Tutorial · 7 min read

Export SoftwareSuggest Reviews to CSV & Excel

Pull overall scores, the four ease-of-use, value-for-money, support and features sub-ratings, firmographics, and full review text from any SoftwareSuggest listing into a clean spreadsheet — the fastest way to learn how buyers in India and Southeast Asia actually judge your software.

SoftwareSuggest is the dominant B2B software review platform across India and Southeast Asia, and its signal is fundamentally different from the US-centric data you find on G2 or Capterra. If you sell into APAC or emerging markets it is invaluable: the reviews here expose region-specific feature gaps, localization needs, and price sensitivity that simply never surface on Western directories. The SoftwareSuggest reviews extractor turns that scattered, paginated feedback into a structured dataset you can sort, filter, and pivot in minutes.

Reading reviews one page at a time gives you anecdotes; exporting them gives you evidence. This guide walks through exactly which fields you get, the CSV schema, a three-step export workflow, and — most importantly — the SoftwareSuggest-specific quirks that make this data uniquely useful for regional research. By the end you'll have a repeatable process for converting any softwaresuggest.com/[product]/reviews page into analysis-ready rows.

What gets exported from SoftwareSuggest

SoftwareSuggest is unusually rich for a review site: alongside the headline star rating it captures four distinct sub-ratings plus reviewer firmographics. Every export includes these columns:

overall_rating — the headline 1–5 star score
ease_of_use — usability sub-rating
value_for_money — price-sensitivity sub-rating (the key APAC signal)
customer_support — support-quality sub-rating
features_rating — feature-depth sub-rating
review_text — the full free-text review
reviewer_name — reviewer display name
industry — reviewer's industry vertical
company_size — firmographic headcount band
pros — structured positives
cons — structured negatives
review_date — date the review was posted

The combination of five rating dimensions plus industry and company_size is what makes SoftwareSuggest exports pivotable in ways a plain star rating never could be.

Sample CSV header

Your export opens cleanly in Excel, Google Sheets, or any BI tool. The first row looks like this:

overall_rating,ease_of_use,value_for_money,customer_support,features_rating,review_text,reviewer_name,industry,company_size,pros,cons,review_date

Each subsequent row is one review. Free-text columns are quoted, so commas inside review_text, pros, and cons never break your columns.

Export SoftwareSuggest reviews in 3 steps

1. Install the extension

Open the Chrome Web Store listing at chromewebstore.google.com/detail/software-suggest-reviews and click Add to Chrome. The extension is lightweight, needs no signup, and pins to your toolbar so it's ready on any SoftwareSuggest page.

2. Navigate to a reviews page

Go to the product you want to analyze. The reviews live at a URL shaped like softwaresuggest.com/[product]/reviews. You can stay on the first page — the extractor handles pagination for you, walking every page of reviews automatically rather than making you click through dozens of “next” links.

3. Export to CSV or Excel

Click the extension icon and hit Export. It collects every review with all five ratings and firmographics, then downloads a CSV (Excel-compatible) to your machine. Open it in Sheets or Excel and you're ready to filter, sort, and pivot immediately.

SoftwareSuggest-specific tips and quirks

SoftwareSuggest data behaves differently from G2 or Capterra. Keep these regional realities in mind when you analyze your export:

The reviewer base is India and SEA, not the US

Expectations around pricing, support hours, and feature priorities differ markedly from Western sites. Treat SoftwareSuggest as a window into how APAC buyers evaluate software, not as a regional copy of G2.

Value-for-money is the headline signal

Price sensitivity runs higher in emerging markets, so the value_for_money sub-rating often tells you more than the overall score. A strong overall rating paired with a weak value score is a clear pricing or packaging warning for the region.

Reviews reference local payments and tax

Expect mentions of GST and other regional taxes, local payment methods, and regional support hours in the free text. These are gold for localization planning — search review_text for GST and currency terms.

Firmographics make it pivotable

Because every row carries industry and company_size, you can segment sentiment by vertical and by SMB-vs-enterprise with no manual tagging.

Sub-ratings can diverge from the overall

Reviewers sometimes leave a glowing overall star count while scoring support or features much lower. Always read the four sub-ratings alongside overall_rating rather than trusting the headline number alone.

Turn SoftwareSuggest reviews into insights

Once the data is in a sheet, three analyses pay for themselves quickly:

Quantify regional price sensitivity

Compare the average value_for_money sub-rating against the same product's G2 score. The gap is a direct measure of how differently APAC buyers perceive your pricing.

Find localization gaps

Keyword-flag localization terms — language, currency, GST, support hours — across review_text and cons to surface the regional gaps your roadmap is missing.

Pivot sentiment by vertical

Pivot overall_rating by industry to identify your strongest APAC verticals — the segments where you already win, and where regional marketing spend will compound.

Who uses exported SoftwareSuggest reviews

India & APAC market-entry teams

Validate demand and read real buyer expectations before committing budget to a regional launch.

Pricing & localization researchers

Mine value-for-money scores and tax, currency, and support mentions to tune regional packaging.

Emerging-market competitor analysts

Benchmark rivals' sub-ratings and complaints to spot openings Western directories never reveal.

Regional vertical-targeting marketers

Use industry firmographics to focus campaigns on the verticals where your ratings are strongest.

Frequently Asked Questions

Why use SoftwareSuggest over G2?

Its reviewer base is concentrated in India and Southeast Asia, so pricing expectations, support norms, and feature priorities reflect emerging-market buyers. If your audience is APAC, this data is far more representative than US-dominated G2 reviews.

Does it capture sub-ratings and firmographics?

Yes. Every export includes the ease-of-use, value-for-money, customer-support, and features sub-ratings alongside the reviewer's industry and company size.

Is it good for market-entry research?

Absolutely. The combination of regional sentiment, price-sensitivity scores, and localization signals makes it one of the cleanest data sources for evaluating an India or SEA launch.

How many reviews can I export?

The extractor walks every page of a listing, so you get the full review history for a product in a single CSV rather than capping at the first page.

Do I need an account?

No. There's no signup or login — install the extension, open a reviews page, and export.

Ready to export your first SoftwareSuggest listing?

Install the extractor and turn any reviews page into an analysis-ready spreadsheet in under a minute.

Get the SoftwareSuggest extractor

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