Customer Success Platforms Enable Hyper-Personalization
Put yourself in the shoes of a consumer. You look down at your phone and see a text message from a company whose brands you use frequently with an offer that seems perfectly matched with your current needs. “Wow,” you think. “This is perfect!” And you click through to order.
The experience, of course, could go the other way. You see the message and somehow it just feels too…personal, bordering on creepy.
That’s the fine line that today’s marketers must navigate as they leverage modern technology to connect with consumers.
Consumers generally appreciate it when companies can provide them with information about products and services that is relevant and tied to their needs, interests, and past purchases. Yet they might balk if this personalization somehow crosses the line—at least in their minds—from feeling helpful to feeling invasive.
Whether consumers feel that personalization is helpful or cringe-worthy is certainly an important consideration for marketers. But potentially an even more important consideration is whether consumers feel that they receive personalized experiences at all.
Several surveys have found that about three-quarters of consumers expect personalized experiences, and though 85 percent of companies think they’re providing them, only 60 percent of consumers agree. Businesses that actually do offer personalization well reap the rewards in increased customer loyalty and retention. On the flip side, companies that fail to provide personalized experiences or that don’t do this well risk losing customers to the competition.
A new marketing technology category called customer success platforms can give them the pathway to success they want.
The Role of Customer Success Platforms
“A customer success platform is really kind of the nerve center for how companies manage ongoing customer value, which is more than just a CRM,” says Nicole McNamara, founder and chief catalyst at business consulting firm Catalyst Innovation and former leader of Salesforce’s Innovation Consulting team. “I think of it as the connective tissue that goes between sales, service, marketing, and product.”
This distinction matters because traditional CRMs focus primarily on managing transactions and contact information, McNamara says. Customer success platforms, by contrast, are designed to orchestrate the entire customer life cycle.
“A customer success platform is a digital solution to help businesses deliver more meaningful, personalized, and long-term relationships with their customers,” adds Joe Welu, CEO and founder of Total Expert, a customer engagement platform provider. “Unlike a traditional CRM, which often focuses primarily on sales management, a customer success platform is designed to help strengthen relationships and deliver lifetime value.”
In the financial services industry, Welu says, success means “staying engaged with consumers as their financial needs evolve so you can educate them about their options, help them make smarter decisions, and build trust to earn lifelong customers.”
Customer success platforms serve as the nexus for data from a wide range of sources, including CRM systems, marketing automation tools, customer support interactions, product usage data, and more. They aggregate this data to provide “a single comprehensive view of each customer,” Welu says. Then these systems leverage intelligent automation to identify opportunities for proactive engagement with customers through relevant content, products, or services.
For instance, Welu says: “If usage patterns suggest a customer might not be realizing the full value of a product, the platform can trigger a personalized email or text message offering information about the product, the benefits of using it, or even how to get started.” In essence, he says, these systems transform raw data into actionable strategies to ensure that customer needs are anticipated to reduce customer churn and maximize lifetime value.
That’s no easy task. As Balaji Balasubramanian, president and chief product officer for SAP Customer Experience, explains: “Success depends on the ability to harmonize data across structured and unstructured sources, first-party and third-party, so every decision and interaction is grounded in real-time intelligence.”
The Four Pillars of Effective Hyper-Personalization
McNamara’s team at Salesforce identified four critical requirements that companies must satisfy to achieve true hyper-personalization. These pillars provide a framework for evaluating readiness and identifying gaps.
Pillar 1: A Connected Technology Stack
“You have to have a tech stack that is connected,” McNamara emphasizes. “CRM has to be at the heart of it, but it can’t stop there. It has to be connected to your [enterprise resource planning system], your marketing stack, and your service platform as well. Those things have to be connected; it doesn’t have to be the same technology, but they do have to be intentionally connected.”
This connectivity challenge is more complex than many organizations realize. As Keri McGhee, chief marketing officer of Attentive, a marketing platform provider, explains: “The biggest hurdle I see brands facing is fragmentation, or lots of data, but no easy way to connect the dots. That’s where AI and identity resolution come in, helping unify data across channels so brands can deliver truly one-to-one experiences at scale.”
Pillar 2: Customer-Centric Business Processes
“You have to have customer-centric business processes,” McNamara continues. “Customer success will have their own metrics, their own understanding of customer needs, and they’re not [necessarily] communicating with the sales organization, the marketing organization, the product organization. Because of that, customer needs are falling through the cracks.”
This requires mapping business processes to customer needs rather than internal departmental structures. Yad Senapathy, founder and CEO of the Project Management Training Institute, has witnessed this transformation firsthand: “I have seen companies using these platforms to reduce their churn rates by more than 30 percent simply by being proactive as opposed to reactive.”
Pillar 3: One Team Around the Customer
The third pillar demands organizational alignment that transcends traditional silos. “You have to have what we call ‘one team around the customer,’” McNamara explains. “No matter where you are inside of the organization, whether you’re in a back-office function like finance or procurement or legal, you have to have access to the right and the exact same information as people in customer-facing roles.”
This shared visibility enables coordinated responses to customer needs. As Kenny Keesee, who leads global support at sales platform provider Apollo.io, puts it: “Instead of the spray-and-pray model you can nudge the right person with the right message at the exact right moment.”
Pillar 4: The Data Flywheel
The fourth pillar creates a virtuous cycle where customer experiences generate data, data drives insights, and insights fuel improved experiences. “When companies do this really well, they have a data flywheel,” McNamara notes. “They create an experience that drives a certain set of data. That data then leads to an insight, and now they can create a new experience as a result of it.”
McNamara illustrates this with Amazon’s returns process: “The company has made returning really easy. Why do they do that? Not because they want all their stuff to be shipped back to them but because the data that a customer is giving them in that transaction is worth far more than the cost of postage.”
AI as the Personalization Catalyst
The integration of artificial intelligence transforms customer success platforms from reactive systems into predictive engines.
McGhee explains how Attentive leverages AI for hyper-personalization: “Built in-house and trained on a proprietary model that analyzes trillions of data points sourced from 90 billion SMS messages in real time, Attentive’s AI is setting a new standard for this type of personalization. Our agents pull together customer signals like shopping behavior and engagement history to figure out who to reach, when to reach them, and what to say.”
AI’s advanced technology capabilities drive several key functions to make personalization both possible and personal.
Predictive intent recognition, for example, can identify when customers are poised to need specific products or services. As McGhee explains: “Say a shoe brand knows when their runner’s shoe will wear out from use. Our personalization engine considers that and will message the customer when it’s time to refresh the footwear.”
In a similar vein, AI can identify subtle signals pointing to emerging customer needs or risks. It can then prompt users to reach out in specific ways, as Anupa Rongala, CEO of business process outsourcing firm Invensis Technologies, explains: “A drop in usage can lead to a proactive support message, and an increase in adoption can lead to focused upselling. This method of planning makes sure that outreach feels timely and relevant.”
AI is also able to generate personalized content at scale, meaning that brand-consistent messaging can be sent to thousands of customers without the type of variance that could occur when messaging is sent by humans. This addresses a major challenge, McNamara says. “If you’re framing a question or prompting [a large language model] one way, and I’m prompting it another, and we’re using company marketing language differently, that creates a real perception and brand problem.”
Importantly, AI can continually refine its personalization based on customer responses and outcomes, meaning that customers are more likely to get the service, communication, and offers that are most likely to interest them over their life cycle with the company. It’s not up to chance or attentive salespeople; technology drives ongoing understanding and enables more timely and accurate customer data.
Of course, despite these AI tools’ potential, actually achieving desired results can be challenging due to legacy systems, budget limitations, adoption challenges, and other organizational and technological barriers.
Overcoming Implementation Challenges
The primary challenge, aside from harnessing the data, is that, in many cases, “the IT side of the house that controls the data and the master data is not talking to the business,” McNamara says. That misalignment is greater than anything else she sees.
The solution requires collaborative design sessions where both sides architect the future. “Companies have to get into a room and design the future together,” McNamara insists. “You haven’t gone through the hard work of doing customer empathy mapping so you understand what they’re going through. You haven’t gone through the journey mapping exercise.”
A particularly dangerous pitfall involves over-customizing platforms rather than leveraging out-of-the-box functionality. McNamara warns: “Companies that are taking a product like Microsoft Dynamics or Salesforce and over-customizing it, as opposed to using its out-of-box functionality, are in a real pickle right now because they can’t unwind decisions that they made forever ago.”
To address these challenges, McNamara strongly recommends external help: “9.5 times out of 10 you need a third party because of orthodoxies, because people are tied to the way things have been done, because they feel like it could be a power grab, and because we’re human. We cannot do this alone; we’re too close to the forest to see the trees.”
Seeking an external view, McNamara says, can help overcome what she calls “orthodoxies”—deep-rooted beliefs that can prevent progress. “It’s not that the technology can’t do what you want,” she explains. “It’s that the people and processes are not written and collaborating in service of making the technology work.”
Success through hyper-personalization done well can be significant. McGhee shares how wellness brand OLLY transformed fragmented data into actionable customer profiles. “By adopting Attentive’s AI Pro for Email, OLLY was able to transform fragmented data into actionable customer profiles. Now, we help OLLY recognize shoppers across channels and consolidate behavioral insights into real-time intelligence.”
The results were substantial: “Personalized recommendations at a regular cadence have generated more than 40 percent of a typical month’s email revenue,” McGhee shares. “Campaigns powered by AI Pro achieved a 201 percent increase in revenue and nine times the ROI compared to baseline.”
Some of the important metrics companies should monitor and compare to benchmark and historical data might include repeat purchase rates and frequency, cross-sell and upsell conversion rates, churn reduction, time to value for new customers, and Net Promoter Score (NPS) improvements.
And one final caveat: Customer success platforms provide the technological foundation, but success ultimately depends on organizational commitment to putting customers at the center of every business decision.
AI and hyper-personalization offer the opportunity to build a strong, sustainable competitive advantage. Customer success platforms, powered by AI and informed and managed by empathetic humans, can ensure that customers are pleased rather than peeved by the outreach and communication they receive. As more and more companies adopt this technology, it will no longer be an option but a must-have. Early adopters are likely to have an edge.
Linda Pophal is a freelance business journalist and content marketer who writes for various business and trade publications. Pophal does content marketing for Fortune 500 companies, small businesses, and individuals on a wide range of subjects, from human resource management and employee relations to marketing, technology, healthcare industry trends, and more.