of where someone is in their buying journey. Today, buyers often don’t need to interact with your brand before they make a purchase decision. They’ve already gathered enough information online to make up their minds, often bypassing the traditional sales funnel. The problem with lead scoring At the heart of the MQL model was lead scoring - essentially assigning points based on a lead's engagement with your content. But as digital marketing evolved, lead scoring became a bit of a guessing game. Lead scoring models were often based on a set of arbitrary rules that didn’t really reflect the true intent or purchasing power of a lead. For example, someone might download an eBook but still have no real interest in your product. On the flip side, someone could be engaging with your content without clicking on a CTA, but they might be closer to making a purchase. This is where MQLs fall short. Lead scoring doesn’t always accurately capture buyer intent, which is crucial in today’s B2B world, where deals can be complex and long-cycle. The disconnect between sales and marketing Another issue with MQLs? The ongoing disconnect between sales and marketing teams. Marketing’s job was to generate leads, and sales’ job was to close them, right? The problem was that marketing teams often flooded sales with MQLs that weren’t truly ready for a sales conversation. In fact, some studies have shown that as much as 80% of MQLs were unqualified for sales, resulting in wasted time and resources. Salespeople, tired of sifting through low-quality leads, started to view MQLs as a distraction rather than a useful tool. And when marketing and sales aren’t aligned, it’s bad news for both teams - and for the bottom line. Quality vs. Quantity The focus on generating large volumes of MQLs led many B2B organizations to prioritize quantity over quality. Sure, you could generate hundreds or even thousands of MQLs, but if they weren’t properly qualified, you were simply wasting resources. B2B marketing has shifted. Instead of aiming for a high number of MQLs, companies are focusing on high-value, highly targeted accounts that are more likely to convert into long-term customers. This is a major reason why MQLs are losing relevance: marketers are realizing that quality, not quantity, should be the goal. The impact of automation and AI The rise of marketing automation, artificial intelligence, and machine learning has added even more complexity to the MQL model. With these tools, marketers can now analyze buyer intent with much more precision. Predictive analytics can tell you exactly where leads are in the buying cycle, making the need for MQLs obsolete. AI can track online behaviours - like what content leads are consuming, what they’re searching for, and how they’re engaging with your brand - giving marketers more insight into a lead’s readiness to buy. With these technologies, MQLs just don’t cut it anymore. Alternative approaches to lead qualification If MQLs are on their way out, what should B2B marketers focus on instead? Fortunately, there are several modern approaches that offer a more accurate and efficient way to qualify leads. The emergence of SQLs (Sales Qualified Leads) One alternative to MQLs is the rise of SQLs (Sales Qualified Leads). While MQLs are marketing’s responsibility, SQLs are the point at which marketing hands the baton to sales. These are leads that have shown clear signs of readiness to make a purchasing decision. SQLs are often defined by behaviors that indicate a real intent to buy, such as requesting a demo or engaging directly with a sales rep. The beauty of SQLs is that they involve collaboration between sales and marketing to define what makes a lead "sales-ready." This is a more refined and dynamic approach to lead qualification that ensures sales teams only get leads who are truly ready to engage. Intent data and predictive analytics Intent data is another game-changer. It’s no longer about waiting for leads to engage with your content - it’s about understanding what leads are already looking for and when they’re ready to buy. With intent data, you can track signals like content consumption, search behavior, and even third-party data to understand what’s driving a lead’s purchasing decision. By leveraging predictive analytics, B2B marketers can forecast which leads are most likely to convert into customers. This allows for a much more efficient qualification process than relying on traditional MQL scoring. Account-Based Marketing (ABM) Account-Based Marketing (ABM) is quickly becoming the go-to strategy for B2B marketers who want to focus on high-value accounts. Rather than casting a wide net and hoping for a good catch, ABM targets specific companies or organizations that fit your ideal customer profile. This personalized, high-touch approach allows you to focus your resources on the accounts that matter most. ABM eliminates the need for MQLs altogether. Instead, marketers work closely with sales to engage the right accounts and decision-makers with tailored messaging. The result is better-qualified leads, more meaningful relationships, and ultimately, higher conversion rates. Buyer journey mapping Understanding the buyer journey is crucial. Instead of relying on MQLs, marketers are mapping out the entire journey - from awareness to decision - to better understand when a lead is truly ready to talk to sales. By tracking engagement at every stage of the journey, marketers can identify when a lead is actually sales-ready, eliminating the guesswork that comes with MQLs. The role of technology in redefining lead qualification Technology has played a huge role in redefining how B2B marketers approach lead qualification. Marketing automation platforms like HubSpot, Marketo, and Salesforce now offer more nuanced ways to track and measure lead behaviour, moving away from simple MQL scoring. AI-powered tools are helping to qualify leads with greater precision. Predictive lead scoring, chatbots, and lead enrichment tools allow marketing and sales teams to make better-informed decisions about which leads are worth pursuing. By integrating these technologies with CRM systems, sales and marketing teams can have a unified view of each lead’s behaviour, making it easier to qualify leads based on intent rather than arbitrary scores. What’s next? The future of lead qualification in B2B marketing So, what’s next? The future of lead qualification is all about hyper-personalization, data-driven insights, and deeper sales-marketing alignment. Gone are the days of generic lead scoring models. The future is about delivering personalized experiences and understanding the true intent behind each lead’s actions. Data will continue to play a massive role in this shift. By leveraging closed-loop analytics, marketers will gain deeper insights into the entire buyer journey, allowing for more accurate lead qualification. And as sales and marketing teams work more closely together, the need for rigid MQL definitions will fade into the background. Final thoughts MQLs had their time in the sun, but the landscape of B2B marketing has changed. Buyer behaviour has shifted, technologies have advanced, and sales and marketing teams are becoming more aligned. As a result, MQLs are no longer the best way to measure lead quality. In the future, we’ll see a move towards more sophisticated, intent-based qualification models like SQLs, intent data, ABM, and predictive analytics becoming the norm. These approaches will help B2B marketers focus on quality over quantity, improving conversion rates and driving better ROI. So, if you’re still holding on to the old MQL model, it’s time to embrace the future of lead qualification. It’s a lot more nuanced, a lot more data-driven, and a whole lot more effective. Find out more about our Lead Management Services

Artificial Intelligence (AI) has transformed the way businesses prioritize and nurture leads, making sales and marketing efforts more efficient. AI-driven lead scoring analyzes vast amounts of data to predict which prospects are most likely to convert, allowing teams to focus on high-value opportunities. However, while AI brings numerous advantages, it also comes with challenges. In this article, we’ll explore the benefits and drawbacks of AI in lead scoring and highlight leading marketing technology platforms that offer AI-powered lead scoring. Understanding AI-driven lead scoring Traditional lead scoring assigns numerical values to prospects based on predefined factors like demographic details, company size, website activity, and email engagement. AI-driven lead scoring, on the other hand, goes beyond these static rules by using machine learning to analyze patterns, detect correlations, and predict which leads are most likely to become customers. Unlike traditional methods, AI continuously learns from new data, adapting its scoring models over time to improve accuracy and effectiveness. Benefits of AI in lead scoring ✅  Enhanced Accuracy - AI processes large datasets and identifies patterns that human analysts might miss, leading to more accurate lead prioritization. ✅  Scalability - AI models can handle millions of data points across various customer touchpoints, making them ideal for businesses of all sizes. ✅  Real-Time Analysis - AI scores leads dynamically, allowing sales teams to engage with high-priority prospects at the right moment. ✅  Improved Personalization - By understanding user behavior, AI can help tailor marketing efforts to individual prospects, increasing engagement and conversion rates. ✅  Optimized Resource Allocation - By identifying high-value leads, businesses can direct their efforts toward the most promising opportunities, reducing wasted time and resources. Challenges of AI in lead scoring ⚠️  Data Dependency - AI models rely on high-quality data. If the data is incomplete or inaccurate, the lead scoring model may generate misleading insights. ⚠️  Complex Implementation - AI-driven lead scoring requires integration with CRM and marketing automation platforms, which can be costly and require technical expertise. ⚠️  Potential Bias - AI models can inherit biases from historical data, leading to unfair scoring that may exclude certain prospects. ⚠️  Lack of Transparency - Some AI models operate as "black boxes," making it difficult for marketers to understand how specific scores are assigned. ⚠️  Over-Reliance on AI - AI should complement human decision-making rather than replace it entirely, as relationship-building and intuition remain crucial in sales. Marketing technology platforms with AI-powered lead scoring Several marketing automation and CRM platforms offer AI-driven lead scoring to help businesses prioritize leads more effectively. Here are some of the top solutions: Oracle Eloqua AI Feature:  Advanced lead scoring powered by Oracle’s machine learning models. Key Benefits: Uses AI to evaluate lead engagement, behavior, and demographic data. Helps businesses prioritize leads based on likelihood to convert. Integrates seamlessly with Oracle’s suite of marketing automation tools. Salesforce Marketing Cloud Account Engagement (MCAE, formerly Pardot) AI Feature:  Einstein Lead Scoring. Key Benefits: Uses Salesforce’s AI to rank leads based on behavioral data. Provides predictive insights for better targeting. Integrates with Salesforce CRM for improved sales and marketing alignment. Adobe Marketo Engage AI Feature:  Predictive content and AI-powered lead scoring. Key Benefits: AI analyzes past customer behavior to predict lead quality. Offers personalized content recommendations based on user engagement. Helps sales teams focus on the most valuable opportunities. HubSpot AI Feature:  AI-powered lead scoring and engagement tracking. Key Benefits: Uses machine learning to score leads based on their interactions with emails, web pages, and content. Helps marketers automate follow-ups and nurture campaigns. Provides insights into lead readiness to improve conversion rates. Final thoughts: Is AI-driven lead scoring right for you? AI-powered lead scoring has the potential to revolutionize sales and marketing by improving accuracy, efficiency, and personalization. However, businesses must be mindful of the challenges, including data quality, potential biases, and implementation complexity. The best approach is to combine AI-driven insights with human intuition, ensuring that marketing and sales teams leverage technology without losing the personal touch that builds relationships and trust. If you’re considering implementing AI-driven lead scoring, choosing the right platform is essential. Solutions like Oracle Eloqua, Salesforce MCAE, and Adobe Marketo Engage offer powerful AI capabilities, helping businesses maximize conversions and drive revenue growth. Want to explore AI-powered lead scoring for your business? Get in touch with our team to find the right solution for you!  🚀   Download our FREE whitepaper

Adobe Summit is one of the biggest annual events in digital marketing, bringing together industry leaders, innovators, and practitioners to explore the latest trends, tools, and technologies. It’s a hub for learning about AI, automation, customer experience, and data-driven strategies that are shaping the future of marketing. Whether you’re a CMO, Marketing Operations leader, or technology specialist, Adobe Summit offers insights and strategies to help you stay ahead of the curve and Adobe Summit 2025 was a powerhouse of insights. Our team was in attendance, soaking up the latest trends and strategies shaping the future of B2B marketing. From AI-driven personalization to optimizing complex buying journeys, here’s what stood out to us from a few of our favourite sessions: Cracking the code: building and scaling B2B buying groups B2B marketing isn’t just about convincing one decision-maker anymore - it’s about engaging entire buying groups. This session broke down how marketers can adapt to this shift. Our key takeaways: Buying groups are getting bigger and more complex, meaning one-size-fits-all marketing doesn’t cut it. Instead, businesses need to personalize outreach for multiple stakeholders with different priorities. Intent data and automation are game changers. By understanding where prospects are in their journey, marketing and sales teams can engage them at the right time with the right message. Seamless, multi-touch engagement is key. Consistency across channels helps build trust and keeps the buying group moving toward a decision. Structuring Marketo Engage for multiple teams and regions Managing Marketo Engage across different teams and locations can feel like herding cats. This session provided practical tips to make it all run smoothly. Our key takeaways: Organizing workspaces and partitions properly prevents chaos and ensures different teams can work effectively while maintaining clean data. A real-world example from Minto Homes showed how Marketo can support both B2B and B2C experiences - proving it’s not just about software, but how you structure it for success. The right integrations can take Marketo to the next level, making reporting and scalability much easier across different markets. Making AI work for your business AI isn’t a buzzword anymore - it’s actively reshaping B2B marketing. This session showed how businesses can harness its power. Our key takeaways: AI-driven predictive analytics help marketers anticipate customer needs before they even realize them, leading to more meaningful interactions. Automating lead scoring and nurturing at scale frees up valuable time, allowing teams to focus on high-value prospects. The session also touched on the ethics of AI, emphasizing that while automation is powerful, the human touch is still crucial in building relationships and trust. B2B reimagined: transforming go-to-market strategies With AI and automation becoming central to B2B marketing, businesses need to rethink how they go to market. Our key takeaways from this session included: Account-based marketing (ABM) is gaining momentum, shifting focus from broad campaigns to highly targeted, high-value account strategies. AI-driven insights are helping marketers refine their messaging, optimize touchpoints, and create more personalized experiences. Aligning sales and marketing teams is more important than ever—when both are working toward the same goal with unified messaging, conversions happen faster. Final thoughts Adobe Summit 2025 made one thing clear: the future of B2B marketing is all about AI, automation, and personalization. Companies that embrace these technologies - while keeping a human touch - will be the ones that thrive. If you’re looking for ways to put these strategies into action, Sojourn Solutions is here to help. Discover more about our AI services

Artificial intelligence (AI) is revolutionizing marketing automation, enabling businesses to engage prospects, personalize experiences, and drive conversions more effectively. However, not all AI-powered marketing automation platforms (MAPs) yet offer the same capabilities. Here, we compare how four major players - Adobe Marketo Engage, Oracle Eloqua, Salesforce Marketing Cloud Account Engagement (MCAE), and HubSpot - currently leverage AI to enhance their (and your) marketing performance. AI-Powered Email Content Creation Creating engaging email campaigns can be time-consuming, but AI is streamlining the process: Adobe Marketo Engage : Features a built-in AI assistant that generates rapid, brand-approved email content and visuals. Oracle Eloqua : Utilizes AI primarily for optimizing subject lines and determining optimal send times. Salesforce MCAE : Integrates with Salesforce's AI tools to automate certain aspects of content creation. HubSpot : Offers an AI-powered content assistant that drafts email copy, calls-to-action (CTAs), and other marketing messages. Winner:  Adobe Marketo Engage & HubSpot for their advanced AI-generated content capabilities. AI Chatbots & Conversational Marketing AI-driven chatbots are transforming customer interactions by providing real-time, automated responses: Adobe Marketo Engage : Introduces "Dynamic Chat," an AI-powered chatbot that offers real-time Q&A with customizable responses. Oracle Eloqua : Lacks a native chatbot feature, necessitating third-party integrations. Salesforce MCAE : Leverages Salesforce's AI to facilitate chatbot-like customer engagement experiences. HubSpot : Provides "ChatSpot AI," an assistant designed for conversational marketing and sales support. Winner:  Adobe Marketo Engage & HubSpot for their built-in AI-driven chatbot functionalities. AI-Enhanced Webinar Content Webinars are valuable marketing tools, and AI can enhance their effectiveness: Adobe Marketo Engage : Employs AI to generate webinar summaries and create video chapters for improved navigation. Oracle Eloqua, Salesforce MCAE, and HubSpot : Currently do not offer AI-driven webinar enhancements. Winner:  Adobe Marketo Engage for its unique AI-powered webinar content features. AI-Driven Meeting Scheduling Efficient scheduling can significantly boost lead conversion rates: Adobe Marketo Engage & HubSpot : Offer built-in AI-powered meeting schedulers. Oracle Eloqua & Salesforce MCAE : Require third-party integrations for scheduling functionalities. Winner:  Adobe Marketo Engage & HubSpot for their native scheduling automation features. Predictive Analytics & Lead Scoring AI assists marketers in prioritizing high-value leads and optimizing campaign performance: Adobe Marketo Engage : Utilizes AI-driven insights to measure ROI and refine marketing strategies. Oracle Eloqua : Features advanced AI-powered lead scoring for enhanced targeting. Salesforce MCAE : Employs Salesforce's AI to predict lead quality and engagement levels. HubSpot : Uses AI to prioritize contacts based on their engagement metrics. Winner:  All platforms provide AI-powered lead scoring, with Adobe Marketo Engage and Oracle Eloqua leading in advanced analytics. AI-Powered Content Personalization Personalized content enhances engagement and conversion rates: Adobe Marketo Engage : Adjusts content and CTAs in real-time based on user interactions. Oracle Eloqua : Employs audience segmentation for targeted campaigns. Salesforce MCAE : Dynamically modifies messaging based on customer behavior. HubSpot : Provides AI-driven content recommendations for emails, websites, and landing pages. Winner:  Adobe Marketo Engage & HubSpot for real-time, AI-driven personalization. Verdict: Which MAP currently offers the most AI integration? Each platform has its strengths: Best for AI Content Creation & Webinars:   Adobe Marketo Engage Best for AI-Powered Chatbots & Scheduling:   HubSpot Best for Predictive Analytics & Lead Scoring:   Oracle Eloqua & Salesforce MCAE Best for AI-Powered Personalization:   Adobe Marketo Engage & HubSpot If your goal is advanced AI-driven automation, content creation, and personalization, Adobe Marketo Engage  and HubSpot  lead the way. For AI-driven lead scoring and predictive analytics, Oracle Eloqua  and Salesforce MCAE  are strong contenders. Final thoughts AI is revolutionizing marketing technology, empowering businesses to automate processes, gain deeper insights, and deliver personalized experiences at scale. From predictive analytics and customer segmentation to AI-driven content creation and real-time campaign optimization, AI enhances efficiency and enables smarter decision-making. Sojourn Solutions can help you seamlessly integrate AI-powered solutions into your MarTech stack for maximum impact. Whether you're selecting the right tools, refining data models, or optimizing AI-driven strategies, we provide the expertise to harness AI’s full potential - so you can work more efficiently, make data-driven decisions, and accelerate growth. Download the FREE whitepaper *All information in this article is presumed correct as of 14th March 2025 - but please reach out to the prospective software companies for confirmation of their current AI capabilities

The Challenge of Multi-Touch Attribution in B2B Attribution in B2B marketing has always been a complex puzzle. Unlike B2C, where customer journeys are often short and direct, B2B buying cycles are long, involve multiple stakeholders, and span several touchpoints across marketing and sales. Traditional attribution models - first-touch, last-touch, and even basic multi-touch - fail to capture the full impact of each interaction. Enter AI. By leveraging machine learning and advanced analytics, AI-powered attribution models can now analyze vast amounts of data, detect patterns, and assign value to each touchpoint in ways that were previously impossible. How AI is Transforming Multi-Touch Attribution 1. Moving Beyond Basic Models Traditional models assign credit in rigid ways: first-touch gives all credit to the initial interaction, last-touch credits only the final interaction, and linear models distribute credit evenly across all touchpoints. AI, however, dynamically evaluates real impact - determining which engagements truly drive conversions rather than treating all interactions equally. 2. AI-Powered Data Integration One of the biggest hurdles in attribution is consolidating data across multiple platforms - CRM, marketing automation, social media, paid ads, email campaigns, and offline events. AI can ingest, clean, and unify  data from these sources, eliminating gaps and giving a holistic view of the customer journey. 3. Predictive Attribution Modeling AI doesn’t just look at past data - it predicts future impact. By analyzing engagement patterns, AI can determine which touchpoints are most likely to influence pipeline acceleration and revenue growth, helping marketers allocate budget more effectively. 4. Understanding the Buying Committee B2B sales involve multiple decision-makers. AI-driven attribution accounts for interactions across the entire buying group , identifying the roles and engagement levels of different stakeholders within an account, not just individual leads. 5. Real-Time Attribution and Optimization With AI, attribution isn’t just a reporting tool - it’s an active optimization engine . Real-time insights allow marketers to adjust campaigns, shift spending, and refine messaging based on what’s actually driving results. The Impact of AI-Powered Attribution on B2B Marketing More Accurate ROI Measurement AI-driven attribution provides a clearer picture of marketing ROI , ensuring that investment is directed toward the most effective channels and tactics. Better Alignment Between Marketing and Sales By tracking interactions across both marketing and sales touchpoints, AI-driven attribution strengthens alignment—helping teams work towards shared revenue goals rather than separate KPIs. Smarter Budget Allocation With AI pinpointing high-performing channels, B2B marketers can make data-backed decisions to shift budget toward strategies that drive actual revenue impact. Enhanced Personalization Understanding which touchpoints matter most enables marketers to craft hyper-personalized experiences  that move accounts through the funnel faster. Final Thoughts AI isn’t just improving B2B attribution - it’s rewriting the rules . By moving beyond static models and providing real-time, predictive insights, AI is finally solving the multi-touch mystery  that has frustrated marketers for years. As AI-driven attribution continues to evolve, B2B marketing leaders must embrace it - not just to track performance, but to drive smarter, more effective strategies that fuel business growth. Download your FREE whitepaper