New tech for customer experience transformation

The days of competing solely on product and price are over. Today, business revolves around the customer—and the experiences you provide them will make or break your brand. Today’s CMOs and digital, sales, and service leaders must consistently maintain profitable growth, scale operations as touchpoints multiply, and draw clarity from increasingly complex, disconnected data.

So, how do you create the type of experiences that woo prospects, inspire customers, and keep everyone coming back for more? Let’s take a look at technology trends that use customer experience (CX) and CRM technologies like AI, augmented reality (AR) and virtual reality (VR), and the Internet of Things (IoT) to transform your customer experiences.

AI in CRM: Turning data into value with AI in CRM

Customer and market data volumes are exploding—streaming into CRM systems from more channels and sources than ever before. But humans can’t keep up, at least not without AI and machine learning. These technologies can make sense of big data, harness it, and learn from it in ways we simply can’t.

For example, look at AI copilots in the flow of work. Embedded copilots summarize customer histories and interactions, prepare meeting briefs, draft sales or service follow‑ups, and suggest next steps. They do all this inside the tools teams already use, so the effort shifts from assembling context to progressing the conversation.

Changing trends in customer service

Customer expectations—including concerns around how organizations use their personal data—have risen along with costs and operational complexity. Today, data lives across more systems and channels than ever before, and teams struggle to act quickly with confidence. Modern CRM is shifting from reactive engagement to real-time customer service orchestration—anticipating customer needs, and then coordinating actions across marketing and service using AI-driven signals. Drivers behind this shift include:

• AI copilots and chatbots
• Automated processes
• Multimodal customer interactions
• Embedded AI in daily decisions

Intelligent CRM automation

By automating key CRM processes, sales, service, and marketing teams can free up their time to focus on more valuable activities, like meeting customer needs and improving their experiences. Automation can also help you widen your net as it gives you the bandwidth to nurture more relationships through the buyer’s journey, identify cross and upsell opportunities, and increase your overall revenue.

For example, lead scoring used to be based on salesperson intuition and educated guesses. With AI, machine learning algorithms can study massive data sets, understand how deals are won and lost, recognize patterns, and identify triggers in the customer’s journey. The algorithm can then automatically apply its learning to the entire sales pipeline and score each lead based on fact, not instinct.

With autonomous workflows, CRM now coordinates end‑to‑end sequences—from lead assignment and approvals to renewals and case resolution. As signals change, the workflow adapts: it assigns the right owner, schedules steps, and updates records, all without manual handoffs.

Hyper-personalization

Traditional personalization includes strategies such as using a customer’s first name in a subject line or sending out a special offer to everyone tagged with the same buyer persona. Hyper-personalization takes much more data into account, not just customer profiles and transaction history, but also online behavior, social media posts, conversational styles, timing and context of past purchases, device type, and even GPS data.

Using this big data along with AI, organizations can more accurately interpret customer intentions, pick up on subtleties, and deliver highly tailored customer experiences. Hyper-personalization allows companies to display specially curated products, and to offer services, promotions, content, and recommendations customized to each customer—automatically and at scale.

CRM chatbots

Multimodal customer interactions now drive conversational flows that blend voice, chat, and images in a natural, increasingly human way. Chatbots not only help customers find answers to basic questions much faster than a rep can, but they can also act as virtual assistants for the sellers, marketers, and customer service agents who use CRM, making agents’ jobs easier and improving their productivity and effectiveness.

A unified conversational AI layer can support both customer‑facing interactions and internal copilots. How? The same conversational layer can power copilots inside the CRM workspace. The conversation engine that interprets language, understands intent, processes context, and retrieves information for customers is the same engine that can:

• Summarize customer interactions for a salesperson.
• Draft replies or recommendations for a service agent.
• Generate insights or next steps within the CRM.
• Assist marketers as they build campaigns.

So instead of building separate systems—one for customer chatbots and another for internal AI assistants—organizations can use a single conversational engine to reduce complexity and increase the value of embedded AI across teams and workflows.

AI-powered customer analytics

Too often, there is a mismatch between what customers want and what companies think they want. AI-powered CRM analytics can fix this issue by analyzing an ocean of data from multiple sources—including customer interactions, internal systems and operations, product usage, and third‑party and external data—to uncover customer insights that would otherwise remain hidden. AI can research and analyze thousands, even millions, of customers to pinpoint their needs, preferences, and interests. AI-enhanced analytics also help customer-facing teams deliver the products, services, content, and experiences they actually want—in real time.

Embedded AI and predictive engagement extend these capabilities even further. Analytics moves from static reports to early signals—such as propensity, sentiment, usage shifts, and overall account health—that feed autonomous workflows. Instead of reacting to a lost deal or an escalated case, teams can intervene earlier with a relevant offer, message, or fix.

AI customer analytics can also dramatically improve sales forecasting, enhance behavior and sentiment analysis, predict potential churn and retention issues, and power one-to-one marketing initiatives.

Immersive customer experiences

The immersive technologies of AR and VR, along with low-cost hardware, have helped forward-looking companies elevate their marketing, sales, e-commerce, and customer service to deliver delightful and differentiated experiences throughout the customer journey. For example, an organization can help customers use AR to scan a malfunctioning product or invite prospects into a VR demo to explore a full environment such as a factory or construction design.

Virtual reality

VR allows users to step inside a computer-generated environment and interact with it. Immersive VR experiences are delivered using headsets, smartphones, hand-held controllers, and even full-room setups.

Some VR examples include:

• Construction site walkthroughs that show investors how a building will look when it’s complete.
• Real estate tours that provide a better buyer experience, speed up sales, and cater to overseas clients.

Augmented reality

AR, on the other hand, overlays digital content on the existing environment. AR-based customer experiences can be delivered through smart glasses, AR applications on smartphones, or specialized screens.

AR examples include:

• Augmented shopping experiences where consumers can point their phone at a product, get more information, and virtually try on clothing and accessories using the camera on their device.
• Using smart mirrors to show shoppers a 360-degree view of themselves in an outfit, compare outfits side by side, change the size or color, get recommendations for complementary items, and ask friends for their opinions on social media.

VR and AR in customer service

Businesses take AR and VR beyond marketing, sales, and e-commerce and apply them to customer service, for example:

• AR can allow customers to hold their phone up to a broken product to get more information about parts, explain complicated issues to agents, or access relevant troubleshooting tips.
• VR can allow customers to see a 3D version of that broken product and walk them through step‑by‑step repair or setup guidance.

As multimodal interactions expand, these conversational and visual interfaces can now share context directly with CRM, meaning AR and VR activity no longer sits in a silo. Instead, what a customer views, tries, or troubleshoots in AR and VR automatically informs the next step in sales, service, or marketing without anyone needing to manually re-enter details.

Internet of Things (IoT)

To strengthen their service operations, many companies now use Internet of Things (IoT) technology, which are connected products that can send real‑time information about how they’re performing. Embedded AI turns these live signals into useful guidance by spotting early signs of issues, suggesting the right time for maintenance, and even drafting customer updates. When something needs human attention, the AI hands the case to a service rep with all the relevant details already organized. This proactive approach helps resolve problems sooner, improves customer experiences, and makes work easier and more efficient for support teams and technicians. It’s a win-win.

IoT in customer service and field service

Before IoT, the customer would have to explain a problem as best they could to a service rep who would try to troubleshoot, and, failing that, dispatch a technician. By connecting IoT device feeds to CRM, the CRM system can automatically create a service ticket, order parts, and schedule a field service technician. Even better, service departments can monitor product data, detect lapses in performance, and identify the cause of the problem before the customer even notices there’s an issue.

IoT in marketing and sales

In marketing and sales, sensor data flowing into your CRM system can let you know how, when, and where individual customers use your products. Predictive usage signals can then drive the next best action, triggering anything from replenishment reminders to value‑based offers through autonomous workflows. With IoT data, sales and marketing people can get to know customer needs, wants, and behaviors on a much deeper level—and deliver the types of experiences that make them feel valued and understood.

Mobile CRM

Mobile CRM—applications that let sales, service, and marketing teams access their most important tools on the go—has been on every major CRM technology list for a decade. But it’s not a bygone trend. Mobile usage has only continued to grow, as have remote work and flexible hours. This means companies need to provide employees with intuitive CRM applications to be their most productive. Today, mobile copilots give field teams fast briefings, capture notes by voice, summarize prior interactions, and schedule follow‑ups—reducing administrative time between visits.

Employees expect to be able to access customer information, track and complete daily tasks, receive notifications and reminders, easily respond to customers, nurture relationships, and collaborate with their teams—from anywhere. Integration with third-party tools like calendars is a must, as is high-quality activity tracking, excellent security, and an offline mode.

In addition to empowering on-the-go employees, mobile CRM can help your team ensure customers get the best possible experience at all times. With real-time notifications and alerts, your people can quickly respond to customers on any channel, including social media. And with access to up-to-date information, they do so with the right background and context.

When AI, automation, immersive tools, and connected data come together, CRM becomes a catalyst for growth rather than a system of record. By adopting these technologies with intention, businesses can turn challenges into momentum and expectations into lasting loyalty.