All posts
Ray Iyer
Ray Iyer
Co-founder & CEO, Anglera

A distributor's guide to curve, port, and pressure data

Why missing curve, port, and pressure data on pump product pages drives wrong-part returns, and a concrete checklist distributors can use to fix it.

A distributor's guide to curve, port, and pressure data

A buyer looking for a replacement end-suction centrifugal pump does not want a glamour shot and a horsepower number. They want to know if the thing will bolt up to their existing piping, run at their duty point without cavitating, and survive the pressure their system actually sees. When a product page can't answer those questions, the buyer either calls support, guesses, or orders three options and returns two. Every path costs a distributor money, and the guess is the most expensive one.

Why this category punishes bad data harder than most

Pumps and fluid power parts are dimensionally unforgiving. A centrifugal pump isn't like a work glove where "close enough" ships fine. Suction and discharge nozzle size and location, shaft diameter, and baseplate footprint are all governed by interchangeability rules in standards like ASME B73.1 specifically so that pumps of the same size designation from different manufacturers can drop into the same piping and foundation. That's a gift to buyers, but only if the product page actually states the designation and the nozzle data instead of burying it in a PDF cut sheet nobody opens before checkout.

This is not a niche data-hygiene complaint. Across MRO categories broadly, 51% of organizations report data-quality problems in their maintenance and repair supply chains, and 49% cite inconsistencies in supplier master data specifically. Pumps sit right in the middle of that world: multi-source supply, spec-driven selection, and a buyer who often has one shot to get the replacement right before a process line goes down.

What a Pumps & Fluid Power buyer actually needs on the page

Not a feature list. A decision-support table. For an end-suction centrifugal pump, the questions buyers ask, in order, look like this:

Buyer questionData the page needs
Will it bolt into my existing pipe and baseplate?ANSI/ISO dimensional designation, suction/discharge nozzle size and location, baseplate footprint
Will it perform at my duty point?Full pump curve: head vs. flow, efficiency, BEP, input power
Will it cavitate in my system?NPSHR curve at the relevant flow range
Will it hold up under my system pressure?Maximum working pressure, casing pressure rating, seal chamber pressure limit
What's actually wetted?Casing/impeller materials, seal type and elastomer compatibility
Will it fit my motor and drive?Shaft diameter, coupling type, motor frame size, rated speed

The Hydraulic Institute's guidance on pump curves is explicit that a curve isn't decoration: head-vs-flow, efficiency, input power, and NPSHR together are what let an engineer confirm a pump matches system requirements at or near its best efficiency point, rather than running oversized, undersized, or in a cavitating condition that shortens seal and bearing life. A spec sheet that has a curve image but no NPSHR line, or a curve with no labeled BEP, is functionally incomplete even though it "has a curve."

Before and after: a raw feed vs. an enriched listing

Here's what a typical raw supplier feed gives a distributor for an end-suction centrifugal pump, versus what the page needs to actually answer the buyer's questions.

Raw feed description: "Cast iron end suction centrifugal pump, 3 HP, close-coupled, for water transfer applications."

Enriched attribute table:

AttributeValue
Dimensional designationANSI B73.1, 2x1.5-8
Suction / discharge nozzle2 in suction / 1.5 in discharge, flanged (125 lb)
Rated flow @ head100 gpm @ 100 ft TDH
BEP flow110 gpm
NPSHR @ rated flow8 ft
Max working pressure175 psi casing
Wetted materialsCast iron casing, bronze impeller
Seal typeMechanical seal, Buna-N elastomer
Motor frame / speedNEMA 145JM, 3,500 rpm

Same pump, but now a buyer or a purchasing system can actually confirm fit before ordering, not after unboxing.

The "ask an answer engine" test

Buyers increasingly qualify parts by asking an AI answer engine something like: "What's the NPSHR for a 2x1.5-8 ANSI end suction pump at 100 gpm, and will it cavitate on a suction lift application?" If the underlying product data doesn't have a machine-readable NPSHR value tied to a flow rate, the answer engine has nothing to retrieve, and the distributor's listing gets skipped in favor of a competitor whose data is structured. Readable-by-humans and readable-by-machines are the same requirement now, not two different projects.

A short checklist for fixing the gap

  • Confirm every pump listing carries a dimensional designation (ANSI B73.1, ISO 2858, or equivalent), not just a model number.
  • Require nozzle size, location, and flange rating as structured fields, not text buried in a PDF.
  • Attach the full curve set: head/flow, efficiency, BEP, NPSHR, and input power, as both an image and structured data points.
  • Capture max working pressure and seal chamber rating separately from the general "specs" blob.
  • Flag listings where wetted materials or seal elastomer are missing. That gap is what drives compatibility-related returns and support tickets, not the dimensional stuff alone.
  • Re-check gap-fill coverage after each new supplier feed lands, since one bad import can silently regress a clean catalog.

Wrong-part returns in a category like this are rarely about the buyer being careless. They're about a product page that couldn't answer the three or four questions that actually mattered. Anglera plugs into whatever PIM a distributor already runs, or works from a flat file if there isn't one, and continuously scores, gap-fills, and enriches attributes like nozzle size, curve data, and pressure ratings against supplier source documents so the values on the page are the ones an engineer would actually check against a real spec. It's live in weeks, not a multi-year integration, because the fix here is closing specific gaps, not replacing the system of record.

Ray Iyer

About the author

Ray IyerCo-founder & CEO, Anglera

Ray is the co-founder and CEO of Anglera, building the product-data infrastructure for agentic commerce — turning messy catalogs into structured, AI-readable data that buyers and answer engines can find. Previously product at Uber; Stanford CS.

See it on your own SKUs.

A 30-minute walkthrough on your categories and your supplier data.

Book a demo