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ICODA’s reported case studies point to different strengths, not one universally winning crypto-marketing channel: GEO and AI search have the strongest conversion figures in the examples, SEO and PR are presented as longer-lasting, and KOL campaigns as faster to deliver reach. Those are conclusions drawn from agency case reports, not the results of a controlled comparison. For a budget decision, the most useful evidence is the baseline, measurement period, outcome definition and whether someone outside the campaign can reproduce the result.
What the case-study comparison can—and cannot—tell you
TechBullion’s October 2, 2026 article by Dan El summarizes reported ICODA campaigns across six channels. Its overall comparison is useful as a map of reported outcomes, but the examples use different projects, goals, periods and measurement methods. They do not establish that one channel will outperform another for a different crypto project.
| Channel | What the reported cases are used to illustrate | What to scrutinize |
|---|---|---|
| GEO and AI search | Higher conversion in one comparison and visibility in AI-generated answers | Referral definitions, engine and query coverage, and repeatability |
| SEO | Organic traffic and search visibility growth over time | Starting traffic, duration, market and other work happening concurrently |
| PR and media placements | Search visibility, reach and outcomes associated with placements | Placement quality, attributable outcomes and the role of other channels |
| Influencer/KOL marketing | Rapid audience reach and coordinated campaign activity | Audience fit, on-chain or conversion outcomes, and market movement |
| Community and reputation | Changes in mentions, sentiment, search visibility and community activity | Sentiment definitions, placement quality and independent verification |
| Paid advertising | Reported purchases, revenue and app-install costs | Attribution, account stability and whether results recur beyond one campaign |
The figures below are claims reported by TechBullion about ICODA-attributed cases. The underlying analytics were not included in the material reviewed, so they should not be read as audited performance guarantees. In particular, a traffic increase, ranking, reach figure, purchase count and return on ad spend (ROAS) measure different things.
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GEO and AI search: promising conversion claims, but test by engine
For Defiway, a crypto payments platform, TechBullion reports a 30-day conversion rate of 46% for ChatGPT-referred visitors versus 29% for Google organic visitors, alongside 24.88% growth in ChatGPT users over that period. The article does not provide the analytics definitions or underlying records, so the comparison is an agency case claim rather than independent confirmation. The conversion-rate difference is meaningful only if the two visitor groups used the same conversion event, attribution window and comparable traffic-quality rules.
#1 Best Overall
Other AI-visibility examples in the article have different baselines and outcomes. TechBullion says ICODA’s own website reached number one in ChatGPT for “best crypto marketing agency” queries within four months; it separately reports ChatGPT referrals converting 2.4 times better than Google Search, explicitly identifying that figure as self-reported. For an unnamed crypto prop-trading firm, the article reports reaching number one in Google AI Overviews in the US and UK within 90 days and 208% growth in Perplexity users. These cases should not be combined into a single conversion benchmark: they concern different sites, engines and measures.
The same article relays ICODA’s AI Visibility page as describing three implementation timelines: opening robots.txt to AI crawlers takes effect within days; answer-first pages with schema markup show results in two to eight weeks; and third-party citations usually begin appearing in four to six weeks. It says the tool samples ChatGPT, Claude, Perplexity and Gemini. These are timelines and product details as described by TechBullion, not independently verified current documentation. Visibility can vary by engine and query, so a ranking claim needs the exact prompt or query, date, location and repeat test.
SEO: distinguish compounding growth from a campaign snapshot
For the no-KYC exchange Godex, TechBullion reports monthly organic visits rising from 7,551 to 20,634 over roughly 18 months, or 2.7 times the starting level. It also reports referring domains increasing from 2,510 to 4,177, conversions up 24% year over year, and AI Overview citations increasing from about 52 to 967. Each measure has a different denominator and period; the article does not establish that SEO work alone caused the changes.
For token-creation platform 20lab, the article reports organic traffic growth of 80% in about four months, a number-one US position for “create a crypto token,” and more than 20 keywords in the top ten. This is a separate project and timeframe from Godex, so the growth percentages are not directly comparable.
TechBullion’s strategic argument is that SEO and GEO can work as a pipeline: pages that already rank in conventional search may also be drawn on by AI Overviews and chat-based search. The cases make that a plausible planning hypothesis, not a demonstrated causal rule. A buyer should ask which pages changed, when they changed, and whether visibility persists across search and AI results.
PR and media placements: placements are inputs, not proof of impact
TechBullion reports that ICODA PR placements are indexed within 24–72 hours on average and remain in search results for months. The article also says ICODA had placed more than 8,000 publications, naming CoinTelegraph, CoinDesk, BeInCrypto and Decrypt. These are figures and outlet examples reported by the article; an outlet name alone does not establish the placement’s format, prominence, audience or effect on a campaign.
In one prop-trading firm campaign, the article says 23 PR publications formed the core of a campaign that reached number one in AI Overviews in two markets. GameFrog reportedly received more than 30 placements, followed by six or more Google top-ten rankings and estimated media reach above two million. Vabble combined PR with YouTube and X; TechBullion associates that campaign with a private round of $1,138,760 and 16,000 new users. Those outcomes are reported campaign figures, not audited results in the material reviewed. The Vabble example in particular combines channels, so it cannot isolate PR’s contribution.
Influencer and KOL marketing: speed does not establish causation
TechBullion describes KOLs as the fastest channel in its case set, reporting a tier-one audience of 4.27 million within 72 hours of a first post. For Banana Gun, a Telegram trading bot, ICODA reportedly coordinated 77 publications—43 on YouTube and 34 on X—from 69 KOLs across five regions. In the six weeks after the campaign, the article reports the token price rising from $15.63 to $43.12. It explicitly cautions that market conditions also played a part: the timing is correlation, not evidence that the campaign caused the price increase.
The article says the Banana Gun effort selected KOLs by region rather than follower count, coordinated launch posts in one window and tracked results on-chain rather than by views. Those are useful details to request in a proposal, but the article does not provide the underlying records for independent review. It also reports a separate effort involving more than 160 AI accounts that reached over 200 million people in five months with zero platform flags. That claim is not independently substantiated in the reviewed material, and reach alone does not show engagement, qualified users or policy compliance beyond the reported period.
Community and reputation: inspect how sentiment and activity are counted
For Godex on Reddit, TechBullion reports mentions growing from 67 to 590 through 523 placements across 39 subreddits. It says positive mentions rose from 63% to 82% in one month. These figures describe placement and sentiment counts, not necessarily unique users or conversions; the article does not provide the coding method used to classify sentiment.
A casino client’s Reddit sentiment reportedly shifted from 41% positive to 82% positive in six weeks, while negative sentiment fell from about 38% to about 10%. Separately, a Bitcoin casino reportedly reached page one on Quora for all six target queries in three weeks without ad spend. Both examples are agency-reported outcomes; the article does not supply an independent sentiment audit or enough detail to establish how long the rankings held.
For RootstockCollective, TechBullion reports that a Discord funnel involving 15 partner communities, combined with PR-driven search, brought in 220 stakers—48.3% of all new stakers—and helped the project reach number one on Google for “Bitcoin DeFi staking.” It also reports holders increasing from 1,095 to 1,550. The article says holder counts can be checked on-chain and identifies this as its strongest case, but the reviewed material did not include an independent chain-data check. A buyer should verify the relevant addresses, dates and definition of a holder before treating the count as confirmed.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Paid advertising: strong reported efficiency can coexist with platform risk
For one Meta token-presale campaign, TechBullion reports $10,377.63 in spend, 8.86 million impressions, a $1.17 CPM, 109 purchases and 5.74× ROAS. For a second AI token presale, it reports $10,000 in spend, 171 purchases and more than $80,000 in revenue in one month, described as 8× ROAS with a $58 cost per acquisition. These are separate historical agency cases. The article does not supply the attribution rules, revenue accounting or repeat-campaign results needed to treat either ROAS figure as a forecast.
For wallet app walllet.com, reported cost per install was $10.42 on Meta, $11.02 on Google, $13.25 on Moloco and $29.85 on X. The article also says the campaign lost more than ten ad accounts. Those platform costs and account losses describe one reported campaign; they do not establish typical costs or the current policy risk for other advertisers. For any paid proposal, ask how the team plans for account interruptions and whether purchase or install attribution can be reconciled against the product’s own records.
How to judge whether a result is credible enough to budget against
Ask for a case record that lets you understand what changed, for whom and over what period—not just a headline percentage. Dan El’s TechBullion article puts it this way: “The best crypto marketing agency is the one that can show baselines, timeframes and verifiable numbers for the channel you need.” Apply that standard with these checks:
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Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →- Match channel to stage and goal. The article proposes KOLs and paid ads for launches, PR and GEO for authority, and SEO for compounding visibility. Treat this as a planning framework, then confirm that the proposed outcome matches your own stage and objective.
- Get the baseline and denominator. Ask what the starting count was, what counts as a visitor, conversion, holder, mention or install, and whether the number is unique or cumulative.
- Set the period and attribution rule. Establish when measurement begins and ends, which conversion event counts, and how the agency separates its activity from other marketing, product changes and market movement.
- Verify outcomes where they occur. For on-chain claims, request the addresses, chain and measurement dates. For search rankings, reproduce the query and record location and date. For analytics claims, request a view that shows the relevant source and event definitions.
- Test AI visibility beyond one screenshot. Check more than one engine and more than one relevant query, and repeat checks over time. A ranking on one prompt is not broad or durable visibility.
- Ask what must be maintained. Find out whether rankings, citations, placements or community visibility require continued content updates, outreach or monitoring, and who owns that work after a campaign.
- Include cost and account risk. For paid campaigns, ask about the effect of disapprovals or lost accounts; for KOL and community work, ask how audiences and placements are vetted.
Why AI-search rankings need especially careful interpretation
A separate Coinpedia press release dated September 18, 2026 describes an audit of more than 25 buyer-intent queries about crypto GEO, AEO, AI SEO and LLM visibility, tested across ChatGPT, Perplexity and Claude in September 2026. It reports ICODA leading every ChatGPT query, with results varying on Perplexity and Claude; only “best crypto GEO agency” produced first-place agreement across all three engines. Coinpedia also says quantitative agency claims were self-reported and advises tracing citation sources. Because the item is a press release and Coinpedia’s disclaimer says it does not endorse, verify or accept responsibility for its accuracy or completeness, the audit is a point-in-time report—not proof of agency quality or a durable ranking.
Across the cases, the most decision-useful distinction is between an outcome that is independently reproducible and one that is only reported by the campaign’s publisher. Ask to see the starting point, the measurement method and a way to check the result before using a case study as the basis for your own budget forecast.
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