In service, sales and operations, AI is becoming part of the process itself, or is doing away with processes that in the past had to be optimized. Much like the move to digital, only on a far larger scale.
If the AI discussion has so far been confined to chat interfaces, (Front-end) it is now clear that the real strategic value lies in changing the deep operational structure. The question is no longer “how will AI answer the customer”, but “how will AI reorganize the company” so as to shorten SLAs, streamline the Back Office and produce a final resolution at first contact.
The move from reactive management to proactive management begins with the “democratization of expertise”. Once AI systems put complex insights in front of the first-line agent in real time, the need to “check with the Back Office” fades away.
In retail, AI connects the supply chain to customer service; smart systems spot a stock delay before the customer is even aware of it and authorize the agent to offer compensation or an immediate alternative, heading off repeat contacts and keeping satisfaction high.
In hospitality and complex services too, the revolution shows up in the optimization of task routing (Dispatching). Instead of the customer waiting for a status check, AI identifies the substance of the request and assigns it directly to the most available and most suitable service provider.
The Back Office holds many processes in the customer value chain that involve processing information and reaching a decision, and that until now have depended on a human service provider. Bringing AI in can shorten the process considerably, sharpen its accuracy and reduce risk.
Checking eligibility under an insurance policy, for example, or reviewing supporting documents in a request to approve a service under the health basket, and so on, today rest on the agent doing the review, take a great deal of time and depend on that person’s level of knowledge and precision.
AI also enables a shift from random statistical quality control to continuous control of 100% of interactions, which makes it possible to identify process failures the moment they occur and correct them immediately.
We see this today in advanced healthcare organizations, where AI manages patient flow by predicting appointment cancellations and automatically slotting waiting lists in by clinical urgency, which shortens the SLA to treatment with no human hand involved.
Where do you start? The strategic Assessment stage Rolling out AI is not a technology project, it is an exercise in process engineering. The first step for any senior management team is to run an Operational Assessment to identify the quiet bottlenecks, the places where information stalls or requires manual approvals. That process includes mapping the customer journeys against current Back-Office capabilities,
defining new success metrics (KPIs) focused on shortening SLAs, and building a roadmap for rolling out tools that support decision-making in the field. Only a precise link between business strategy and operational infrastructure will let the organization harness the power of AI and turn service into a winning competitive asset.
In short, this is the time to act, to think big and to start small.
At the executive roundtable led by 7I’s together with Tiff and CommBox, held in October 2025,
we examined personalization in service from several different angles
The journey from personal service in the branch to personalized service in digital
Customer service used to rest on a personal relationship with a representative at the branch – a banker, a doctor, an insurance agent or a salesperson. Personal familiarity, a face-to-face conversation, and reading needs out of human interaction were the basis of the service experience. As Asaf Eldar, Head of the Retail Division at Discount Bank, described it,
“Walking into the bank and seeing a familiar face gave me a different feeling… It will be hard to reproduce the depth of emotion people felt – it probably creates far more chemistry than I can imagine.”
Over the years, and mainly on the back of accelerating digitization – including COVID and the war – service moved to central contact centers, apps and websites. The central challenge: how do you preserve that personal, empathetic feeling when the service is delivered remotely and automatically?
Today, leading organizations are building Hyper-Personalization capabilities – deep personalization based on data, AI, and precise identification of the customer’s needs in real time. The goal: to bring the personal feeling back, this time with technology.
Why does this matter now?
Customers are already there. They are used to tailored service from platforms such as NETFLIX – 80% of viewing on Netflix is the result of personalization – and the same holds for digital platforms like Amazon and Google.
Customers expect the organization to recognize them, understand their needs, and offer them the right thing, at the right time, in the right channel. As Asaf Eldar put it, “in the end people want an answer to the need they have right now”
A 2025 Medallia survey covering the preferences of 23,000 customers found that 61% of consumers are willing to pay more for a personalized experience, while only about 25% of consumers have experienced a very high level of personalization
“Personalization is a question of resolution”
Eldar highlighted the gap between what organizations imagine and what customers actually need, and warned against shallow personalization built on nothing more than basic customer details.
Udi Asulin, Head of the Telephone Service Operation at Maccabi Healthcare Services (a large Israeli HMO), described the launch of specialized contact centers serving different populations. On the face of it that could have cost operational efficiency, but in practice it produced a 10% drop in repeat calls. In his words,
“If we do not know how to connect to the customer’s needs, to make the service accessible to them using the information we already hold – then it is not really personal, and we will never get to hyper.”
We also learned that if you are going to personalize, it had better be accurate. 61% of consumers say that “reliable information” is the single most important element of the customer experience (Qualtrics 2025)
Shai Ben Moshe, Head of the Customers, Sales and Service Division at Bank Hapoalim, stressed the importance of precision in personalization:
“If we offer a customer something that does not suit them – it annoys them, and it produces the opposite result.”
53% of consumers say they will cut their spending on a brand after an unsatisfactory experience (Qualtrics 2025)
We learned that it is worth examining and sharpening the line between personal service and the customer’s privacy.
Udi Asulin of Maccabi noted that customers mostly expect us to use the information we hold, while medical confidentiality of course does not allow it, and that creates a gap between expectations and data protection. Nir Lautman, Chief Customer Officer at Clal Finance and Insurance described how they chose instead to surprise customers in places with no connection to insurance at all – happy moments, such as sending a gift to a new mother.
Lautman (Clal) shared that in insurance, knowing the customer is the basis for pricing the premium. Recently it has become possible to raise the resolution using data, understand the customer’s individual needs, and build products that fit them – Clal BEHAVE in motor insurance, for example, which uses driving monitoring to let customers who drive carefully pay less.
Aliza Gavra CDO and CX at – MAX, described how a location-based service they offered customers was read by those customers as “Big Brother”, and after reviewing the reaction they decided to withdraw it.
Elad Mizrahi, CEO of Tiff described the rollout of bots together with CommBox and stressed the importance of process continuity around anything that starts in a bot.
Consistently examining customer intent and the actions the bot failed to close, while carrying all the information forward into the rest of the journey, is a necessary condition for building customer trust in personalization that no human is running.
We are all only at the beginning this is the time to dream
Even the leading organizations are at the early stages of implementing Hyper-Personalization. This is a long journey, and it takes patience, trial and error. 
As Asaf Eldar noted,
“The war was a catalyst for a great many technology processes – it cleared the blockages and accelerated projects that had been planned for six months and closed in two weeks.”
According to the 7I’s 2025 survey, among the 40 companies taking part in the roundtable, 50% of organizations in Israel already include personalization in their strategy, only half of those have put a budget behind it, and fewer still have aligned the organization’s targets to it.
Karni Kaplan, an expert in operations and technology for the Contact Center, noted in her talk that although the expectation had been that AI’s impact would show up as efficiency gains in staffed service, adoption of AI tools in customer service stands at just 24%
Technology is a condition, but not a sufficient one
Advanced technology infrastructure and AI capabilities are indeed required, but the drive has to come from the organization itself.
The change involves adjustments to the organizational structure, to service and sales processes, to metrics and to culture. Udi Asulin, for example, described how Maccabi Healthcare Services mapped its customer journeys in detail together with the medical division, which led to a significant improvement in the availability of physiotherapy services.
Aliza Gavra stressed the importance of organizational structure:
“There is genuinely a role like that in the structure – a customer experience manager – whose job is to listen, to understand, and to give the right thing.”
Quality data is the foundation for everything
Without a strong, clean, up-to-date database there is no way to produce personalization. Aliza Gavra (MAX) reminds us that data is the fuel that drives the engine, and that quality data is the foundation for everything. Without it, she argues, there is no real personalization. Aliza also reinforced the need to fit the customer experience to the different identities of the same customer, and the importance of measuring digital channel adoption accurately.
According to the 7I’s June 2025 survey, 88% of organizations report that they are not exploiting the full potential of their data for personalization.
We asked participants what can be learned from their experience – how do you start well?
- Dream big, start small – do not wait for the perfect solution. Start with small, measured steps that create immediate value. Asaf Eldar’s advice: “better to give the customer something than to try to build the whole dream.”
- Identify the high-value populations and events – focus on the cases where Hyper-Personalization will create real benefit for the customer and for the organization. Clal Insurance, for example, developed a product that monitors customers’ driving behavior and offers them a premium tailored to it.
- Work at the organizational level as well – cultural change is a condition for success. Personalization is not only technology – it is a new way of thinking. As Asaf Eldar noted, “as Israelis we need to know our customers – to know they are looking for protektzia, the inside track – and turn that into personalization.”
After an interesting day, we concluded…
Hyper-Personalization is not just a buzzword – it is a deep shift in thinking. Organizations that can balance technology, data and human sensitivity will lead the market. The executives who took part stressed one point: this is a journey that demands vision, flexibility and a genuine ability to listen to the customer.
]]>Advanced technologies and fast, real-time data processing are slowly freeing us from classifying customers on the basis of historical data. They allow ever-greater personalization of the service and the product to the individual customer, matched also to the moment of consumption, to geographic location at that time, and to further contextual variables. Heightened personalization – Hyper Personalization is built on analysis of historical data combined with forecasts.
This is going to get interesting… for every one of us, personally
We are all already well familiar with the way Netflix, Spotify and Wolt match content, based on viewing history, searches and preferences, on the viewer’s profile, on geography and even on the time of day.
Imagine that kind of service at the bank, at the HMO (health fund), at the clothing store, at the supermarket… it is not far off.
hyper personalization, then, is a business strategy that uses advanced technologies to deliver highly personalized experiences, products or services based on the customer’s behavior and preferences and on the context they are in.
hyper personalization uses technologies such as artificial intelligence (AI), creative intelligence, machine learning (ML) and real-time data analysis to create heightened personalized experiences for customers. It goes well beyond the basics such as addressing customers by name or recommending products based on their purchase history. hyper personalization draws on far more data, more current and more precise: browsing patterns, location, preferences, similar customers, and contextual factors such as the weather or the time of day.
hyper personalization is steadily gaining ground in sectors such as retail, entertainment, healthcare and banking, improving the user experience and raising customer engagement.
Customers like it, they even expect it.. it is taken for granted
Heightened personalization is welcomed. According to a study by the IBM Institute for Business Value, three in five consumers want to use artificial-intelligence applications while they shop. Another study, by McKinsey, found that 71% of consumers expect businesses to deliver personalized content. Of those customers, 67% say they feel let down when their interactions with businesses are not matched to their needs.
Consumers expect interactions matched to their preferences, their behaviors and their particular needs rather than generic approaches. hyper personalization answers that demand while strengthening customer-retention strategy. The benefits of personalized marketing show up in hard results: according to McKinsey, it can cut customer-acquisition costs by up to 50%, lift revenue by 5-15% and raise marketing ROI by 10-30%.
When customers feel understood and valued, they are more likely to connect with the brand, buy again and build long-term loyalty. That emotional connection is a differentiator in a competitive market. Customers favor brands that understand and prioritize their individual needs and preferences.
hyper personalization also supports innovation. Collecting data and analyzing customer behavior lets businesses understand emerging customer trends and behaviors in depth. These activities sit alongside initiatives in which businesses use technology to sharpen their strategies, develop new products and anticipate future customer needs.
How hyper personalization differs from traditional personalization
The main difference between hyper personalization and traditional personalization lies in the depth of the data used and in the degree of tailoring. Personalization as practiced to date generally uses basic customer information such as names, purchase history or demographics, in order to create generic personalized experiences.
Mentioning a customer’s name in an email, or recommending products based on earlier purchases, is traditional personalization. With the tools we had before the AI revolution this was certainly effective up to a point. The technology allowed analysis of static data, which could miss the customer’s changing needs or preferences.
hyper personalization goes beyond those tactics through advanced technologies such as artificial intelligence, machine learning and real-time data analysis. It draws on a wide range of data including behavioral patterns, browsing activity, location, device usage and even contextual factors such as timing, phone type or the weather.
That depth lets businesses create highly personalized, dynamic experiences that adapt to the customer’s evolving context. An e-commerce platform, for example, might recommend products in real time based on a customer’s recent clicks, their preferences and current trends among similar users.
Combining historical data with forecasts and external data
Traditional personalization is also reactive, based on past data. hyper personalization is proactive, using predictive analytics to offer more relevant experiences. It analyzes patterns in customer data in order to predict future behaviors or preferences. That capability lets businesses anticipate customer needs before those needs are stated explicitly. This level of sophistication makes hyper personalization effective at creating meaningful engagement, raising conversion and building customer loyalty.
Implementing hyper personalization requires a robust, integrated data infrastructure and a commitment to data privacy. Businesses must handle sensitive data and customer data responsibly, and comply with privacy-protection regulation, in order to preserve trust.
hyper personalization is not just technology – it demands serious organizational readiness – it is a revolution
The heightened-personalization process is already under way, at one stage or another, in every organization. Can it be implemented within the setups that already exist?
Traditionally, organizations are set up around definitions and classifications known in advance. We are used to tying the service channel to the handling party, and the customer classification to the SLA and the service provider. The heightened-personalization revolution forces us to create a flatter and more flexible world.
To set and enable the handling party, the SLA and the other parameters that shape the service, the product, the price and the operation for every single interaction, we need an organizational structure that is flatter, more flexible and more complex. And a move to an operating model that supports this organizational transformation.
The change is sweeping and calls for adjustments on every front:
Technology, systems integration and data management
And on the organizational fronts: strategy, workforce, skills, compensation models, regulation and legal risk, operating and management methods, KPI’s, management routines and organization – every organizational component needs to be adapted to the new world.
hyper personalization creates business value on every front
hyper personalization is a powerful instrument in the customer economy and delivers benefits across many business fronts: an improved customer experience, higher customer engagement and with it stronger retention and loyalty, consistency across channels, revenue growth, operational efficiency, proactivity in service and in sales, better marketing ROI, deeper insight into customers
When will we succeed – when the technology meets the business and the organization
The move from personalized service to Hyper Personalization creates significant challenges, but also opportunities to improve the customer experience and increase customer loyalty. Advanced technologies let businesses deliver customer experiences that are distinctive and highly personalized. For that to succeed, the business and organizational thinking has to be adjusted on every front.
A comprehensive rollout of heightened personalization – covering both the technology adjustments and the matching organizational readiness – can drive accelerated business growth.
Sources:
What is hyper-personalization IBM
How Generative AI Is Driving Hyperpersonalization – Forbes
Hyper-Personalization vs. Personalization: Hyper-Personalizing the Customer Experience -mendix
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