Join us for an insightful Master B2B Fireside Chat on navigating the complex world of B2B e-commerce decision-making in 2026.
Host Brian Beck leads a discussion with industry veterans Brian Gillespie (VP of Product at HCL Software), Adrienne Hartman (EVP of Marketing at JJ Keller), and Nathan Schatz (Head of IT Product Management at SHI).
In this fireside chat, we explore:
– Balancing backend system complexity with customer experience
– When to fail fast vs. when to take time with major decisions
– The impact of AI on marketing and e-commerce strategy
– Meeting the expectations of Gen Z buyers while serving traditional customers
– The shift from monolithic to composable commerce architectures
– Why data doesn’t always tell the whole story
– Getting organizational buy-in without endless business cases
Strategy & Prioritization
What are the most important decisions B2B e-commerce leaders face today?
B2B e-commerce leaders are constantly balancing two competing priorities: modernizing backend systems (data infrastructure, ERP integrations, EDI, inventory) and improving the front-end buyer experience. Making progress on one without the other limits results — for example, better inventory data is only valuable if it’s surfaced in the customer-facing experience.
Additional decision pressure comes from managing multiple channels simultaneously — a branded website, Amazon storefronts, e-procurement platforms, and traditional EDI — while evaluating where to invest in AI tools that are rapidly reshaping both marketing and operations.
How should B2B companies decide how fast to move on new initiatives?
Speed should match the risk profile of the decision. Tactical changes — A/B tests, content updates, new feature flags — should move fast. Failing quickly on low-stakes experiments is healthy and generates learning. Larger platform or infrastructure decisions (like selecting a customer data platform) warrant deeper analysis and stakeholder alignment.
“Some of the decisions that have to be fast are the things that have less of a potential catastrophic impact or less effort and work to put in.” — Adrienne Artman, SVP Marketing, JJ Keller
The key is not speed for its own sake, but speed relative to the window of market opportunity and the cost of reversing course if the decision is wrong.
What framework should new B2B e-commerce leaders use for setting priorities?
Experienced practitioners recommend three foundational steps:
- Define your North Star — the single primary metric your team is evaluated on (revenue, customer acquisition, digital adoption rate).
- Ensure you have access to the data needed to measure progress toward that goal, and that it can be pulled quickly.
- Build or secure a dedicated technology team within the e-commerce function to reduce dependency on shared IT resources.
Every subsequent decision should be weighed against whether it moves you closer to that primary objective.
AI & Technology
How is AI changing decision-making in B2B e-commerce?
AI is impacting B2B e-commerce decision-making in two distinct ways.
On the internal side, generative AI tools allow teams to prototype faster — creating mockups, demos, and data models that used to take weeks in a fraction of the time, which accelerates buy-in and organizational alignment.
On the external side, AI is changing how buyers discover products and vendors. Traditional SEO is being replaced by answer engine and generative engine optimization (AEO/GEO), meaning B2B brands need to rethink how they establish relevance and visibility with buyers who are now querying AI systems rather than search engines.
What is composable commerce and why does it matter for B2B decision-making?
Composable commerce is an architectural approach where the front-end experience layer is decoupled from backend systems (headless), allowing teams to make changes to one without redeploying everything. In a traditional monolithic platform, even small front-end updates required full application releases — slowing decisions and increasing risk.
With a composable architecture, front-end changes can be pushed nightly, A/B tests run continuously, and new features launched without disrupting backend operations. This directly reduces the organizational friction around making and executing decisions quickly.
Can B2B companies trust data to make e-commerce decisions?
Data is essential but not infallible. One panelist shared a real-world example where data indicated a certain site feature was unnecessary — it was intentionally left off a new platform launch. The result was a measurable negative impact on revenue because the feature had a strong psychological and emotional role in the buyer’s journey that the data failed to capture.
“The numbers will say anything you want to hear if you torture them enough.” — Adrienne Artman, SVP Marketing, JJ Keller
The practical guidance: use data to inform decisions, but pair it with experienced gut instinct — especially for changes that affect buyer behavior and emotion. Also prioritize reducing your “time to data” so reports can be pulled quickly when a fast decision is needed.
Organizational Alignment
How do you get organizational buy-in for large B2B e-commerce investments?
The most effective approach is leading with vision, not consensus. Rather than building a business case and seeking broad agreement, identify one key executive champion, then build a compelling story — ideally a visual prototype or mockup — that shows what success looks like.
Amazon’s internal practice of writing the press release before starting a project is a useful model: define the end outcome first, make it vivid, and use that vision to get people to follow rather than negotiate.
“Don’t get consensus. Get people to follow. Come in with the idea. Come in with the concept. Prove it through data and workshops — that moves a lot faster.” — Brian Gillespie, VP Product, HCL Software
How should B2B companies balance serving longtime customers vs. new digital-native buyers?
B2B companies serve two increasingly divergent customer cohorts: longtime buyers accustomed to phone orders, quotes, and EDI, and a rising generation of Gen Z workers who expect seamless, fully digital, self-service experiences and have no tolerance for manual processes.
The recommended approach is channel agnosticism — making every channel (phone, web, EDI, e-procurement, Amazon) work well, rather than forcing customers toward one preferred experience. Use persona analysis and behavioral data to understand who is coming in and what they need, and weight investment accordingly without abandoning any segment entirely.
Do B2B companies still need to justify e-commerce investment with formal business cases?
The bar has shifted significantly. Whereas a decade ago, e-commerce leaders had to build exhaustive ROI models just to get a project approved, the case for digital investment is now broadly understood at the executive level. Detailed revenue-uplift projections are still useful for sizing and prioritizing specific initiatives, but the fundamental argument for having a strong digital commerce capability no longer needs to be made from scratch.
The conversation has moved from “should we invest in e-commerce?” to “how do we allocate and sequence that investment wisely?”
