Problems in B2B software
Problems that owners and product teams of B2B software recognise, with why they happen, how they show up and the options. The last group covers interface patterns that look reasonable in a review and cause problems in daily use.
32 Entries
01
Product demos lose deals
B2B buyers usually decide from a demo and a trial, before any daily user has worked in the product, so the interface is judged in the time a demo takes.
02
Onboarding needs a consultant
New customers cannot start using the product without a consultant or a member of the vendor's team present, and training is repeated because users forget it.
03
Setup complexity blocks adoption
Setup often has no state between not configured and live, so users who want the product stop before they see it work.
04
Customers buy the product and adoption stays low
A buyer's decision does not make users adopt the product. Low adoption usually becomes visible at renewal, when the customer asks what they pay for.
05
Support requests concentrate on the same screens
Each ticket costs the vendor time and the customer a stopped task. When tickets cluster on a few screens, the cause is usually the screen.
06
Enterprise buyers ask for audit and roles the product cannot show
A product that sold well to smaller customers meets larger or regulated buyers who ask who changed what, who may approve what, and how access is controlled.
07
An interface built for technical users fails business users
Technical users think in the system's internal structure, business users think in terms of their work, and training rarely closes the gap.
08
When should B2B software be redesigned?
Age alone is a weak reason to redesign. A dated look over working flows can be refreshed without a full redesign.
09
Redesign or rebuild?
A redesign changes the interface and keeps the data model and backend.
10
Can you redesign one module first?
Yes.
11
How do you measure a B2B software redesign?
Measure a redesign by the tasks it was meant to improve: task time, errors, support load, onboarding time and work done outside the product.
12
Legacy migration stalls on inconsistent data
Over the years old fields were used inconsistently, with several values in one field and free text where structure was expected.
13
An AI-built prototype cannot be changed safely
Typical signs are a single large file, no component structure and visible generation artefacts, so each targeted change breaks something else.
14
A module was built off-spec and needs rework
A module shipped and behaves differently from its specification in totals, nesting and line-item behaviour.
15
The design system has no brand in it
A standard component library makes a product consistent and accessible, and buyers struggle to tell it apart from competitors on the same library.
16
How do interface problems cause bad production data?
People keep working when capture is slow, and the record falls behind. Reports and dashboards cannot repair data that was captured wrongly.
17
Traceability falls short of a regulated industry’s requirements
Traceability that suits general manufacturing falls short for regulated buyers: unlinked nonconformances, incomplete audit trails, aggregate records.
18
The same action repeats across a dozen similar records
The user decided once for the whole group of records, and the interface asks for twelve separate decisions.
19
The report is too long to be read
When every item in a report is relevant, removing items does little. The report needs a structure that supports a decision at a higher level.
20
Vertical space runs out before the content does
The problem is most visible on laptops in data-heavy tools, where fixed page elements leave little room for the rows users need.
21
A manual process has stopped scaling
Work done by hand at launch, such as checking each report, is still done carefully and now arrives late.
22
An integration returns incomplete data
Bank feeds and external systems return limited history, missing fields or ambiguous matches, and screens designed for complete data break on them.
23
The system slows down on historical data
Ledgers, transactions and logs reach hundreds of thousands of rows in real use, and screens tested on a demo dataset slow down.
24
Users default to chat and never find the structured mode
Structured workflows often give better output than open chat, so when users stay in chat the quality they receive goes down.
25
Happy-path interface
Short picks, partial receipts and rework have no path in the system, so users handle them outside it.
26
Correction harder than entry
An entry takes one step, and fixing it needs a supervisor, a separate screen or a support ticket.
27
Status stored and not shown
Hold and block states live on detail pages, so blocked work gets started anyway and supervisors answer status questions by phone.
28
Permission-shaped screens
One layout serves every role with fields hidden by permission.
29
Flat list for a graph
Lot genealogy, bills of materials and approval chains are graphs. Shown as rows, they turn simple trace questions into long investigations.
30
Silent defaults
The system applies defaults without showing them.
31
The parallel spreadsheet
Users keep a spreadsheet next to the system to plan, check or report.
32
Designed on demo data
Screens were designed and tested with a small, clean dataset.