Your Next Customer Might Not Be a Person

September 24, 2026


For most of ecommerce history, the process has been straightforward.


A person searches for a product. They compare a few options. They visit a store, read the product page, make a decision and complete the purchase.


AI is beginning to change that process.


A series of recent announcements points toward a different version of online shopping, one where AI doesn't simply recommend what someone should buy. It can search, compare, communicate with businesses and increasingly take action on the customer's behalf.


At the same time, AI is appearing on the other side of the transaction too. Businesses are beginning to use AI agents to monitor ecommerce stores, identify problems and even conduct conversations with customers.


Put those developments together and something interesting starts to emerge:


AI could increasingly operate on both sides of ecommerce.


AI Agents Are Starting to Buy Things


One of the biggest steps toward this future is giving AI the ability to actually complete transactions.


Mastercard's Agent Pay initiative is designed to enable AI agents to make payments on behalf of consumers while maintaining authorization and controls around the transaction.

New integrations are beginning to connect that infrastructure to AI agents. Google and its partners are also developing technology intended to make it easier for AI agents to discover products and transact with participating businesses.


That changes what an AI shopping assistant could eventually do.


Today, you might ask an AI:

“What's the best hiking backpack under $200?”


It can research the question and recommend several options.


The emerging model goes further.


You could tell an AI what you need, your budget and your preferences. The AI could search different stores, compare products, evaluate prices and availability and eventually help complete the purchase.


The customer moves from doing the shopping to describing the outcome they want.


Shopping Could Become a Conversation


This could also change how people discover products.


Traditional ecommerce requires customers to navigate categories, search results, filters and product pages.


AI allows the interaction to begin with a request instead.


“Find me a lightweight laptop under $1,000.”


“I need a birthday gift for a seven-year-old who loves Minecraft.”


“Find running shoes similar to these, but under $150.”


Instead of figuring out which keywords, filters and websites to use, the customer simply explains what they want.


The AI can do more of the searching and comparing.


For businesses, that introduces an entirely different kind of customer journey. A potential buyer may never browse a website the same way a person does. An AI could increasingly become the layer between the customer and the businesses competing for that purchase.


Even Advertising Could Become Conversational


Advertising may change for the same reason.


OpenAI is testing Sponsored Agents that can allow someone to move from an advertisement into a conversation with an AI agent created by the advertiser. The early integrations described include Shopify for ecommerce and HubSpot for CRM.


That's a very different interaction from clicking a traditional digital ad.


Instead of:


Ad → landing page → browse → form or checkout


the experience could increasingly look like:


Ad → conversation → questions → recommendation → action


A customer could ask about availability, specifications, pricing or which product fits their situation without navigating several pages to find the answer.


The advertisement stops being only a doorway to a website. It can become the beginning of the sales conversation.


But AI Isn't Only Appearing on the Customer's Side


This is where the bigger shift becomes more interesting.


While some companies are building AI that shops for customers, others are building AI that works for the businesses selling to them.


Noibu, for example, recently introduced AI agents designed to monitor ecommerce operations, identify problems, diagnose issues, propose fixes and measure the results.


Tasks that traditionally required someone to continuously inspect analytics, identify problems and determine what needed attention can increasingly be assisted by software operating in the background.


That doesn't mean an AI is suddenly replacing an entire ecommerce team.


But it does mean the software businesses use is beginning to move beyond simply reporting what happened.


It can increasingly identify what needs attention and help determine what should happen next.


AI Can Talk to Your Customers Too


Customer research is changing in a similar way.


Marvin recently introduced Live Intercept, which uses AI to conduct customer interviews directly on websites. The system can ask follow-up questions based on someone's responses and conduct conversations across more than 40 languages.


Traditionally, meaningful customer research might require recruiting participants, scheduling interviews, conducting them and analyzing the results.


AI makes it possible for parts of that process to happen continuously.


A business could potentially learn why customers hesitate, what they're looking for or what confused them while those customers are actually interacting with the business.


Again, AI isn't just sitting on the customer's side helping someone shop.


It's sitting on the business side helping the company understand the person shopping.


AI Could Be on Both Sides of the Transaction


Taken individually, these announcements look like separate technology stories.


Payments for AI agents.


Conversational advertising.


Automated ecommerce monitoring.


AI-powered customer interviews.


Taken together, they point toward something bigger.


On one side of a transaction, an AI could search for products, compare options, communicate with sellers and help make a purchase for a customer.


On the other side, another AI could monitor the store, answer questions, analyze customer behavior and help the business improve its operation.


We aren't at a point where this describes everyday ecommerce. People are still browsing websites, comparing products and clicking checkout buttons themselves.


But the infrastructure for something different is being built.


And if these technologies continue developing in the same direction, ecommerce may increasingly involve something that would have sounded strange only a few years ago:


AI doing business with AI.


Sources


Practical Ecommerce: New Ecommerce Tools, September 23, 2026

Your Next Marketer Might Need to Code

October 26, 2026
Marketing is becoming more technical. As businesses adopt AI tools, automation and increasingly complex software, a new kind of specialist is emerging: the marketing engineer. For years, businesses have built marketing teams around familiar responsibilities: advertising, content creation, search engine optimization, social media and lead generation. Those responsibilities haven't disappeared. But the technology behind them has become increasingly complicated. Businesses now rely on advertising platforms, customer relationship management systems, email automation, website analytics, e-commerce software and AI tools. Making those systems work together is becoming an important part of marketing performance. That's where the marketing engineer comes in. What Is a Marketing Engineer? A marketing engineer combines marketing knowledge with technical skills. Traditional marketing specialists might develop a campaign strategy, create content or manage advertising budgets. A marketing engineer can help build the technical systems that make those activities more effective. That might involve connecting a CRM to advertising platforms, automating reporting, improving conversion tracking, integrating customer data or developing workflows using APIs and AI tools. The role connects marketing strategy with technical execution. Rather than relying entirely on separate developers, analysts and software specialists, businesses can use technical marketing expertise to bridge those functions. The Problem With Disconnected Marketing Systems Many businesses already have the technology they need. The challenge is getting it to work together. A company might use Google Ads to attract customers, Shopify to process orders, Klaviyo for email marketing and a CRM to manage relationships. Each platform collects information, but that doesn't necessarily mean the information is connected. Employees may still need to download reports, transfer leads between systems, update spreadsheets or manually compare campaign results against actual sales. Those disconnected processes can make marketing slower and more difficult to measure. Marketing engineering focuses on improving the connections between systems. When information moves reliably between platforms, businesses can reduce repetitive work and make decisions using more complete data. AI Search Is Changing How Businesses Get Discovered Technical marketing is also becoming more relevant as AI-powered search develops. Traditional search engine optimization focuses on helping websites appear in organic search results. But customers increasingly use AI-powered tools to research products, compare services and find answers. That has brought greater attention to two related concepts. Answer Engine Optimization (AEO) focuses on making information clear, accessible and useful for answer-based discovery. Generative Engine Optimization (GEO) focuses on improving how content can be discovered, understood and potentially referenced by generative AI systems. These approaches overlap with established SEO practices, including technically accessible websites, useful content and clear information architecture. They do not guarantee inclusion in AI-generated answers. For businesses, the practical lesson is that website content and technical structure need to support more than traditional search rankings. Automation Can Eliminate Repetitive Marketing Work Another opportunity is workflow automation. Marketing departments often spend considerable time on tasks that don't require much creative judgment. Downloading reports, updating spreadsheets, transferring customer information, preparing campaign summaries and moving data between applications are common examples. Many of these activities can be automated when systems are properly connected. That doesn't eliminate the need for marketers. It can give them more time to focus on strategy, creative development, customer relationships and improving campaign performance. The objective isn't to automate everything. It's to identify which tasks can be handled more reliably and efficiently through technology. Better Data Can Lead to Better Marketing Decisions One of the biggest challenges in marketing is understanding which activities actually contribute to revenue. A campaign might generate thousands of impressions, hundreds of clicks and dozens of leads without producing profitable customers. Marketing engineers can help businesses connect advertising activity with customer and sales information. That includes improving conversion tracking, integrating data sources and identifying where potential customers drop out of the buying process. The goal is to move beyond reporting what happened on an advertising platform and develop a clearer understanding of what happened across the business. Does Your Business Need a Marketing Engineer? Not every company needs to hire a full-time technical marketing specialist. For smaller businesses, the first step is identifying where disconnected systems, manual processes or unreliable data are creating problems. Consider whether your advertising and sales platforms share information, whether campaign performance can be connected to revenue and whether repetitive reporting tasks could be automated. It is also worth reviewing whether your website is technically accessible, well structured and capable of answering the questions potential customers are asking. Depending on the complexity of the business, these improvements might be handled by an internal employee, an outside specialist or a combination of both. The important decision isn't necessarily who to hire. It's determining which capabilities the business actually needs. The Future of Marketing Is More Connected Creative thinking, compelling messaging and customer relationships remain essential to effective marketing. But those strengths increasingly depend on the technology supporting them. Businesses need systems that communicate, data that can be trusted and processes that allow teams to work efficiently. Marketing engineering represents one approach to bringing those capabilities together. The next competitive advantage may not come from producing more content or launching more campaigns. It may come from building a marketing operation where everything works together.

P&G Rebuilt Its Operations and Saved $600 Million. Here's How.

October 23, 2026
Procter & Gamble didn't simply outsource its support operations. It first rebuilt how they worked, then brought in outside partners. By 2008, its business-services transformation had generated approximately $600 million in cumulative savings. In the late 1990s, Procter & Gamble faced a problem familiar to businesses of almost every size: too many teams performing similar work. Finance, human resources and other support functions were spread across different parts of the company. That meant duplicated activities, inconsistent processes and unnecessary costs. Instead of continuing to expand those departments independently, P&G decided to fundamentally change how its business operated. First, P&G Fixed Its Internal Operations In 1999, P&G began bringing its support functions into a single global organization. Over the following three years, the company consolidated and standardized more than 70 services. It also established shared-service centers to support operations around the world. The goal was to replace fragmented systems with a more consistent and efficient operating structure. Importantly, P&G didn't begin by handing all these functions to outside companies. It first reorganized how the work was performed internally. That foundation would make the next phase possible. Then Came $4.2 Billion in Outsourcing Agreements In 2003, P&G entered into outsourcing partnerships valued at approximately $4.2 billion. Outside specialists took responsibility for selected operations, including IT infrastructure, payroll support, accounts payable and facilities management. Rather than maintaining every capability internally, P&G could rely on partners with specialized expertise, established systems and the scale to manage these activities. But it didn't outsource everything. The company retained control of functions it considered strategically important, including procurement, logistics, IT architecture and technology-driven innovation. This distinction was central to the strategy. P&G wasn't trying to eliminate internal operations. It was deciding which activities made sense to manage itself and which could be handled more effectively by partners. The Benefits Went Beyond Cost Savings One of the clearest examples came during P&G's integration of Gillette. According to P&G's business-services leadership, its established systems and outsourcing partners helped the company mobilize approximately 750 additional people within weeks. The business-services integration was completed in 15 months, a process its leadership believed could otherwise have taken three to four years. That flexibility mattered. P&G could draw on existing capabilities and outside resources without having to build every part of the operation from scratch. By 2008, the company's broader business-services transformation had produced approximately $600 million in cumulative savings. Those savings came from a combination of internal consolidation, standardized processes and selective outsourcing, not outsourcing alone. What Smaller Businesses Can Learn Most businesses aren't managing P&G's scale or negotiating multibillion-dollar agreements. But the underlying decision is surprisingly relevant. As companies grow, they often add employees and departments without reconsidering how work gets done. Over time, the same problems can emerge: duplicated tasks, fragmented responsibilities, rising administrative costs and employees spending too much time on activities outside their core expertise. The first step isn't necessarily outsourcing. It's understanding the operation. Which processes are inefficient? Which functions require direct internal control? Which activities could a specialist handle more effectively? Customer support, bookkeeping, administrative work, creative production and certain technology operations may be candidates for outside support, depending on the business. But outsourcing a poorly defined process can simply transfer the problem to someone else. P&G's experience illustrates a more disciplined approach: improve the system, identify which capabilities are strategically important and use external partners where they offer a genuine advantage. You Don't Have to Build Everything In-House The most important lesson from P&G's transformation isn't that every business should outsource more. It's that growth doesn't require owning and managing every operational function. By combining stronger internal processes with carefully selected partners, businesses can reduce unnecessary complexity and concentrate their resources where they create the most value. Sometimes the smartest way to grow isn't to build another department. It's to rethink how the work gets done. Sources McKinsey & Company, From internal service provider to strategic partner: An interview with the head of Global Business Services at P&G (2008). Procter & Gamble, 2008 Annual Report.