✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount

SleekRank for ETF fee comparisons

Keep ETFs and pairs as rows, and SleekRank generates /etfs/{ticker}/ and /etfs/{a}-vs-{b}/ pages from your existing WordPress template, with expense ratio, AUM, tracking error, index, and top holdings pulled from one source.

€50 off for the first 100 lifetime licenses!

SleekRank for ETF fee comparisons

ETF expense ratios change without much fanfare

ETF issuers cut expense ratios, change benchmark indices, and replicate competing products on a calendar that does not align with publishing schedules. A VOO review from last quarter might miss a Schwab fee cut on SCHX, a State Street rebrand on a sector fund, or a structural change to dividend timing. Per-ETF reviews and head-to-heads compound these inconsistencies across dozens of pages running for low-cost index keywords.

SleekRank reads one source, a sheet of ETFs with ticker, name, issuer, index_tracked, expense_ratio_bps, aum_billions, average_volume, tracking_error_bps, dividend_yield, holdings_count, top_ten_concentration, and a verdict column. It drives per-ETF pages at /etfs/{ticker}/ and head-to-heads at /etfs/{a}-vs-{b}/ from the same row data. The base page is a normal WordPress page, and the row values fill the expense block, AUM stat, and verdict slot.

Expense ratio in basis points is the column most prone to silent drift, since issuers cut fees mid-cycle to defend AUM. Stored as one column with effective_date, tag mapping renders the live expense ratio on every page that references the fund, with a small note from a second column when a recent cut applies.

Workflow

From ETF sheet to per-ticker and head-to-head pages

1

Build the ETF sheet

One row per ETF with ticker, name, issuer, index_tracked, expense_ratio_bps, aum_billions, average_volume, tracking_error_bps, dividend_yield, holdings_count, top_ten_concentration, and a verdict paragraph.
2

Wire the ETF template

Place an h1, expense block, AUM stat, index pill, tracking error tag, yield stat, and verdict block on a WordPress page. Tag, selector, list, and meta mappings inject row values per ETF.
3

Add a pairs page group

A second page group from a pairs sheet generates /etfs/{a}-vs-{b}/ pages, joining both ETF rows side by side with a head-to-head verdict and winner column specific to the matchup.
4

Refresh on issuer news

When an issuer cuts an expense ratio or restructures a fund, edit the relevant columns and flush the cache. Per-ETF and pair pages reflect the new facts before the next crawl picks them up.

Data in, pages out

ETF matrix in, fund pages out

Each row is one ETF with expense ratio, AUM, tracking error, and index tracked.
Data source: Google Sheets / CSV
slug ticker expense_ratio_bps aum_billions index_tracked
voo VOO 3 $489 S&P 500
vti VTI 3 $455 CRSP US Total Market
spy SPY 9 $565 S&P 500
ivv IVV 3 $520 S&P 500
schx SCHX 3 $45 Dow Jones US Large-Cap Total Stock Market
URL pattern: /etfs/{slug}/
Generated pages
  • /etfs/voo/
  • /etfs/vti/
  • /etfs/spy/
  • /etfs/voo-vs-vti/
  • /etfs/spy-vs-voo/

Comparison

Hand-edited ETF reviews versus one synced matrix

Manual ETF reviews

  • Expense ratios drift after issuer fee cuts
  • AUM and average volume fall behind monthly fund flows
  • Tracking error figures rarely refresh on legacy pages
  • Adding a new ticker means writing a stack of pages
  • Top-holdings concentration shifts every reconstitution
  • Index methodology changes rarely propagate everywhere

SleekRank

  • One row drives the per-ETF page and every pair
  • Expense and AUM columns flow through to all pages
  • Tracking error and dividend yield columns stay aligned
  • Top-holdings and concentration columns sync across the catalog
  • Cache flush updates every page after a sheet edit
  • Sitemap reflects current tickers automatically

Features

What SleekRank gives you for ETF fee comparisons

Expense ratio in one place

Expense ratio in basis points injects into the fee block on every page that references the ETF, so a fee cut from any issuer is one row edit instead of a sweep across solo, pair, and category roll-up pages.

Pair page support

A pairs page group joins two ETF rows into a /a-vs-b/ template so head-to-heads stay in step with per-ETF pages, with side-by-side specs and a matchup-specific verdict from the pairs sheet.

Tracking error and yield

Tracking error in basis points and trailing twelve-month yield render from dedicated columns, keeping technical accuracy claims honest as funds reconstitute and dividends roll forward.

Use cases

Who builds ETF fee comparisons with SleekRank

ETF affiliate sites

Sites earning on broker referrals through ETF guides cover the long tail of ticker and pair queries from one sheet, with expense ratios aligned with each fund's prospectus.

Investing publications

Editors maintain a master ETF matrix, and per-ETF plus head-to-head pages follow without separate edits, so a fee cut propagates across the review set in one cache cycle.

Index investor communities

Boglehead-style communities publish structured ETF comparisons used in portfolio recommendation threads, with one sheet driving public reference pages that beat the lifespan of any forum post.

The bigger picture

Why ETF comparisons need a data layer

ETF readers care about expense ratio, AUM scale, liquidity, and benchmark fidelity, since those drive long-run net return on a passive position. Manual review pages drift on exactly these axes because issuers cut fees mid-cycle and AUM moves with monthly fund flows that editorial teams cannot manually patch across a thirty-page catalog. A page that quotes nine basis points on a fund that has been three for a year is wrong the moment a reader cross-checks the issuer page, and the credibility loss closes the conversion the keyword research promised.

SleekRank pins these facts to a single row, so an expense cut or AUM update is one column edit that propagates everywhere on the next cache cycle, keeping the fund catalog defensible long enough for readers to make decisions based on numbers that match the prospectus.

Questions

Common questions about SleekRank for ETF fee comparisons

Not directly. SleekRank renders from your data source. If your sheet pulls from a vendor NAV feed or you maintain it editorially, those values flow through on the cache cycle. The import layer is upstream of SleekRank, which is responsible for rendering whatever is current in the source consistently across solo and pair pages.

 

Both page groups read from the same ETFs sheet. The pairs group joins two rows at render time using a ticker pair from a pairs sheet. A change to an ETF row updates every page that references the fund, including per-ETF, pair, and any category roll-ups, after the cache window expires.

 

Define another page group with a different URL pattern, source from the same sheet, and filter on index_tracked. A /etfs/sp500/ landing page becomes its own SEO target, with intro copy on the base page and the matching subset rendered from the source.

 

Yes. Store sector exposure as a JSON column or a primary_sector field on each row. A /etfs/technology/ landing page filters on that column, list mapping renders the matching tickers, and the same expense and tracking-error columns flow through to each sector page.

 

Yes. The pairs sheet has its own verdict column. The per-ETF verdicts handle solo pages, and the pair verdict drives matchup-specific recommendations. If a pair row's verdict is empty, the template can fall back to a templated summary built from the two solo verdicts. You control the wording per matchup when nuance is needed.

 

Set a closed_date column on the row. Selector mapping renders a closure banner on the affected per-ETF page, and pair pages can either keep the comparison for historical search traffic or drop the fund from the ranking via a template conditional on closed_date.

 

Yes. Map an image URL column to og:image with the meta type, so each per-ETF page renders its own social card. Pairing with SleekPixel lets the OG image render on the fly from the row data, overlaying ticker, expense ratio, and AUM on a styled background.

 

Add prospectus_url and disclosures columns on each row. Selector mapping renders the prospectus link and any required disclosure inline on each per-ETF page. Sitewide regulatory language sits in a global config and renders via a shared footer component so it stays consistent across the catalog.

 

Pricing

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