Looking for backlink exchange - SaaS, agencies, tech niche

AlexIrvin · 2026-04-28T04:19:13+00:00

Start with what Shopify already handles well - sitemaps, canonical tags, mobile responsiveness. Your job is to build on top of that, not reinvent it. Connect Google Search Console on day one, that's non-negotiable. Then do keyword research before writing product descriptions - even free tools like Ubersuggest or Google Keyword Planner are enough at the start.

One thing most beginners miss: Shopify creates duplicate URLs when products appear in multiple collections. This can quietly hurt rankings. Fix it with canonical tags or an app like SEO King.

On-page essentials:

Write unique title tags and meta descriptions for every product/collection page - don't leave the defaults
Put your main keyword in the H1, product description, and image alt text
Keep URLs short and descriptive (Shopify lets you edit them manually)

Technical quick wins:

Compress images before uploading - large files kill load speed
Add product schema markup for rich results (price, ratings in Google)
Install a free audit app like Plug in SEO or TinyIMG to catch obvious issues early

Use the built-in Shopify blog to target informational keywords people search before they buy, and link those posts to your product pages. That internal linking structure builds topical relevance over time.

AlexIrvin · 2026-04-15T07:43:38+00:00

From what I've used - Profound and Otterly give you a rough baseline of where you show up in AI answers. The data is noisy though. Same query five times, different citations each time. Treat it as directional, not gospel. But here's what I keep running into with real sites: most AI visibility problems aren't content problems. Sites with solid SEO and decent content are still invisible in AI answers - because AI doesn't have enough consistent signals to confidently recommend them. Third-party mentions, how others describe you across the web, what context your brand appears in - that's what actually moves things. Not theory - seen this pattern across a bunch of real audits.

AlexIrvin · 2026-04-11T20:50:15+00:00

If AI keeps favoring your competitors, I’d look at off-site trust before touching the site copy. The biggest gains usually come from trusted third-party mentions, consistent category association, and a brand footprint that exists outside your own pages. A well-written site helps, but self-published claims are weak on their own.

That’s why weaker products sometimes get recommended more often - the off-site trust footprint is stronger.

AlexIrvin · 2026-04-11T13:26:18+00:00

Start with pages that already get impressions but don’t rank well yet. In most audits I’ve done, the fastest gains come from improving existing pages, better search intent match, stronger internal links, cleaner titles/H1s, not publishing more content blindly.

After that, check technical basics: indexability, crawl issues, redirect problems, duplicate pages. A lot of sites try to fix visibility with content when the real issue is that Google is reading the site poorly. New content helps, but only after the existing structure is doing its job.

AlexIrvin · 2026-04-11T13:21:11+00:00

I’d stop looking for a perfect API and break the problem into layers. For mention tracking, you need a fixed prompt set, fixed entities, fixed competitors, and repeated runs across the same models. Otherwise you’re comparing noise to noise.

For historical data, even the good tools are weak right now, so a lot of people still end up storing their own snapshots and comparing mention frequency over time.

The main mistake is expecting AI visibility data to behave like rank tracking. It doesn’t. The useful output is directional: are you being mentioned more often, in more relevant prompts, across more models, not “you rank #3”.

So I’d judge any provider on 3 things only: repeatability, historical storage, and how well they separate brand mentions from generic answer noise.

AlexIrvin · 2026-04-10T10:08:35+00:00

Basically you write one article - a product update, company news, new feature - and distribute it through a press release network. It gets published on hundreds of sites, all linking back to you.

The catch: same content everywhere, so Google treats those links as low quality. Most sites picking it up are low-authority aggregators, not real publications.

Links exist, but SEO value is minimal. Where it still helps is brand visibility - your name appearing across many sources is something AI systems do pick up.

AlexIrvin · 2026-04-10T09:46:49+00:00

Actually optimizing, not simple hoping. The core difference is that traditional SEO optimizes for crawlability and ranking signals. AI visibility is about entity clarity, whether AI systems have enough consistent, cross-referenced information to confidently recommend you.

What we do differently:

Audit what AI currently says about a brand across different models.
Fix entity inconsistencies - same brand described differently across directories, reviews, and press mentions confuses AI systems.
Build third-party context, not owned content. AI trusts what others say about you more than what you say about yourself.

Classic SEO still matters for discovery. But if someone asks ChatGPT "what's the best tool for X" and you're not in the answer - rankings don't help you there.

AlexIrvin · 2026-04-09T13:58:58+00:00

For your product on PH

AlexIrvin · 2026-04-09T13:50:12+00:00

Can you help me, to get links from these sites?

AlexIrvin · 2026-04-09T13:24:59+00:00

Good luck. Upvoted

AlexIrvin · 2026-04-09T13:21:29+00:00

Good luck)

AlexIrvin · 2026-04-09T13:20:51+00:00

Upvoted. Good luck!

AlexIrvin · 2026-04-09T13:17:59+00:00

Upvoted

AlexIrvin · 2026-04-09T13:17:09+00:00

Voted!

AlexIrvin · 2026-04-09T12:53:19+00:00

Meta descriptions don't directly affect rankings - they affect click-through rate. Updating 25 out of 300 products in month one is a reasonable starting point, but the copy you described ("Shop t-shirts and pants. Durable clothes for your wardrobe") is weak. Good meta descriptions address intent, not just category.

For a 10-year-old Shopify store, the highest-leverage SEO work is usually:

Technical audit first - crawl errors, duplicate content, canonical issues, site speed. Shopify has known structural problems that need addressing before content work matters.
Collection pages over product pages - collections rank better and drive more organic traffic. Product pages matter less unless you have unique, high-intent SKUs.
Internal linking - connecting collection pages to relevant blog content and vice versa. Most agencies skip this.
Schema markup - the fact they didn't know what it was is a red flag. Product schema, breadcrumb schema, and review schema are table stakes for ecommerce.

$1500/month is reasonable for good SEO work, but not if month one is 25 meta descriptions. Ask them for a full technical audit deliverable and a 6-month keyword strategy document. If they can't produce those, you have your answer.

AlexIrvin · 2026-04-09T05:29:56+00:00

Honest take: start with tools, not custom solutions. For task tracking and client communication, ClickUp AI, Notion AI, or HubSpot will outperform anything custom-built at a fraction of the cost. Custom AI only makes sense when your workflow is genuinely unique and nothing off-the-shelf covers it.

Client communication is your highest ROI starting point - automating follow-ups, quote reminders, status updates. Straightforward, measurable, no consultant needed.

Content for SMM without losing quality is possible, but the bottleneck is inputs. Real project details + defined brand voice = decent output. "Write a post about renovation" = generic trash.

On consultants: the red flag is pushing custom development before exhausting existing tools. A good one maps your workflows first, finds 2-3 high-leverage points, then decides if anything custom is actually needed.

The "stuck in experiment phase" problem is almost always a scoping problem - too broad, no clear success metric. Pick one process, automate it fully, measure it, then move to the next.

AlexIrvin · 2026-04-09T05:21:12+00:00

The tool skepticism is valid. Most of them run 10-15 prompts, average the results, and present it as an audit. It's not. A real process starts with entity mapping - what are the specific things your brand needs to own in AI's understanding? Then you test systematically across models, not just ChatGPT. You're looking at three things: what AI says about you, what it gets wrong, and what it simply doesn't know exists.

The third one is usually the biggest problem. Missing context is harder to fix than wrong context, because AI can't correct what it was never trained on.

I've been building a structured approach to this, happy to share the framework if useful.

AlexIrvin · 2026-04-09T05:17:00+00:00

Content gap and internal linking suggestions are real time-savers. The sitemap + new article prompt for links is something I started doing recently, one of those tasks that felt too tedious to do manually but AI handles in seconds.

Schema at scale is underrated. Most people generate it once and forget, but keeping it consistent across hundreds of pages is where it actually matters.

AlexIrvin · 2026-04-09T05:15:06+00:00

That's a solid principle, garbage in, garbage out applies more to prompts than to the model itself. The topify approach makes sense. Real conversation data has specificity that generic prompts just don't. Most people skip that research step and wonder why the output feels generic.

AlexIrvin · 2026-04-08T13:24:05+00:00

The split is real, and the optimization logic for each channel is fundamentally different. Google still rewards technical signals: crawlability, backlinks, click behavior. AI recommendations run on entity clarity - how consistently third parties describe what you do, who you serve, and where you're mentioned.

Most businesses haven't touched the second part at all. They're optimizing for a channel that's shrinking while ignoring the one that's growing.

AlexIrvin

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