AI, Personalization, and the New Customer Journey
- Lokesh Alluri, Senior Manager, Digital and Customer Analytics at Lenovo
- AI and Automation, Campaign Optimization, Content Strategy and Marketing, Customer Data Platform (CDP), Customer Experience (CX), Data Management and Analytics, Digital Transformation, Managing Org Transformation, Managing Your Career, Martech Stacks, Multi-Channel Journeys, Other Martech, Platform and Data Integration, Sales and Marketing Orchestration, Strategy and Trends
Artificial intelligence is rapidly reshaping how brands understand customers, personalize experiences, and make decisions. The Martechify team sat down with Lokesh Alluri, Senior Manager of Digital and Customer Analytics at Lenovo, to discuss the evolving role of analytics, the future of customer journeys, and why human judgment may become even more valuable in an AI-driven world.
Watch the full interview with Lenovo’s Lokesh Alluri to hear his perspective on AI, personalization, and the evolving customer journey. Learn how analytics, LLMs, and human judgment are reshaping martech strategies and helping brands create more seamless, human-centered experiences.
From pocket to cloud: Understanding Lenovo's scope and personalization
Many people know Lenovo for ThinkPad laptops, but the company’s reach goes much further. “We sell and we operate in about 180 markets, and we sell direct to consumers via our e-commerce group,” said Lokesh. The product range spans from consumer products like Motorola phones to enterprise servers. “We sell a lot of devices, from phones to laptops. And we have a huge variety of tablets all the way to servers for server setup.”
At this scale, personalization takes on a different meaning entirely. “How do we convert each click into an amazing experience for our customers? That’s what personalization means to us at our scale,” Lokesh noted. His role spans a unique intersection: “My role currently sits at the intersection of martech, analytics, and personalization to enable our business [to] make smart additions. My job is to make sure we’re using data the right way to create seamless and intuitive experiences for our customers.”
For Lenovo, personalization means:
— Helping customers navigate complex product decisions
— Delivering intuitive, seamless digital journeys
— Ensuring relevance without intrusion
At this scale, personalization is not about inserting a first name into an email. It is about orchestrating data, experimentation, and content across markets in a way that feels coherent and human. Lokesh reflected, “I think at this point, personalization is more of an expectation from customers. Every customer is expecting the brand to personalize the experience for them. So now the real differentiator in that aspect is as a brand, how do I deploy personalization in a way that is helpful and is not intrusive?”
He also underscored that privacy and compliance, both on-site and off-site, are more critical now than ever before.
At this scale, personalization takes on a different meaning entirely. “How do we convert each click into an amazing experience for our customers? That’s what personalization means to us at our scale,” Lokesh noted. His role spans a unique intersection: “My role currently sits at the intersection of martech, analytics, and personalization to enable our business [to] make smart additions. My job is to make sure we’re using data the right way to create seamless and intuitive experiences for our customers.”
For Lenovo, personalization means:
— Helping customers navigate complex product decisions
— Delivering intuitive, seamless digital journeys
— Ensuring relevance without intrusion
At this scale, personalization is not about inserting a first name into an email. It is about orchestrating data, experimentation, and content across markets in a way that feels coherent and human. Lokesh reflected, “I think at this point, personalization is more of an expectation from customers. Every customer is expecting the brand to personalize the experience for them. So now the real differentiator in that aspect is as a brand, how do I deploy personalization in a way that is helpful and is not intrusive?”
He also underscored that privacy and compliance, both on-site and off-site, are more critical now than ever before.
The evolving role of analytics in an AI world
As AI transforms the analytics landscape, Lokesh sees a fundamental shift approaching. “I think what analysts will do more and more going forward is to spend more time thinking as opposed to doing, because I think the doing part can be handled by AI more efficiently as time passes,” he observed.
This evolution requires analysts to move beyond traditional reporting. “As an analyst, I should not be just crunching numbers and generating reports. I should always think: Will whatever I do in this report enable a particular decision? Will it move the needle in the right direction?”
The key differentiator, he says, lies in human judgment and strategic thinking. Lokesh referenced advice from Ajit Sivadasan, Lenovo’s former President of Global eCommerce: “You cannot out-AI AI; you can only out-human AI.” This philosophy shapes how he sees the future of brand success and how he approaches hiring and team development.
This evolution requires analysts to move beyond traditional reporting. “As an analyst, I should not be just crunching numbers and generating reports. I should always think: Will whatever I do in this report enable a particular decision? Will it move the needle in the right direction?”
The key differentiator, he says, lies in human judgment and strategic thinking. Lokesh referenced advice from Ajit Sivadasan, Lenovo’s former President of Global eCommerce: “You cannot out-AI AI; you can only out-human AI.” This philosophy shapes how he sees the future of brand success and how he approaches hiring and team development.
Hiring in the age of AI assistants
When recruiting recent graduates who rely on the latest AI tools to support their work, Lokesh focused on fundamental human capabilities. “We are all equipped with AI technology… the differentiator that I look for is that curiosity and critical thinking.”
He’s not opposed to candidates using AI tools during assessments. Instead, he evaluates depth of understanding: “There is no problem with them using Claude code or ChatGPT or whatever, but is there a depth? Did they really understand the problem that I’m trying to solve for?”
He’s not opposed to candidates using AI tools during assessments. Instead, he evaluates depth of understanding: “There is no problem with them using Claude code or ChatGPT or whatever, but is there a depth? Did they really understand the problem that I’m trying to solve for?”
Customer journeys in the LLM era
The emergence of Large Language Models has fundamentally altered customer behavior, as Lokesh discovered through his own experience. He illustrated the shift with a personal example of purchasing diamond earrings, first turning to ChatGPT to understand clarity, shape, and certification before engaging with retailers.
“Pre-LLMs, I think that journey would have been much longer,” he reflected. “For a big purchase over $2,000, especially for a product with multiple components, I’d go through weeks of research. Now my journey has shrunk because I arrive on the retailer site more educated.”
This shift challenges traditional funnel thinking. Customers may arrive at brand websites already educated and ready to purchase, compressing what were previously lengthy consideration phases.
“Pre-LLMs, I think that journey would have been much longer,” he reflected. “For a big purchase over $2,000, especially for a product with multiple components, I’d go through weeks of research. Now my journey has shrunk because I arrive on the retailer site more educated.”
This shift challenges traditional funnel thinking. Customers may arrive at brand websites already educated and ready to purchase, compressing what were previously lengthy consideration phases.
Current martech trends and data governance
Lokesh believes customer data platforms (CDPs) will remain foundational in helping brands unify fragmented customer journeys, but the rise of generative AI introduces a major new blind spot. “CDPs are still prevalent in terms of piecing together various aspects of customer data so that we at least know what the unified view of the customer or unified journey across channels and devices looks like,” he explained. However, interactions happening inside large language models represent “the missing piece in the recent shift in journeys.”
Today, marketers can connect signals from channels like search by analyzing keywords in platforms such as Google Ads, but similar visibility doesn’t yet exist for AI-driven discovery. As LLM platforms increasingly begin to serve ads and recommendations, Lokesh expects new mechanisms to emerge that surface at least partial signals such as customer intent or the context behind a query. “If not the whole prompt, at least [the AI engine] will tell us what the intent of the customer was or what they were looking for,” said Lokesh.
Those insights could help brands move beyond simply labeling traffic as a “ChatGPT or Claude hit” and instead integrate richer data into their systems to better personalize experiences. According to Lokesh, this will likely require “a lot of architectural shift” in martech stacks to accommodate new dimensions of AI-mediated customer behavior.
Today, marketers can connect signals from channels like search by analyzing keywords in platforms such as Google Ads, but similar visibility doesn’t yet exist for AI-driven discovery. As LLM platforms increasingly begin to serve ads and recommendations, Lokesh expects new mechanisms to emerge that surface at least partial signals such as customer intent or the context behind a query. “If not the whole prompt, at least [the AI engine] will tell us what the intent of the customer was or what they were looking for,” said Lokesh.
Those insights could help brands move beyond simply labeling traffic as a “ChatGPT or Claude hit” and instead integrate richer data into their systems to better personalize experiences. According to Lokesh, this will likely require “a lot of architectural shift” in martech stacks to accommodate new dimensions of AI-mediated customer behavior.
Brand differentiation in an AI-saturated market
As AI tools become commoditized, authentic storytelling becomes the ultimate differentiator. “Now more than ever, brands are enabled with best-in-class technology and best-in-class AI—everybody will have access to that,” he said. “I think brands will start to out-human each other by sharing the authentic core story of who they are. That will be the differentiator.”
Looking forward
For global enterprises navigating the intersection of scale, personalization, and AI, Lokesh’s insights offer a roadmap. Success requires robust data foundations, human-centered AI implementation, and authentic brand storytelling. As customer journeys continue evolving with new technologies, the brands that thrive will be those that combine technological sophistication with genuine human connection.
The question isn’t whether AI will transform martech operations, but how quickly organizations can adapt their strategies, teams, and customer experiences for this new reality.
The question isn’t whether AI will transform martech operations, but how quickly organizations can adapt their strategies, teams, and customer experiences for this new reality.
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