Let’s be honest: B2B email marketing often feels like a digital handshake – polite, professional, but rarely memorable. It’s easy to be so focused on product features and ROI that you forget you’re communicating with people, each driven by unique values and motivations. It’s time to inject a shot of creativity into your B2B customer acquisition strategies, transforming them from transactional exchanges into opportunities for genuine connection. The key? Psychographic data.
Psychographics: The Creative Compass for B2B
Forget the outdated notion of generic “decision makers.” Psychographics allow you to understand the why behind B2B buying decisions. By delving into the values, interests, attitudes, and motivations of your target audience, you can move beyond surface-level demographics and craft communications that resonate on a deeper, more human level. Think of it as adding a layer of empathy to your data-driven strategy, transforming cold leads into engaged prospects.
Mapping Motivations to Moments of Opportunity
Imagine knowing that a significant portion of your audience is driven by a desire for innovation. This insight isn’t just a data point; it’s a creative springboard. How can you leverage that motivation to craft a compelling campaign? Perhaps you showcase how your solution is disrupting the industry, highlighting its cutting-edge features and potential for transformative growth. Identifying these moments (and aligning your messaging accordingly) is where creativity meets opportunity in B2B.
By moving beyond technical specifications and crafting campaigns that showcase how your solution directly addresses these underlying needs, you can create targeted, resonant messaging that transforms prospects into engaged customers.
Crafting Messages That Spark Engagement (and Action)
Messages will often need to be tailored to your target’s role in an organization, particularly when a buying committee is involved in the decision-making process. Psychographic data allows you to craft messages that speak directly to their core values and beliefs.
If you want to engage organizations and individuals that prioritize sustainability, showcase your commitment to environmentally friendly practices. Or for those who value cost savings, highlight how your company’s solutions deliver operational efficiencies while enhancing service quality. Tell a story. Share the impact of your initiatives and highlight your commitment. The key is to be authentic and avoid empty buzzwords. Show, don’t just tell.
Integrating Psychographics: A Strategic Symphony of Data and Creativity
Effective B2B acquisition requires a strategic blend of data and creativity. Segment your audience based on psychographic profiles and tailor your content strategy accordingly. A segment that values thought leadership might be more responsive to white papers and webinars, while a segment that prioritizes peer-to-peer learning might engage more with case studies and user forums. Continuous testing and optimization are crucial for refining your approach and maximizing results.
Ethical Considerations: Building Trust Through Responsible Practices
As you embrace the power of psychographic data, you must also acknowledge ethical responsibilities. Transparency and respect for privacy are non-negotiable. Be clear about how you’re collecting and using data and ensure you’re adhering to all relevant regulations. Building trust is essential for long-term success in B2B, and that trust can easily be broken by unethical practices.
By embracing the creative potential of psychographic data and integrating it into B2B strategies, you can unlock hyper-relevant moments that drive engagement, build brand loyalty, and ultimately, achieve your business goals. It’s time to move beyond generic messaging and start connecting with your audience on a human level, transforming your campaigns from digital handshakes into meaningful conversations.
To learn more, check out our recent webinar Find your next customer with data-fueled email acquisition.
A massive 78% of people are more likely to trust a brand if it’s transparent about the personal data it’s collecting and how it’s used, according to our 2025 CX Trends Report, A Human-Centered Approach to Customer Experience.
This strongly held opinion seems like a compelling incentive for brands to be candid about their data collection and use. But are brands doing enough to provide their customers with a transparent data exchange? Let’s find out.
People are getting savvier about data use
The vast majority (98%) of the more than 2,000 people we surveyed are already aware that brands are using their data to tailor marketing and advertising messaging and strategies. They also are starting to understand the benefits of sharing data to drive this type of personalization, especially among younger demographics. In the 16-34 year old age group:
- 64% see the benefit of sharing data to see more relevant product or service advertisements, compared with 44% in the 55-and-older age group.
- 63% see the benefit of sharing data to get recommendations for new products or services on websites they’re browsing, compared with 39% in the 55-and-older age group.
- 62% see the benefit of sharing data to receive targeted discounts on products or services, compared with 52% in the 55-and-older age group.
However, the younger people who appreciate the benefits of data sharing are also more likely to have concerns about data privacy. Overall, a third (33%) of survey respondents say they’ve stopped using a product or service due to concerns around data transparency and the way data is used. This percentage rises to 45% for the 16-34 age group. It seems transparency isn’t just a nice-to-have – it has become a prerequisite.
Brands think they’re being transparent
About two-thirds of the brands we surveyed for the 2025 CX trends report are already collecting personal data, engagement data, or behavioral data to inform their marketing campaigns. Overall, they’re confident about their collection and use of customer information:
- 68% of brands believe they offer a clear value exchange.
- 79% say their organization has a good understanding of data privacy laws.
- 63% report they only collect customer data that will actually be used.
As the VP of Marketing Strategy at a retail and investment bank told us, “We try to be as transparent as possible, telling our customers about the personalized benefits that help them manage, save, and grow their money. But to offer those benefits, we have to know things about our customers – if we’re helping them save for a holiday, we have to know what their budget is. So we have to be very clear with our T&Cs during the onboarding process.”
But customers don’t necessarily agree
The data suggests that even though brands believe they’re doing their best to operate with transparency, there remains an important gap between brand and consumer perceptions. Here are two key examples:
- Understanding: 67% of brands believe their customers have a good understanding of how their data is used for marketing and advertising. However, only 56% of those people say this is the case.
- Expectations: 78% of brands think they’re meeting customer expectations around personal data collection. But just 49% of people say they’re satisfied with the data transparency companies provide.
The good news is that when asked how their data collection practices will change in the next three years, brands say their number one focus is making it easier for people to understand how their data is being collected, stored, and used. So how should they go about achieving this?
Customers must be at the heart of data strategies
The future of data exchange will be centered around the customer. The report reveals that brands can build strong, trusting relationships with those customers by focusing on three key areas:
- Invest in a robust cloud-based infrastructure capable of securely storing and managing vast volumes of data, and use enterprise identity solutions to create a unified customer view.
- Articulate a clear and compelling value exchange with tangible benefits that really resonate, encouraging customers to share their data willingly.
- Implement easy-to-understand privacy policies that clearly communicate how data will be used and empower people to easily control the types of data they share.
Read Acxiom’s 2025 CX Trends Report, A Human-Centered Approach to Customer Experience to discover what 200 senior marketing professionals and more than 2,000 people in the U.S. and U.K. think about the five trends that we predict will shape CX this year. You’ll also benefit from expert guidance on how you can use these insights to grow your own business.
Imagine if every time you saw close friends, they spoke to you like they’d never met you – like it was your first encounter, and they didn’t know anything about you. Wouldn’t that be more than a little strange?
Until recently, that’s exactly how brands interacted with their customers. They took a linear, channel-based approach to marketing, starting a new and potentially different conversation with customers at every touchpoint, resulting in disjointed, frustrating customer experiences.
Fortunately, brands are now shifting their approach and interacting with people the way people interact with people. Along the journey from awareness to consideration to conversion, customers use multiple channels, platforms, and devices to engage with brands. Brands strive for consistent, personalized experiences at every touchpoint to propel customers toward conversion.
Introducing Customer Journey Analytics
To support this approach and understand individual interactions and the entire customer journey, brands need a corresponding shift in measurement and analytics. They must be able to recognize customers at each interaction and access information about them to enable a seamless experience. For brands that use Adobe, this typically means a transition from event-based Adobe Analytics to Adobe Customer Journey Analytics.
Every part of the Adobe Experience Cloud – from Mix Modeler to Adobe Journey Optimizer – is moving toward a journey-based approach. This shift was evident at Adobe Summit 2025, where major innovations were unveiled to define customer journey orchestration in the AI era.
Analytics has to follow. Suppose everything in a platform executes a journey-based strategy, but analytics measure events. In that case, it’s like having a cockpit where the instruments don’t register the position and progress of the airplane on its journey. Like a pilot, a marketer needs to know where people are in their journey and anticipate where they are going.
With Adobe Customer Journey Analytics, brands don’t just see when customers click an organic search ad on their smartphone and land on their website. They can also see that the same customers visit the website on their desktop, browse products, put something in their cart, and then leave the site. They can determine what action to take to bring customers back to complete their purchase or explore alternative options.
Adobe Customer Journey Analytics unifies data across channels and devices to understand full customer journeys and assigns it to a single profile. From the very first customer engagement, marketers can begin to collect behavioral signals – albeit anonymously, at least initially. They start building an understanding of how customers interact with their brand and how they evaluate different products and services.
When customers provide information that allows them to be identified – often an email address – brands can integrate Adobe’s Experience Platform and Acxiom to link that anonymous data with a known identity. They can enrich their information with Acxiom’s market-leading InfoBase data to better understand who those people are, what interests them, and what motivates them. This understanding enables the personalized experiences that will move customers through the consideration steps and ultimately get them to convert.
A lighthouse approach to the Adobe Customer Journey Analytics transition
Transitioning from event-based Adobe Analytics to journey-based Adobe Customer Journey Analytics can be a challenge. Underlying data mapping between the systems is needed to transition legacy event data, and the dashboards and analytic models of any third-party analytics tools like Databricks or Tableau also need to be adjusted. Moreover, different perspectives and deeper insights will inevitably change attribution alignment, organizational structures, and how marketers allocate budget.
As an Adobe Platinum solution and technology partner, Acxiom can support you with a structured, step-by-step pathway to this transition. We take a lighthouse approach, identifying and transitioning a single journey to begin, measuring it in both systems concurrently. This allows your teams to determine how measurement will need to change and acts as a north star for the rest of the migration. Then, as your confidence in the new approach grows, we’ll help you layer on more journeys until you are fully transitioned to Adobe Customer Journey Analytics.
The transition pathway includes six steps:
Step one: Assess current-state marketing analytics capability
The first step is diagnostics. We use a blueprinting process to understand what measurement tools you’re using, how data is being captured and managed, which metrics are being measured, who is using them, and for what purpose.
Step two: Develop new marketing insights, vision, and goals
The next stage is to define the business outcomes you want to achieve with the new journey strategy and create use cases for the initial lighthouse. Which data signals need to be captured at different points on the journey? Do they exist in the event-based analytics tool, or must the Adobe Experience Platform capture them?
Step three: Optimize the campaign planning process with journey-based insights
Once the lighthouse’s desired business outcomes are defined, we’ll create a future state design for enabling technology, data, analytics, process enhancements, and an agile organizational operating model. This will be validated with you at every stage to ensure the right solution for your needs.
Step four: Design data flows and models for integration
At this stage, we’ll prioritize the tasks that must be completed for the initial transition. This may require a change in operating model, shifting from teams focused on single-channel measurement to cross-functional teams looking at journey measurement.
Step five: Build architecture with a phased implementation roadmap
At this stage, we’ll launch the initial lighthouse and start to capture data. We’ll measure interactions simultaneously in Adobe Customer Journey Analytics and Adobe Analytics to compare and understand the differences.
Step six: Deliver white-glove support through migration and adoption
Once you’re comfortable with the initial lighthouse, we’ll iteratively repeat the process until everything is migrated to the new system and everyone is on the same page. Ultimately, we’ll turn off the old system because the events are still being captured in Adobe Customer Journey Analytics.
A home improvement retailer’s speedy renovation
A home improvement retailer used Acxiom’s Adobe professional services team to migrate from Adobe Analytics to Adobe Customer Journey Analytics. Thanks to Acxiom’s proven data automation services, the transition timeline was reduced by weeks.
Based on insights from the end-to-end customer journey, the retailer prioritized e-commerce personalization as the most valuable channel in the buying experience and allocated $1 million in media and channel spend more effectively.
Get in touch to learn more about how Acxiom can ease your transition from Adobe Analytics to Adobe Customer Journey Analytics. Let us support your shift from siloed, linear marketing to a journey-focused approach that interacts with customers the way they interact with you.
People increasingly expect the brands they buy from to treat diverse customer groups with sensitivity. Almost two-thirds (64%) believe it’s important for brands to demonstrate inclusivity through their products and services, according to Acxiom’s 2025 CX Trends Report, A Human-Centered Approach to Customer Experience.
Is inclusivity just for the young?
It won’t surprise you to know that the desire for inclusivity is especially strong among younger age groups. The report reveals:
- 53% of 16-34-year-olds have specifically purchased a product or service from a brand due to its inclusivity commitments, compared with just 22% of those 55 and older.
- 25% of 16-34-year-olds have actively avoided purchasing from a brand due to concerns over inclusivity, compared with just 13% of those 55 and older.
But this doesn’t mean brands only need to consider inclusivity when catering to younger demographics, as different age groups may have different concerns. While younger people may be more interested in inclusive products and services that cater to people of different genders, abilities, and cultural backgrounds, older groups might be more interested in things like age-related inclusivity and catering to different levels of technological fluency.
There are considerable benefits for brands that get inclusivity right. Among those that have taken steps toward inclusive product and service design, 53% report increased revenue, 45% report enhanced brand reputation, and 42% report improved customer satisfaction.
As the Director of Digital Marketing at a retail bank in the U.K. explains, “We developed a product for a set of our customers that are historically underserved by banks. This was a result of us really listening to our customers – we have amazing software that flagged this from recorded calls and other customer service interactions. It was a risky product for us to build, but it was worth it to help people out. Not only has it made a huge difference to our customers, but it led to a lot of buzz and ultimately changed perceptions around our brand.”
There are gaps in brand inclusivity strategies
Brands are picking up on the fact that people care about this issue a great deal, with 80% of those who took part in the report recognizing that a commitment to inclusivity is important to their customers. However, there is a gap between understanding and action, as only 55% have taken steps to ensure products or services are inclusive.
It’s important to acknowledge that consumers don’t just want brands hand-waving at the issue of inclusivity. They want brands to be making real, tangible steps toward fostering a more inclusive culture for the one in five people with special requirements. And there is a difference between what people are prioritizing and the actions brands are taking. For instance:
- 53% of people want brands to make customer support more inclusive, but only 25% of brands are actively trying to make this happen.
- 36% of people want brands to design more inclusive products, but just 18% of brands are prioritizing this.
Finally, there’s a gap between the categories of diversity people think brands should be focusing on and the groups they’re actually considering. While people want brands to ensure they’re being more inclusive of disabilities and diverse cultural backgrounds, the brands that are paying attention to inclusivity are focused on people with disparate levels of financial literacy and tech fluency.
What should brands be doing about inclusivity?
Inclusivity shouldn’t be a tick-box exercise. Brands must make a long-term commitment to catering to diversity if they want to build deeper customer relationships and enjoy the rewards of getting it right, such as differentiating their offering in the market.
To embrace inclusivity, brands need to really understand their customers, and that means using their first-party data – enriched with other trusted data sources – to create a unified view. AI will inevitably be used to identify patterns and preferences and inform brand strategies, although care must be taken with training data to ensure AI promotes rather than inhibits inclusivity.
By using data and technology to gain a deeper understanding of diverse customer needs and preferences, brands can provide truly inclusive products, services, and experiences. They will be able to weave inclusivity through the entire customer journey, from initial awareness to product and service design to post-purchase engagement.
Read Acxiom’s 2025 CX Trends Report, A Human-Centered Approach to Customer Experience, to discover how 200 senior marketing professionals and more than 2,000 people in the U.S. and U.K. see five trends we predict will shape CX this year. You’ll also benefit from expert guidance on how you can use these insights – which focus on finding the right balance between technology and human interaction – to grow your business.
Loyalty programs are a staple of the modern customer experience in almost all industries, from retail and travel to utilities and hospitality. And rightly so.
According to Acxiom’s 2025 CX Trends Report, 78% of people believe they should be rewarded for their loyalty to a brand, and the same proportion says they’re more likely to stay loyal if they are adequately rewarded. Six in ten (60%) even say they would choose to buy from a brand that offers a loyalty program over one that doesn’t.
The question is: Are brands actually getting the most from their loyalty programs? The report, which is based on a survey of more than 2,000 consumers and 200 brands in the U.S. and U.K., suggests this isn’t always the case.
Brands are keen to make loyalty initiatives work
Loyalty programs help brands achieve a variety of goals. According to the survey, brands say these are the biggest benefits of loyalty programs: boosting customer referrals through brand advocacy, increasing customer lifetime value, and improving customer retention. These are the main reasons 91% of brands offer some form of rewards or benefits to loyal customers.
On the surface, brands appear to be doing all the right things. When asked how they reward customer loyalty, their top three answers were:
- Exclusive discounts or offers
- Exclusive events or experiences
- Personalized recommendations
These align well with people’s expectations. When asked which loyalty benefits would make them more likely to consider a brand for their next purchase, the top three responses were:
- Exclusive discounts or rewards
- Offers tailored to individual preferences
- Early access to sales
Brands recognize the importance of exclusivity in keeping their customers loyal, with 72% feeling it’s beneficial to create a sense of exclusivity around their loyalty program, and 70% already using a tiered approach where their most valuable members receive the highest levels of reward.
They also appear to understand the necessity for personalization. Two-thirds (67%) use customer data to tailor benefits for individual members, and almost half of those (45%) use AI as part of the process. They understand that the use of data to generate deeper customer insights leads to more personalized experiences, which in turn can foster lasting loyalty.
As the Director of Customer Marketing at a U.K. retailer explains, “AI is helping us to accelerate decision making, both in terms of deciding which promotions we should give to each customer and ensuring this is more personalized for every individual. Whereas previously you might have given a promotion to lots of people all at the same rate, we can now use AI to distinguish which customers should get which promotion.”
But despite these promising trends, it seems brands are facing some key challenges with making loyalty programs work.
Where brands struggle with loyalty programs
The first area of contention highlighted by the report is defining what loyalty actually means to the brand, and therefore what type of behavior the program is designed to encourage and reward. The brands surveyed say they are most likely to define loyalty as customer lifetime value, but they may also be looking at customer engagement or range and frequency of purchases. Interestingly, only a third define loyalty on the basis of advocacy, despite referrals being cited as the most important benefit of setting up a loyalty program.
The next area of concern is measurement. When asked about their biggest challenges in running loyalty programs, difficulties measuring success are at the top of the list, followed by issues with maintaining programs in the long term. These challenges are inextricably linked. If brands can’t accurately define the kind of loyalty they’re aiming to foster and aren’t appropriately set up to measure the success of their initiatives, how can they possibly expect to keep these programs profitable for an extended period?
Part of the problem may well be technology. A surprisingly low 21% of the brands that offer loyalty programs say they’re using a loyalty platform to manage it. Among those that are using a loyalty platform, 45% report struggling because the platform isn’t effectively integrated with the rest of their systems.
Help is at hand
There’s little doubt that loyalty programs can be beneficial for both the customers that reap the rewards and the brands that rely on them for referrals, retention, and revenue. But if brands want to make the most of this now well-established trend in improving customer experience, the data suggests they’re going to need a little help.
Working with expert partners can help brands continue their quest for exclusivity by making effective use of AI to identify high-value customers and build tiered loyalty programs. It can help them implement sophisticated measurement capabilities to monitor program success on an ongoing basis and optimize performance against well-defined benchmarks. And it can help them seamlessly integrate data and systems so they can understand customers’ differing needs and drive personalized interactions that inspire lasting loyalty.
Read Acxiom’s 2025 CX Predictions Report, A Human-Centered Approach to Customer Experience, for more views from senior marketing professionals and consumers, along with expert guidance on how brands can use these insights to grow their business.
How JPW Industries is Transforming Customer Experience with AI
Overcoming operational challenges with Salesforce AI solutions.
In a dynamic industry shaped by ever-evolving customer demands, JPW Industries—a leading player in woodworking and metalworking tools—found itself grappling with operational challenges in order servicing and customer support. Handling thousands of orders monthly, often through email and fax, required significant manual effort and seasonal labor adjustments. To overcome these hurdles, the company partnered with RafterOne to implement Salesforce AI technology, including Einstein and Agentforce, revolutionizing their processes.
We sat down with Terri Eshleman, Vice President of Customer Experience & Direct Sales at JPW Industries, to learn about their journey, the impact of adopting AI technology, and what the future holds for their business. Here’s what she had to say.
Why JPW Industries Embraced Salesforce AI Solutions
Q1: What motivated JPW Industries to explore AI-driven solutions?
The journey began because we were looking for a way to automate our order process. We handle just shy of 3,000 orders a month, which are emailed or faxed to us. Processing them requires a lot of headcount and labor, which becomes a significant strain, especially during peak seasons.
Salesforce has always been a strong partner for us. When I reached out to them about potential solutions, they introduced us to Einstein and Agentforce. Initially, we were only focused on order automation, but the project quickly grew into something much larger—one that’s poised to have a huge impact on all aspects of our business, including our call centers, technical support, and direct sales teams.
Q2: Why did JPW choose RafterOne as a partner for this transformation?
We chose RafterOne because of their outstanding reputation. They came highly recommended as an experienced, well-rounded AI partner and with a project of this scale, we couldn’t afford to take risks. We needed the best partner, and RafterOne was the clear choice.
Q3: How has the implementation journey been for your team so far?
It’s been a lot of work, but enjoyable work. The process has forced us to take a step back and reevaluate how we store and use information, even down to how our agents complete fields in Salesforce.
We discovered areas where we needed to reset and refine our approach to lay the foundation for Einstein to truly shine. The partnership with RafterOne has been exceptional—transparent conversations, well-managed timelines, and incredible project management. It’s been a genuinely pleasant experience throughout the process of launching Einstein for service and gearing up to launch Agentforce soon.
Q4: What specific challenges do you expect Einstein and Agentforce to solve?
JPW is the result of six companies merging over time, which means we’ve accumulated decades of tribal knowledge stored in people’s minds rather than centralized systems. Our agents spend a lot of time digging through shared drives, catalogs, and manuals for answers, which prolongs training and case resolution times.
Einstein and Agentforce will help us build a knowledge database and an intelligent copilot for our agents. This will significantly shorten the six months it currently takes to train new agents and improve the quality of technical support. For example, my team repairs high-value machines remotely—often based only on photos or emails. Now, with AI-powered live troubleshooting, we expect to see substantial returns in terms of efficiency and customer satisfaction.
Another major benefit is 24/7 customer support. Today, we’re limited to business hours, but with Agentforce, we can serve our customers whenever they need us.
Q5: Why is Agentforce particularly exciting for JPW Industries?
I like to think of Agentforce as an invisible army. It’s scalable, which means our business can grow without needing to add more staff. It frees up our team to focus on meaningful conversations with customers—building relationships instead of handling transactional tasks like sending invoices or booking appointments.
Relationships are the backbone of long-term success, and Agentforce allows us to invest in those relationships by taking care of the repetitive tasks that often distract our agents from what truly matters.
Q6: How has your team responded to the integration of these AI tools?
Initially, there were concerns—some employees worried that AI might replace their roles. But I explained that this isn’t about replacing people; it’s about enhancing what we can do together. Our customers value meaningful human interactions, and AI allows us to focus on those. This is a partnership between humans and technology. By automating repetitive tasks, AI empowers our team to provide better service and build stronger customer relationships.
Q7: What results do you anticipate from these implementations?
Better service translates into a stronger reputation, which ultimately drives sales and growth. We’re a company poised for growth, and this project is setting us up to serve our customers better and achieve our business goals.
We expect shorter call times because agents will have faster access to information, which builds trust with customers. Reducing case resolution times will also free-up agents to handle more calls and deepen customer relationships.
Just 4 weeks since going live with Einstein Service Agent and Visual Remote Assistant (VRA), we are already experiencing positive results, and our agents are very happy. Since launch, we have processed 900 more cases than the previous month while reducing case closure time by 4 hours. This improvement translates to a 15% increase in cases handled and a 12% reduction in response time—equivalent to saving two full workdays. Additionally, our return rate for machinery was reduced by 2.2% due to VRA usage. In one specific case, the field service technician was able to diagnose the issue and avoid returning the equipment by assisting in a live repair.
Our specific goal for Agentforce is a reduction in cases due to self-service capabilities for the customer. We are excited to be launching soon and expect to see significant results quickly.
Conclusion
Key Takeaways from JPW Industries’ Journey
JPW Industries’ collaboration with RafterOne demonstrates how AI can transform business processes, streamline operations, and enhance customer relationships. By implementing Einstein and Agentforce, the company is not only solving immediate challenges but also positioning itself for scalable growth and long-term success.
Ready to Transform Your Business with AI?
If you’re looking to transform your operations and maximize ROI like JPW Industries, consider starting with an AI Readiness Assessment. Discover how Salesforce AI solutions can help your business scale and succeed.
Your Next Top Performer Isn’t Human–It’s Powered by Data
Customer expectations and the demands on your employees are at an all-time high. They demand instant answers, seamless experiences, and personalized interactions–but your systems and employees are struggling to keep up. The challenge? Too much information, everywhere, all at once.
Teams often work across disconnected systems, manually searching for data spread across multiple platforms. This leads to delays, inefficiencies, and frustration. In fact, 86% of service agents and 74% of mobile workers report that customer expectations are higher than ever before. (Salesforce)
To meet these growing demands, companies need more than automation—they need intelligent, real-time data that guides AI-driven customer interactions. That’s where Agentforce, powered by Salesforce Data Cloud, steps in.
The Problem: Drowning in Data
Businesses today collect vast amounts of customer data, but much of it remains locked away in separate systems–inaccessible when it’s needed most. This creates a ripple effect:
- Slower response times: Customers wait too long for answers.
- Incomplete insights: Agents lack the full picture to make informed decisions.
- Escalation overload: Simple queries get pushed to Tier 2 and Tier 3 support.
Even traditional Master Data Management (MDM) initiatives struggle to solve this. While they centralize data, they don’t necessarily make it actionable or easily accessible for customer-facing teams and AI.
The Solution: The Well-Informed Agent
Together, Agentforce and Salesforce Data Cloud transform AI-driven customer service by breaking down data silos and ensuring real-time, unified intelligence across every interaction.
By activating and contextualizing customer data, businesses can:
- Automate Repetitive Tasks: AI agents handle inquiries instantly, reducing wait times.
- Predict Customer Needs: AIi-driven insights allow businesses to proactively solve issues before they arise.
- Deliver Personalized, AI-Powered Interactions: Every conversation is based on complete, real-time insights, ensuring accuracy and relevance.
With Data Cloud fueling Agentforce, AI agents and employees can:
- Access Unified Data in Real-Time: No more fragmented systems or outdated information.
- Increase Efficiency and Lower Costs: Faster resolutions prevent costly escalations.
- Ensure Compliance & Data Governance: Businesses gain efficiency without sacrificing security.
The result? A scalable AI-powered workforce that doesn’t just respond to customer needs, it anticipates them.
AI in Action: How Data Cloud Powers Smarter CX
From retail to healthcare, businesses are reimagining customer experiences with data-driven intelligence. But automation alone isn’t enough. Without real-time, connected data, even the most advanced AI falls short of delivering meaningful impact.
Enter Salesforce Data Cloud. By unifying fragmented data into a real-time, always-on intelligence layer, businesses gain a complete, actionable view of every customer. This foundation enables AI-powered solutions like Agentforce to go beyond automation—driving personalized, predictive, and more effective interactions.
Across industries, companies are proving what’s possible when AI has the right data behind it. Here’s how businesses are leveraging Agentforce and Data Cloud together to transform both employee and customer experiences.
Industry Use Cases:
Retail and Consumer Goods
- Personalized product recommendations based on purchase history
- Automated order tracking, returns, and refund processing
- Real-time inventory updates and product availability
Manufacturing
- Proactive customer support for product usage, warranties, and maintenance
- AI-driven predictive maintenance alerts based on real-time equipment data
- Automated order fulfillment updates and tracking
Financial Services
- AI-assisted fraud detection and risk assessments
- Automated customer inquiries for accounts, loans, and investment portfolios
- Personalized financial product recommendations based on user behavior
Media and Technology
- AI-powered content recommendations and dynamic personalization
- Real-time social sentiment tracking for customer engagement
- Automated troubleshooting for customer support
Travel and Hospitality
- AI-curated travel itineraries and personalized booking experiences
- Automated booking charges, cancellations, and refund processing
- Real-time flight status updates and travel alerts
Insurance and Payer Services
- AI-driven claims verification and fraud detection
- Automated policy renewals and modifications
- Real-time customer service for coverage, benefits, and claims
As technology advances, businesses that embrace AI and real-time data will be best positioned for long-term success. Intelligent agents have the power to turn frustration into seamless interactions, leveraging data to create smarter, more responsive engagements.
The Future is Here: Is Your Business Ready?
The pace of AI adoption is accelerating, and businesses that prioritize real-time connected data will be the ones setting the standard for customer experience innovation. The question is no longer if AI will transform CX–but how quickly will your company adapt to stay ahead? Salesforce Data Cloud and Agentforce aren’t just automating interactions, they’re helping businesses turn data into real-time, intelligent engagement that drives lasting value.
Is your organization ready to harness the full potential of AI-driven CX? Let’s Connect!
Solve your toughest data challenges
The Future of AI in Salesforce
Why autonomous agents matter now.
AI used to support you from the sidelines. Now, it’s a part of the team. And that changes everything.
Salesforce’s Agentforce launch offers a glimpse into what’s next: autonomous AI agents handling real work, engaging with customers, and making real-time decisions. Instead of recommending the next best action, these agents are starting to take it.
For businesses, this opens up incredible potential. But, like any new tech wave, there’s a difference between buying the tool and being ready to use it well. Let’s discuss why this matters now – and what it means for your teams.
What’s driving this shift?
Across all industries, teams are pressured to do more with less while delivering personalized experiences faster than ever. However, legacy systems and disconnected data make it incredibly difficult to scale. Frankly, our current ways of working can’t keep up. Sales and service teams are drowning in repetitive tasks, fragmented tools, and rising customer expectations. AI’s next evolution is here to fix that.
A few key forces pushing this forward:
- Data overload: There’s simply too much information for humans to process it all in real time.
- Customer demand for instant answers: Patience is thin. People want speed and accuracy.
- Agent burnout: Teams spend too much time on low-value tasks, not enough on human connection.
Autonomous agents are designed to bridge those gaps. The right ones act like digital teammates – tackling the repetitive stuff so your focus remains where it matters most.
What can autonomous agents do?
If this still sounds theoretical, here’s where it gets real. Early use cases we’re seeing clients test today:
- Resolving routine inquiries: “Where’s my order?” or “Reset my password.” Those simple tasks get done without a human touching them.
- Summarizing complex account data: Instead of scrolling through records, agents pull key points instantly.
- Coaching sales reps in real time: Suggest the next best question, flag buying signals, and cut down ramp-up time.
“By deploying autonomous agents, JPW Industries increased case volume by 15%, cut response time by 12%, and reduced return rates—saving the equivalent of two full workdays.”
The Catch (because there’s always one)
Here’s the thing – the tech is impressive, but it’s not plug-and-play. Launching autonomous agents takes real planning.
- Your data has to be ready: “Garbage in, garbage out” is very real here.
- Guardrails matter: AI needs clear boundaries to avoid hallucinations or bad customer experiences.
- It’s not just about buying Agentforce: It’s about using it wisely.
When done right, AI agents scale your team. Done wrong, they create new headaches. That’s where planning and thoughtful design come in. That’s also why the most successful AI rollouts don’t start with tech – they start with data. If your data isn’t unified, trusted, and accessible, no AI agent, no matter how advanced, can deliver its full potential. We explore that in more depth in our blog about data readiness for AI adoption.
Ready to explore what’s possible?
The companies that win with AI won’t be the first to buy it – they’ll be the first to implement it well. That kind of success takes more than the right tools. It starts with a clear view of your customer journey, strong data foundations, and thoughtful design around how AI supports your people and your goals.
Every organization’s path looks a little different. But the most important step is always the first: asking not just what AI can do but what you’re ready for. That’s where meaningful progress begins.