Skip to content
MarketScale
‹ Back to IndustriesSoftware & Technology

B2B eCommerce's real barrier isn't technology, it's the complexity that digital moves, not removes

Manufacturers and distributors are finding that digitizing their operations often shifts complexity rather than removing it entirely. Key challenges include maintaining customer loyalty, ensuring AI readiness, and effectively managing data. Companies must focus on strategic implementation to overcome these obstacles.

This story was produced through MarketScale. See how Software & Technology teams put it to work with Executive Thought Leadership.

By MarketScale Newsroom · B2b EcommerceDigital TransformationManufacturingDistribution
Share
Learn this in 60 seconds

Key facts, context, and what it means, in one minute.

:60
0:001:00
B2B eCommerce's real barrier isn't technology, it's the complexity that digital moves, not removes

Key takeaways

01

Digital transformation shifts complexity rather than eliminating it.

02

AI readiness and effective data management are critical for success in digitization.

Get featured

Want to get featured in MarketScale Software & Technology?

Create a free MarketScale workspace and get your company's expertise featured across our Software & Technology coverage. No credit card, no demo required.

Request an invite

Going digital does not make B2B operations simpler. It makes them differently complicated. That finding, surfacing repeatedly across practitioner conversations tracked by the B2B eCommerce Association in mid-2026, is reshaping how forward-looking manufacturers and distributors plan their commerce investments, and when they decide to automate.

The commercial pressure to digitize is real. According to Forbes Advisor's updated e-commerce statistics, global e-commerce continues to expand at a pace that makes standing still an increasingly costly option for B2B sellers. But the companies moving fastest are not necessarily the ones winning. The ones winning are the ones that understood what they were getting into before they picked a platform.

Digitization moves the problem, it doesn't solve it

The founders of Virto Commerce, in a conversation published by the B2B eCommerce Association in July 2026, framed the dynamic precisely: a new commerce platform doesn't remove complexity from a manufacturer or distributor's operation. It relocates it. What once lived in phone calls, spreadsheets, and rep relationships migrates to product data pipelines, integration layers, and internal governance questions that most teams haven't answered yet.

That relocation catches organizations off guard. A distributor that digitizes its catalog without first cleaning and structuring its product data ships the same data problems to a new address, now customer-facing. A manufacturer that builds a self-service portal without aligning sales and marketing incentives often finds its field team actively working around the channel it just spent months building.

The companies winning B2B eCommerce are not the ones that picked the best platform, they're the ones that fixed the right things before they picked any platform at all.

Cameron Ashley Building Products offers a concrete counter-model. As detailed by the B2B eCommerce Association in July 2026, the company's digital platform was built primarily from customer conversations rather than competitive benchmarking. Courtney Seim, who led the effort, described a process of listening directly to contractors and dealers about what information they needed, in what format, and at what point in the buying process, then building backward from those answers. The result was a platform shaped around actual purchasing workflows, not an assumed template.

AI readiness requires a foundation, not just a budget line

AI has entered almost every B2B commerce conversation in 2026, but practitioner guidance from the B2B eCommerce Association is clear: most manufacturers and distributors are not ready to automate, even when they think they are. In a podcast published July 30, 2026, Graham Lubie introduced the concept of an 'AI enablement pyramid', a structured way of evaluating organizational readiness before committing to automation investments.

The pyramid's logic is straightforward. The base layers, clean data, documented processes, and clear ownership of decisions, must be solid before any AI layer is added on top. Operators who skip those foundations and jump to tooling tend to automate their existing problems at greater speed and scale, which is worse than not automating at all. For a VP of Operations evaluating an AI-powered demand forecasting or dynamic pricing tool, the practical question isn't which vendor to choose, it's whether the product data and order history feeding that tool are accurate enough to produce a reliable output.

The B2B eCommerce Association's coverage also flagged regional variation in how these readiness questions play out. A July 30, 2026 piece on Latin American B2B eCommerce noted that momentum in markets like Brazil and Mexico is building, but the pace differs meaningfully from North American and European markets, with community and peer networks playing an outsized role in accelerating adoption where formal digital infrastructure is still developing.

Loyalty is an operational problem, not a marketing one

A recurring thread in B2B eCommerce practitioner conversations this year is the gap between how loyalty is designed and how B2B buyers actually experience it. In a podcast published July 16, 2026 by the B2B eCommerce Association, Dechay Watts argued that most manufacturer and distributor loyalty programs are built around the wrong currency. Points and rebate tiers matter far less to a B2B buyer than whether the inventory data in the portal is accurate, whether the order confirmation matches what actually ships, and whether a problem gets resolved quickly.

Operational trust, in this framing, is the loyalty program. A buyer who can rely on a distributor's self-service channel to show real stock levels, confirm pricing without calling a rep, and track a shipment in real time will return, not because of a rewards balance, but because the channel saves them time and reduces their own operational risk. That reframe has direct implications for how commerce teams should prioritize their roadmaps: reliability features and data accuracy before points engines.

In B2B, a loyalty program that runs on points loses to a portal that simply tells the truth about stock.

Sales and marketing alignment is still the hardest internal problem

Adrienne Hartman, who brings 26 years of experience in technical and commercial roles, addressed what the B2B eCommerce Association described in a July 28, 2026 podcast as one of the most persistent blockers to eCommerce growth: sales and marketing teams that operate on separate measures of success. When a distributor's marketing team is optimizing for digital channel revenue and its sales team is compensated purely on rep-attributed orders, the eCommerce platform often becomes a source of internal friction rather than growth.

Hartman's argument, as reported by the B2B eCommerce Association, centers on building shared metrics and feedback loops between the two functions, so that digital behavior data informs rep outreach and rep intelligence shapes digital merchandising. Organizations that achieve that alignment, she contended, see eCommerce act as an accelerant for the entire revenue operation, not a competing channel. Those that don't tend to find their digital investments stalling at a fraction of the addressable opportunity.

Across all these practitioner perspectives, the pattern holds: the technology is rarely the constraint. Platform maturity in B2B commerce has advanced significantly, as Forbes Advisor's e-commerce statistics confirm in documenting the scale of global digital commerce growth. The constraint is almost always the organizational and data work that has to precede the platform, and that most teams underestimate until they're already mid-deployment.

Sources

Featured companies

Your experts belong here

Every story in MarketScale Software & Technology starts with a company putting its solutions engineers, product teams, and customer engineers on the record. Buyers are already reading this topic. The only question is whose experts they find.

Buyers ask AI engines who to consider, and published expert answers are what those engines cite.

Get your team featuredSee how it works15 minutes, straight to a calendar.

About the author

MarketScale Newsroom
MarketScale NewsroomEditorial Team, MarketScale

The MarketScale Newsroom reports on the companies, technologies, and trends shaping 16 B2B industries. It turns primary sources and expert commentary into clear, useful coverage for the people doing the work.

Follow Software & Technology Insights

Get new expert content in your inbox.

Software & Technology: are you visible to AI?

Before they reach out, Software & Technology buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one Software & Technology expert. Your company is full of them.

This article was produced through MarketScale. The same platform turns your solutions engineers, product teams, and customer engineers into the articles, video, and social content Software & Technology buyers are searching for. Create a free workspace and see it with your own people. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Software & Technology Insights

Dell’s $95B AI backlog is turning AI rollouts into a delivery-date problem

Dell has a reported $95B AI backlog. AI infrastructure lead times are still a gating factor in 2026. CIO Dive and Bain & Co. expect higher IT costs, while pricing shifts and on-prem moves are changing procurement playbooks.

  • 01A vendor’s backlog number is becoming a planning input, it indicates when AI timelines are gated by physical delivery, not approvals.
  • 02Outcome-based AI pricing sounds like savings, but it shifts risk into defining outcomes, metering how they are measured, and vendor governance.
  • 03The return to private cloud and on-prem for some AI workloads suggests facilities power, rack space, and supply contracts belong in AI roadmaps early.

Sep 5, 2026

AI is now a DAM governance requirement, not a demo feature

CMSWire’s 2026 DAM coverage shows AI fit and governance now drive enterprise DAM selection. Gartner’s DAM reviews point to cross-functional adoption and third-party access needs. Plan for metadata strategy, rights workflows, and integration requirements during refreshes happening now.

  • 01If the DAM roadmap does not spell out how governance, metadata, and rights management will support AI-driven use cases, teams can get stuck in approval and control issues instead of moving forward with storage and delivery.
  • 02Bynder shows up as a “Customer Favorite” in Forrester’s Q1 2026 DAM Wave cited by CMSWire and also appears repeatedly in Gartner peer-rating views, a rare cross-benchmark signal procurement teams can use.
  • 03For organizations with legacy archives, CMSWire’s 20%+ 1990s hard-drive failure-rate reference reframes digitization as a time-bound risk, not a “nice-to-have” project.

Sep 5, 2026

OpenAI's GPT-6 Astra pitch is to skip integrations and run the software UI itself

OpenAI's GPT-6 Astra pitch is to skip integrations and run the software UI itself

OpenAI shipped GPT-6 Astra on Sept. 3 with a "computer use" capability that lets the model operate existing software UIs directly instead of requiring custom API integrations. The staged rollout through Daybreak, ChatGPT tiers, and AWS shifts the automation bottleneck from building connectors to governing UI-driven sessions, with speed measured in minutes per task as the cost input.

  • 01Astra operates software via pixels, keyboard, and mouse interactions to bypass API integration work on the long tail of internal tools without clean API access
  • 02OpenAI reported Astra at 40 minutes per task (47% faster than GPT-5.6 Sol at 75 minutes), making task time the practical proxy for compute cost modeling and throughput evaluation
  • 03Enterprises must define governance before broad rollout: eligible workflows for UI automation, audit logging systems, identity and secrets handling, and fallback procedures when UIs change or sessions break

Sep 3, 2026

Explore More Software & Technology Insights

Read more expert perspectives from across Software & Technology.

Browse Software & Technology Hub

About the Expert

MarketScale Newsroom
MarketScale Newsroom

Editorial Team

MarketScale

The MarketScale Newsroom reports on the companies, technologies, and trends shaping 16 B2B industries. It turns primary sources and expert commentary into clear, useful coverage for the people doing the work.

For B2B teams

Your experts could be publishing here

Stories like this one run on content MarketScale captures from real practitioners. See how your team's expertise becomes coverage in Software & Technology and beyond.

Book a 15-minute demo

Or call us. No forms required. We pick up. 214-945-2512