B2B is driving growth for Lowe’s while consumer remodeling stalls
The hosts opened with breaking news about Lowe’s earnings. The company projected sales growth of 7% to 9% for fiscal year 2025, but that growth is largely driven by B2B acquisitions, specifically Foundation Building Materials and Artisan Design Group. Comparable sales were forecast to be flat to up only 2%, with homeowners reportedly reluctant to remodel.
Andy noted that this pattern is becoming familiar. Consumer sales are flat while B2B drives growth. At the same time, profits are down due to tariff impacts, and companies are using AI as both a real productivity tool and an excuse for white-collar layoffs.
There’s a revolution taking place on the back end. That’s what this research shows about the supply chain.
Andy Hoar, Master B2B
The cost savings side: where AI delivers measurable results
Brian presented research on AI cost savings. According to sources cited in the episode, 49% of companies using AI report savings. Sector leaders see the highest cost reductions in supply chain (46%), particularly in back-office and compliance automation. Wharton research reportedly found that generative AI delivers 25% labor cost savings on specific tasks, though the enterprise-wide impact is often closer to 5% due to scaling challenges.
Andy attributed the gap between task-level and enterprise-wide impact to companies not changing how they work. They plug AI into existing processes rather than rethinking processes around what AI does well. This mirrors the early days of eCommerce, when companies treated digital as a separate initiative rather than a reason to transform operations.
The revenue side: promising but harder to prove
Brian cited additional research on AI revenue generation. McKinsey reportedly estimated that generative AI and advanced analytics could unlock up to $4.4 trillion in economic value. Boston Consulting Group reportedly found that AI-ready companies are achieving five times the revenue increases compared to laggards, and that 82% of top-performing companies target growth and innovation with AI compared to 50% of average companies.
Andy noted that revenue gains are harder to prove than cost savings. Cost savings can be demonstrated with A/B tests and direct comparison. Revenue gains invite attribution debates, with sales, customer service, and digital teams all claiming credit for the same lift. This is why companies often buy AI to make money but renew because of the cost savings.
Guest Trevor Pope on AI in experimentation
Trevor Pope, Senior Director of Solution Architecture at Optimizely, joined to discuss how AI is changing experimentation for manufacturers and distributors. He explained that AI is used at multiple stages: generating experiment ideas, suggesting variations to test, analyzing results, and even writing the code needed to implement page changes.
One key shift is that non-developers can now make template and page modifications using AI-generated code. This eliminates the bottleneck of waiting for developer resources or hiring external consultants. Customers report 25% time savings, and Trevor noted that one person can now run entire experimentation programs that previously required larger teams.
AI also helps with SEO and GEO optimization. Teams can analyze their sites for metadata issues, open graph tags, and other factors without requiring external experts or waiting for periodic audits. The analysis happens continuously rather than at six-month or annual intervals.
A distributor’s $250,000 win from shipping optimization
Trevor shared a case study of a mid-size distributor that increased sales by $250,000 in 90 days through AI-powered experimentation. The key insight came from understanding what their customers cared about.
The distributor discovered that their customers were not evaluated on product cost but on shipping cost. Internal reporting at customer organizations analyzed shipping expenses, not product prices. By making shipping costs and delivery timing more prominent on product pages, the distributor increased conversions. Customers were willing to pay higher product prices if shipping was competitive and delivery dates were clear.
They figured out very quickly that shipping was a major differentiator that the reporting side at their customer analyzed.
Trevor Pope, Optimizely
Community poll: making money leads, but saving money sustains
The hosts shared results from a community poll asking about the highest priority for AI. Making money led with 41%, followed by saving money at 30% and improving customer experience at 27%.
Trevor noted that making money is typically the reason companies buy AI tools. Andy added a refinement: making money is why companies start the process, but saving money is often why they renew. The revenue gains are real but difficult to attribute, while cost savings are straightforward to measure. Teams that can demonstrate clear efficiency gains are more likely to maintain budget and support.
Setting up measurement frameworks before starting
Andy closed with a reminder about measurement. Whatever gets measured gets managed, as Peter Drucker famously said. Companies often start AI projects without considering how they will evaluate success. They open the doors and worry about outcomes later.
The better approach is to establish a measurement framework in advance. Define what success looks like, set baselines, and decide which metrics matter before launching. The hosts noted that this will be a focus of the upcoming Master B2B Summit, where practitioners will share their approaches to measuring AI impact.