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Generative Engine Optimization (GEO): 20 Plays to Get Mentioned by AI

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A new discipline is being born in real time. Being cited in ChatGPT, Perplexity, Claude, and Gemini answers is becoming as important as ranking in Google — and the early movers are winning categories. Most brands haven’t started optimizing for AI engines. The window is open in a way that Google SEO hasn’t been open for twenty years. 20 practical moves for becoming the brand AI engines name and recommend.

Key Takeaways

  • AI engines reward direct-answer intros, question-format headings, FAQ/HowTo schema, and entity coverage.
  • Original research and named frameworks are citation magnets — “According to [your brand]” is the most valuable sentence pattern in GEO.
  • Brand entity recognition (Wikipedia, Wikidata, schema, consistent bios) is a 2–3 year compounding investment.
  • Track citation share monthly across ChatGPT, Perplexity, Claude, Gemini — most brands don’t.
  • Start with #162 (track AI engine citations) and #163 (create quotable statements).

20 Practical Moves at a Glance

# Play Best when Expected result
161 Optimize for AI Overviews Any SEO-active content team 30+ AI Overview citations
162 Track AI engine citations Forward-looking marketing teams 40%+ citation share achievable
163 Create quotable statements Category thought-leadership plays ~500 inquiries/year from citations
164 Build answer-engine structure Technical or help content teams 20–25x AI referral traffic
165 Monitor ChatGPT/Perplexity/Claude mentions Brands with outdated AI descriptions 15%+ demo rate lift
166 Optimize FAQ for answer engines Categories with common questions 20%+ FAQs gain AI citations
167 Build topical authority for AI engines Building ownership of a niche 15x inbound in one topic
168 Create original research (citable) PR + thought leadership combined 100+ earned citations per report
169 Structure content for RAG retrieval Technical and developer content 40%+ developer-side discovery
170 Optimize for conversational queries Opening a new acquisition channel 10K+ monthly visits from AI
171 Build brand entity recognition Established but under-recognized brands Brand search impressions +40%
172 Create direct-answer intros All future-facing content teams 3x AI citation rate
173 Use claim-evidence-source pattern Research and data-driven content Top-cited source in your niche
174 Track AI share-of-voice Modern marketing leadership 3x category share-of-voice
175 Correct AI-engine misinformation Brands with inaccurate AI descriptions AI descriptions corrected in 30–60 days
176 Optimize for multi-modal search Image-rich product catalogs 4x visual search traffic
177 Build authoritative landing pages Consultants/experts with niches One page = 40%+ of traffic
178 Generate testimonial-rich content Review-signal-positive categories 45+ AI-sourced demos/month
179 Optimize for voice assistants Local service businesses 8–10x voice-driven calls
180 Create AI-friendly product pages DTC and ecommerce brands 5–7% revenue from AI engines

Highlights

Optimize for AI Overviews

Direct-answer intro (2–3 sentences), question-format H2s, FAQ/HowTo schema, cite original sources. A B2B SaaS restructured 40 high-traffic articles — citations in AI Overviews grew from 3 to 29 in 90 days; AI Overview clicks rose ~6,400 monthly visits.

Create Original Research

Surveys and data reports = citation magnets. An HR-tech startup published a 1,500-person original survey — cited in 140+ articles, LinkedIn posts, and AI engine responses over 18 months. Report downloads: 11,000+, of which 1,200 became qualified leads.

Build Brand Entity Recognition

Wikipedia/Wikidata, consistent NAP, Knowledge Graph entity, structured data. A mid-market SaaS established a Knowledge Graph entity in 4 months; AI engines started naming them correctly — brand search impressions grew 38%.

Create Direct-Answer Intros

First 50 words decide citation. A content team rewrote intros on 60 articles — AI Overview citation rate went from 8% to 31%. Now every new piece is written with AI citation in mind.

Frequently Asked Questions

What’s the difference between SEO, AEO, and GEO?

SEO earns eligibility (being indexed and rankable). AEO earns selection (being cited inside AI answers). GEO earns mention (being named or recommended in generative responses). All three run together; you need each for full visibility.

Why is GEO a 2–3 year play?

Brand entity strength compounds slowly. Wikipedia entries take time to earn. Cross-surface mentions (podcasts, press, Reddit) build over quarters. The brands establishing entity authority in 2025–26 will benefit for years; this is a now-or-never window.

How do I track AI engine citations?

Manually for free (run 25 priority queries weekly across ChatGPT, Perplexity, Claude, Gemini, log results) or via paid tools (Profound, Otterly, BrightEdge AI Catalyst). Manual tracking is sufficient for the first year.

What content gets cited most by AI engines?

Original research, named frameworks, comprehensive guides, FAQ pages with crisp answers, and pages with clear claim-evidence-source structure. Vague summaries and SEO-optimized listicles get cited least.

Should I optimize differently for ChatGPT vs Perplexity?

Slightly. Perplexity is citation-forward and rewards original data and methodology. ChatGPT favors recent content and recognized brands. Build one strong foundation; tune format emphasis per engine.

How do I correct AI misinformation about my brand?

Identify quarterly inaccuracies via manual querying. Publish clear correction content with schema. Earn citations to the correct source. AI descriptions typically update within 30–60 days for high-quality corrections.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Riman Agency AEO 2E series — full 29-chapter playbook
  • Aggarwal et al. — “GEO: Generative Engine Optimization” (arXiv)

Work With Riman Agency

Riman Agency builds GEO programs that compound across years. Get in touch for a 90-day GEO foundation.

Part 9 of our 25-part series. Previous: SEO Fundamentals. Up next: Social Media Strategy.

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AI SEO Fundamentals: 20 Plays for Modern Organic Search

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SEO is not dead. It split in two. Classical search still drives real traffic — but it looks different when half your audience is asking AI engines instead of Google. The winning 2026 SEO strategy combines classical discipline (topic authority, internal linking, technical hygiene, structured data) with AI-scale execution (content refresh at scale, entity coverage, meta optimization in bulk). 20 practical moves for organic search that compounds.

Key Takeaways

  • SEO is the eligibility layer for everything else, including AEO and GEO. No SEO foundation = no AI engine ceiling.
  • Topic clusters beat single-keyword pages. AI engines retrieve clusters, not keywords.
  • Content refresh at scale typically lifts existing-page traffic 30–50% with no new content.
  • Entity-based SEO opens long-tail rankings you didn’t directly target.
  • Search Console is the highest-ROI free tool — most teams underuse it dramatically.

20 Practical Moves at a Glance

# Play Best when Expected result
141 Run topic cluster research SEO-driven growth teams 100K+ monthly visits per 3 clusters
142 Run entity-based SEO Content sites with entity-rich topics 50%+ organic lift, no new content
143 Audit existing content Blogs with 300+ articles 40%+ organic lift from refreshes
144 Build internal linking strategy SEO plays needing authority flow 3–5 ranking positions gained
145 Generate meta/alt/schema at scale Mid-to-large content sites 15–20% SERP CTR lift
146 Mine long-tail keywords Competitive categories 3–4x conversion on long-tail
147 Optimize for featured snippets Question-driven content topics 30%+ snippet capture rate
148 Run local SEO optimization Multi-location service businesses 100%+ local leads growth
149 Build E-E-A-T signals YMYL categories 60%+ organic lift on YMYL
150 Update for freshness Content older than 18 months 50%+ organic recovery
151 Run a technical SEO audit Large sites with audit reports 25%+ organic lift from top fixes
152 Research backlink opportunities DR-constrained SEO plays DR up 10+ points, 70%+ traffic lift
153 Analyze competitor backlinks Manual link-building operations 3–4x outreach success rate
154 Do content gap analysis Catching up on SEO parity 30K+ monthly visits recaptured
155 Map URL structure + redirects Site redesigns or migrations 20%+ post-migration recovery
156 Recover broken links Sites with recent migrations 10K+ monthly visits recovered
157 Optimize page speed Slow sites impacting rankings Ranking lift + bounce reduction
158 Audit mobile UX Mobile-majority traffic sites Mobile conversion 1.5–2x
159 Deploy structured data at scale Ecommerce and content sites 20–30% SERP CTR lift
160 Cluster content by search intent Traffic-rich but conversion-poor SEO 60%+ demo request lift

Highlights

Run Topic Cluster Research

Pick a pillar topic. Generate 30–50 subtopics by intent. Build 1 pillar + 10–15 spokes. A B2B HR-tech team built 3 clusters of 15 articles each over 9 months — combined organic traffic: 115,000 monthly visits worth ~$84K/mo in equivalent paid search value.

Audit Existing Content

Classify pages: keep / refresh / merge / prune. A 7-year-old SaaS blog with 800 articles refreshed 48 high-potential pages — organic traffic lifted 41% in 3 months at ~$280K annualized paid search equivalent.

Build Internal Linking Strategy

120 strategic internal links over 6 weeks. Key commercial pages gained 4 ranking positions on average; top target keyword moved from #8 to #3. Free, fast, reliably effective.

Generate Meta/Alt/Schema at Scale

400 pages’ meta data processed in 2 days vs ~3 weeks manually. SERP CTR rose 18% from optimized meta descriptions — adding ~12,000 clicks/month.

Frequently Asked Questions

Is SEO worth investing in given AI Overviews?

Yes — more than ever. SEO is the eligibility layer for AI engines too. Failing at SEO means failing at AEO and GEO. The brands with the best SEO foundations are also the brands most cited by AI engines.

What’s the highest-ROI SEO play in 2026?

Refreshing existing content. Most mature blogs have 40–60% of pages with refresh potential that’s never executed. Refresh ROI consistently beats new-content ROI for libraries over 200 articles.

How are topic clusters different from keyword targeting?

Topic clusters are pillar pages + 10–15 spoke pages all interlinked, covering a topic comprehensively. Modern engines (and AI engines) retrieve clusters, not single keywords. Clusters beat keyword targeting on every modern SEO metric.

Should I still build backlinks?

Yes — but earned through original work, not bought. Highest-yield strategies: original research, free useful tools, guest posts on respected publications. Bought links carry rising risk and falling reward.

What’s the most underused free SEO tool?

Google Search Console. Most bloggers haven’t logged in for 90 days. It tells you exactly which queries you’re ranking for, which pages aren’t indexed, and where Core Web Vitals are slipping. 30 minutes per week is the highest-ROI SEO investment you can make.

How does E-E-A-T affect content?

Especially in YMYL categories (health, finance, law), demonstrable Experience + Expertise + Authoritativeness + Trustworthiness drives ranking. Author bylines, credentials, citations, and original data all serve as signals. Sites investing in E-E-A-T see 50–70% lifts on sensitive topics.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Google Search Central documentation
  • Riman Agency AEO 2E series

Work With Riman Agency

Riman Agency runs SEO + AEO health audits with prioritized fix lists. Get in touch for a 30-day SEO health check.

Part 8 of our 25-part series. Previous: Video & Audio. Up next: GEO — Generative Engine Optimization.

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AI Video and Audio Content: 20 Plays for Production at Modern Cadence

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Video is 80% of social consumption. AI is the only way brands can produce at the volume modern video demands. AI transcription, captioning, auto-editing, avatars, and voiceover all matured into production-ready tools in 2024–25. A single marketer can now script, edit, and publish three Shorts a week. 20 practical moves for systematic video and audio production.

Key Takeaways

  • Repurposing long video to Shorts is the highest-leverage video play — one podcast = 15–20 clips.
  • Auto-captioning lifts video completion rates 40%+ across platforms (most social video is watched muted).
  • Show notes and chapter markers (#125, #126) drive podcast discoverability and listener retention.
  • YouTube SEO + thumbnail optimization (#130, #131) routinely lifts CTR 30–50%.
  • AI voiceover ($200/mo subscriptions) replaces $150/video human voiceover at production scale.

20 Practical Moves at a Glance

# Play Best when Expected result
121 Script short-form videos Founders/experts building audience 25x subscriber growth in 6 months
122 Generate AI avatars for video Multilingual enablement content $40K+ saved on talent costs
123 Repurpose long video to shorts Podcasters/webinar producers 5–6x audience growth rate
124 Auto-caption and translate video Any team producing video 40%+ completion rate lift
125 Create podcast show notes Podcasters with websites 10x organic traffic
126 Generate podcast chapter markers Long-form podcasts (30+ min) 15–20% retention lift
127 Auto-edit raw footage Content creators and video teams 70%+ editing time saved
128 Create AI voiceover narration High-volume video production $50K+/year vs human voiceover
129 Build explainer animation scripts Complex or technical products 60–80% trial conversion lift
130 Generate YouTube title + description YouTube creators of any size ~2x CTR on titles
131 Create video thumbnails YouTube creators seeking growth 30–50% CTR lift
132 Script webinars and live sessions B2B webinar-driven pipeline 2x post-webinar demos
133 Build a video SEO strategy Products needing visual explanation 200+ video-sourced leads/month
134 Create audiograms from podcasts Audio-first creators 3x podcast audience growth
135 Generate training videos Customer education at scale 40%+ faster time-to-activation
136 Repurpose webinars into podcasts Teams with webinar libraries Second audience for same content
137 Create product demo videos Products with long existing demos 30%+ trial signup lift
138 Design testimonial video structures B2B conversion-focused pages 2–3x landing page conversion
139 Build a YouTube Shorts factory Consultants/creators building inbound 6-figure inbound from Shorts
140 Script TikTok/Reels from data Niche experts with data access Single viral = 10+ inbound leads

Highlights

Repurpose Long Video to Shorts

One 60-min podcast → 15–20 Shorts via Opus Clip, Vizard, or Descript. A business podcast turned every episode into 15–20 Shorts; over 12 months, Shorts drove 2.4M views and grew newsletter signups from 200/week to 1,100/week.

Create Podcast Show Notes

AI-generated SEO-optimized show notes with summary, key points, timestamps, quotes. A B2B podcast’s show notes site grew from 1,400 to 18,000 monthly visits in 9 months — became the #2 source of new podcast subscribers.

Generate YouTube Title + Description

10 title + description variants per video; A/B test via YouTube tools. A channel with 50K subs lifted average CTR from 4.1% to 7.8% over 90 days — nearly doubling views per upload with no change in content quality.

Build a YouTube Shorts Factory

5 Shorts/week using systematic process. A consultant did this for 12 months — built 45K subscribers; inbound from Shorts drove 6 new consulting clients worth $180K in fees.

Frequently Asked Questions

What’s the most underused video play?

Repurposing long-form video to Shorts. Teams with podcasts or webinar libraries are sitting on goldmines. AI tools like Opus Clip make 15–20 Shorts per long video economical — 5x audience growth without producing new content.

Are AI avatars ready for production use?

Yes for specific cases — multilingual training videos, narrated explainers, internal enablement. Disclose them. Less suitable for brand-defining hero content where authenticity matters most.

What matters most for YouTube growth?

Title and thumbnail (90% of CTR), then first 30 seconds (retention). AI tools optimize all three at scale. The compounding effect over 50–100 videos is substantial.

Should I add captions to all video?

Yes. Most social video is watched muted; captions lift completion rates 40%+. Auto-captioning tools (Descript, CapCut, Captions) make this trivially cheap.

How do I get podcast distribution?

Show notes drive SEO; chapter markers improve retention; audiograms unlock social discovery; transcripts feed AI engines. The “podcast → 8 derivative content pieces” pipeline is what scales podcasts beyond their immediate listener base.

What’s the budget for AI video production?

$50–$200/month for tools (Descript, Opus Clip, ElevenLabs). Replaces what was previously $5K–$15K per video in agency costs. ROI typically pays back in the first month.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Tools: Descript, Opus Clip, Vizard, ElevenLabs, HeyGen, Riverside, Captions

Work With Riman Agency

Riman Agency builds video repurposing pipelines for content teams. Get in touch for a 30-day video factory build.

Part 7 of our 25-part series. Previous: Visual Content. Up next: SEO Fundamentals.

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AI Visual Content and Design: 20 Plays for Brand-Consistent Production at Scale

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Visual production costs collapsed one-hundred-fold in two years. Visual strategy is now the differentiator — not budget or production capacity. AI image and design tools (Midjourney, Firefly, DALL·E, Flux, Ideogram, Canva Magic) passed the commercial threshold in 2024–25. The new constraint is cohesive visual strategy. 20 practical moves for using AI to produce consistent, on-brand visuals at scale.

Key Takeaways

  • Pick one image generator and master it. Style consistency builds brand recognition; tool-hopping fragments it.
  • Original charts and data viz are the highest-leverage visual asset — AI engines cite them disproportionately.
  • Stock photography is now a “slop signal.” AI-generated brand imagery outperforms it on engagement.
  • AI video is good for short clips and edits — not for replacing real video at long form.
  • Always disclose AI-generated images. Trust beats stealth in 2026.

20 Practical Moves at a Glance

# Play Best when Expected result
101 Generate on-brand AI imagery Brand-heavy creative orgs 90%+ cost reduction vs stock
102 Create social graphics at scale Small teams without in-house design 3 weeks → 1 afternoon
103 Design presentation decks with AI Leaders giving frequent talks 10x faster deck production
104 Build infographics from data Data-rich PR and reports 3–5x amplification vs full report
105 Generate diverse stock-alternative visuals Brands tired of stock-photo sameness 25–35% engagement lift
106 Create product mockups Apps, SaaS, consumer products $10K+ saved per shoot
107 Design email hero images Email-heavy marketing programs 20%+ email CTR lift
108 Build brand style guide with AI Mid-stage companies lacking docs $20K+ design agency fees saved
109 Generate UI mockups Pre-launch product marketing Marketing ships before product
110 Create before/after visuals Transformation-based products 3x CTR on transformation creative
111 Design data visualizations Research and reporting content 3x shares on data content
112 Build carousel posts LinkedIn B2B brand-building 4–5x reach vs text posts
113 Create meme-style content Developer, creative, youth audiences Viral moments on zero budget
114 Generate Pinterest-optimized pins Recipe, home, craft, DIY verticals 40%+ of traffic from Pinterest
115 Design case study visuals B2B sales-enablement content 3–4x case study reach
116 Build quote cards programmatically Podcasters and interview creators Weeks of content from one hour
117 Create animated explainers Product explanation needs $10K+ and 5 weeks saved
118 Generate lookbook content (DTC) Seasonal DTC and fashion 98%+ cost reduction vs shoot
119 Design email newsletter templates Consistent high-volume email ~20 hrs/month reclaimed
120 Build event marketing visuals Events with modest creative budget $10K+ saved per event

Highlights

Generate On-Brand AI Imagery

Build a visual style guide (palette, mood, composition) and include it in every prompt. A DTC brand replaced 60% of stock photo usage, dropped monthly visual cost from $4,800 to $420 — and AI-generated visuals outperformed stock 1.8x in ad CTR.

Create Social Graphics at Scale

One afternoon = a month of social visuals using Canva Magic, Adobe Express, or Figma plugins. A 2-person marketing team produced 60 graphics across 3 channels in one session — work that previously took 3 weeks of freelancer back-and-forth.

Build Infographics from Data

Turn 40-page reports into one shareable infographic. A B2B research team did this — got 5,200 LinkedIn shares, picked up by 3 industry publications, drove 12,000 report downloads in 60 days.

Build Carousel Posts

10-slide LinkedIn carousels with consistent typography. A B2B consultant began posting 2/week — profile views grew 8x in 4 months, inbound messages went from 1 to 14/week.

Frequently Asked Questions

Which AI image generator is best?

It depends on use case. Midjourney for aesthetic quality and mood; DALL·E for speed and simple concepts; Imagen for photorealism; Flux for customization and style training; Ideogram/Recraft for posters with text. Pick one and master it — consistency beats novelty.

Should I still use stock photography?

Generally no. Stock has become a “slop signal” by 2026 — readers recognize and discount it. AI-generated brand-consistent imagery outperforms generic stock on engagement and feels more on-brand.

What’s the highest-ROI visual asset to invest in?

Original charts and data viz. AI engines cite them as evidence; other writers screenshot them with credit; they signal you’ve done real work. Run one mini-survey per quarter and you’ll have four citation-worthy chart posts a year.

Can AI video replace real video?

Not yet for long-form (over ~30 seconds). Useful for short hooks, animated explainers under 60 seconds, and edits of real footage. Most-watched video content on social still involves a real person on camera.

Do I need to disclose AI-generated visuals?

Yes. Caption with “Image generated with [tool].” Never depict real people without consent. Never present AI footage as documentary. Disclosure is a trust signal in 2026 — hiding AI use carries far more risk than disclosing it.

How do I build visual brand consistency with AI?

Three habits: pick a 3–5 color palette, settle on a style descriptor you reuse in every prompt, maintain a style guide page with sample images and prompt notes. After 6 months of consistent style, your visuals become recognizable from the thumbnail.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Tools: Midjourney, Firefly, DALL·E, Flux, Ideogram, Canva Magic, Datawrapper, Flourish

Work With Riman Agency

Riman Agency builds visual identity systems for content teams. Get in touch for a 14-day visual upgrade.

Part 6 of our 25-part series. Previous: Copywriting. Up next: Video & Audio Content.

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AI Copywriting and Long-Form Content: 20 Plays for Voice That Cuts Through

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AI can write. It cannot yet create the voice that makes people trust you. In a world of commoditized output, voice is the moat. Generic AI writing is most obvious and most punishing in copy contexts — landing pages, sales emails, product descriptions, brand manifestos. 20 practical moves for using AI as leverage on voice, not a replacement for it.

Key Takeaways

  • Brand voice training is foundational — without it, AI default voice gets recognized and penalized.
  • 50-headline testing routinely lifts CTR 2–3x — highest-leverage tactical play in copy.
  • Long-form pillars become economical when AI handles scaffolding; humans add insight and voice.
  • Cold outreach copy typically goes from 2% to 7%+ reply rate with proper personalization.
  • Multilingual content finally feasible with AI + native-speaker review.

20 Practical Moves at a Glance

# Play Best when Expected result
81 Write with trained brand voice Teams using AI for content at scale AI output passes ‘is this you?’ test
82 Generate 50 headlines and test Any content-driven traffic play 2–3x headline CTR
83 Write landing pages that convert Key landing pages needing lift 100%+ conversion lift possible
84 Produce long-form pillar content SEO-led content strategies ~60% page-1 rate
85 Craft story-driven case studies B2B sales-enablement content 3x pipeline influence
86 Write conversion-focused CTAs High-traffic conversion pages 25–40% CTA CTR lift
87 Create 10-flavor elevator pitches Founders and senior leaders Fundraising cycles 50%+ shorter
88 Draft executive thought pieces C-suite or senior brand-building 5x inbound meetings
89 Build FAQ content at scale Support-heavy products 30%+ ticket reduction
90 Write product descriptions that sell Ecommerce with 50+ SKUs 15–20% product-page conversion
91 Generate comparison content B2B with 2+ direct competitors 5–7% demo conversion
92 Create ultimate guides systematically Authority-building SEO plays 10K+ monthly visits per guide
93 Draft sales collateral scripts Sales-marketing enablement 15–25% close rate lift
94 Write effective white papers Enterprise B2B lead generation 800+ qualified downloads
95 Craft research report narratives Data-driven PR strategies 40+ earned media mentions
96 Generate cold outreach copy Outbound SDR teams 3x cold outreach replies
97 Write refund/disclaimer copy humanely Consumer brands with returns Return-customer NPS +20 points
98 Create “vs” pages for SEO Competitive B2B SaaS 4x avg conversion rate
99 Draft editorial letters and manifestos Brand-defining moments Shareable brand statement
100 Build multilingual content Expanding to new geo markets 5–7x international organic traffic

Highlights — The Plays That Compound

Brand Voice Training

Extract sentence length, tone, signature phrases, and banned phrases from 5–10 best samples. Save as a voice doc included in every prompt. One B2B brand’s AI content went from 31% to 87% pass-rate on internal blind tests after this single setup.

Generate 50 Headlines and Test

50 variants in 5 styles per article. Pick 3 by human judgment, A/B test. A growth marketer’s monthly blog traffic grew 62% over 3 months purely from headline optimization — same content, better titles.

Write Landing Pages That Convert

Use frameworks like PAS, AIDA, StoryBrand. Generate 3 variants with different angles. A SaaS landing page rebuild went from 2.1% to 4.8% conversion — annualized impact ~$390K.

Generate Cold Outreach Copy

Personalize using ICP + offer + research. 5 variants per prospect. An SDR team’s reply rate went from 2% to 7.4% — at 1,500 emails/week, that’s ~80 more replies weekly and ~3x more meetings booked.

Frequently Asked Questions

How do I keep my brand voice when using AI?

Build a voice document — sentence length, tone, signature phrases, banned phrases, default stance — and paste it into every AI prompt. Then do a deliberate voice pass on every draft, cutting 10–20% of word count.

Why are 50 headline variants worth the effort?

Headlines decide whether content gets read. AI makes 50 variants cost essentially nothing. Best variants typically lift CTR 2–3x over gut-feel picks. Highest-ROI tactical play in all of content marketing.

Should I use AI for sales emails?

Yes — but only with personalization. Generic AI emails get filtered. Personalized AI emails (referencing specific buyer signals) typically lift reply rates 3x. The personalization is what matters; AI just makes it scalable.

How do “vs” pages perform vs general SEO content?

Significantly better on conversion. They capture high-intent comparison searches. A SaaS startup’s 14 vs pages drove 31,000 monthly visits collectively, with conversion 4.2x site average because intent was higher.

What’s the ROI of multilingual content?

Significant for B2B and creator brands. AI translation + native-speaker review is dramatically cheaper than traditional translation. One B2B SaaS grew international organic from 3% to 19% of total in 9 months after launching Spanish, German, French versions of top content.

Should I disclose AI-assisted writing?

Yes when it would change what readers think they’re getting. Heavy AI assistance with light editing should be disclosed. Full human writing with AI editing usually doesn’t need disclosure. The defensible heuristic: trust beats stealth.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Eugene Schwartz — Breakthrough Advertising (awareness levels)
  • Ann Handley — Everybody Writes (voice + craft)

Work With Riman Agency

Riman Agency builds AI-assisted writing systems with brand voice protection. Get in touch for a 30-day copy upgrade.

Part 5 of our 25-part series. Previous: Content Strategy. Up next: Visual Content & Design.

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AI Content Strategy and Planning: 20 Plays for the Post-Volume Era

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The content arms race is over. Everyone has AI. The winners now compete on strategy, distribution, and taste. Volume stopped being a differentiator and started being a minimum. What matters now is whether content is genuinely useful, distinctive, and distributed — does it reflect a real point of view, does it compound, does it match business goals. 20 practical moves for content strategy that compounds rather than scatters.

Key Takeaways

  • Topic clusters beat isolated posts. Pillar + 10–15 spokes is the new minimum unit of SEO ambition.
  • Content audits unlock dramatic gains — most mature libraries have 40–60% of pages worth refreshing but un-refreshed.
  • The repurposing pipeline turns one hero asset into 15 derivatives — leverage that compounds.
  • Original data, named frameworks, and controversial takes are how voice cuts through commodity AI content.
  • Editorial calendars planned with AI ship 2–3x more content with the same headcount.

20 Practical Moves at a Glance

# Play Best when Expected result
61 Build topic cluster strategy SEO-led growth strategies 40K+ monthly organic visits/cluster
62 Create editorial calendar with AI Small content teams 2x production without new hires
63 Map content to funnel stages Content portfolios needing balance 50%+ trial signup lift
64 Audit content performance Mature content libraries (500+) 30%+ organic traffic lift
65 Identify content gaps vs competitors Catch-up or parity SEO plays 20K+ monthly visits recaptured
66 Build evergreen content library Long-horizon content strategy Top-15 = 60%+ of organic traffic
67 Plan seasonal content campaigns Seasonal or cyclical businesses 50%+ lift in peak quarter
68 Create a content pillars framework When brand voice feels scattered Brand-voice clarity +30 points
69 Map formats to audience preferences Multi-generational audiences Engagement +25% from reallocation
70 Design content repurposing pipeline Teams with <3 content producers 3x output without new hires
71 Build an idea capture system Solo creators and consultants 2x content engagement
72 Create content brief template Agencies and high-volume teams 65%+ brief time savings
73 Assess content ROI per piece Teams investing heavily in content 40%+ pipeline lift
74 Plan UGC campaigns Consumer brands with visual product 5–10x ROAS on UGC campaigns
75 Build storytelling framework Content feeling bland or corporate 2x content time-on-page
76 Create content style guide Teams scaling content production 60%+ editorial time saved
77 Plan content distribution matrix High content quality, low reach 4x content views
78 Design controversial take content Thought-leadership focused roles 100K+ post reach for POV content
79 Build newsletter content strategy Building owned audience 40%+ open rates on winning concept
80 Map content to keyword clusters Mid-size content libraries 80%+ organic traffic YoY

Highlights — The Compounding Plays

Topic Cluster Strategy

One pillar topic, 10–15 spoke pages, dense interlinking. A B2B HR-tech team built one cluster around “employee retention” — within 6 months, ranked for 340+ keywords and grew the pillar from 0 to 48,000 monthly visits.

Audit Content Performance

Classify every page: keep / refresh / merge / prune. A publisher with 1,200 articles refreshed 60 flagged as high-potential — organic traffic grew 34% in 3 months with no new content.

Design Content Repurposing Pipeline

One quarterly hero asset → 15+ derivatives across channels. A B2B team produced one industry report per quarter and repurposed it 18 ways — output went from 4 LinkedIn posts/week to 14 without new headcount; pipeline grew 3.4x.

Design Controversial Take Content

Steel-man category orthodoxy, then publish your counter with evidence. A marketing-ops consultant published a contrarian post — 420K impressions, 18 inbound demos, 3 closed deals worth $140K in 30 days.

Frequently Asked Questions

Why is content volume no longer a winning strategy?

AI collapsed production cost to near zero. Every competitor can publish 20 posts a week now. Volume is a minimum, not a moat. What matters in 2026 is whether content has POV, evidence, and distribution — qualities AI alone cannot supply.

What’s the most underused content play?

Auditing existing content. Most mature libraries have 40–60% of pages worth refreshing but un-refreshed. Refresh ROI consistently beats new-content ROI for libraries over 200 articles.

How many topic clusters should a B2B blog run?

3–5 priority clusters at any time. More than that fragments authority; fewer than that limits topical breadth. Each cluster should have a pillar + 10–15 spokes with dense internal linking.

What’s the right ratio of new content vs refreshed content?

For mature blogs (500+ pages), spend 40–60% of content effort on refreshing high-potential existing pages. The math is brutal in favor of refresh — most teams under-allocate to it because new content feels more productive.

How do controversial takes drive results?

Bold POVs earn attention. AI commodity content is increasingly suppressed by algorithms; opinionated, evidence-backed contrarian takes get amplified. One controversial take can outperform 50 conventional posts on engagement and inbound.

Should content briefs be AI-drafted?

Yes — with a human-defined template. The brief is the highest-leverage 10 minutes in the entire content process. AI fills the brief; humans validate the strategic intent. Brief quality determines downstream content quality.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Riman Agency AEO 2E series — citation-friendly content patterns
  • Tools: Clearscope, Surfer, Frase, Notion, Airtable

Work With Riman Agency

Riman Agency installs content operating systems — clusters, calendars, repurposing pipelines, audit cadences. Get in touch for a 90-day program.

Part 4 of our 25-part 500 Ways AI Marketing series. Previous: Audience Research. Up next: Copywriting & Long-Form Content.

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Audience Research and Personas: 20 AI Plays for Sharper Customer Understanding

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Most personas gather dust. AI changes that. AI mines support tickets, reviews, calls, and reviews to build personas that update themselves. JTBD becomes a real working framework. Voice-of-customer libraries become searchable knowledge bases that every brief draws from. 20 practical moves for living, behavior-grounded audience understanding.

Key Takeaways

  • Generic personas underperform behavior-grounded ones by 3–5x on conversion and engagement.
  • Mining tickets and reviews surfaces real customer language — replace marketing-speak with verbatim phrasing.
  • Stated vs revealed preference analysis reveals when surveys lie. Trust behavior over statements.
  • Voice-of-customer libraries make every brief sharper. Force-multiplier for content teams.
  • Start with #41 (rich personas), #43 (mine tickets), and #44 (extract JTBD) for fastest impact.

The 20 practical moves (Quick Reference)

# Play Best when Expected result
41 Build rich personas from scraps Sales finds marketing content off-target MQL→SQL up 20–30%
42 Run synthetic customer interviews Pre-research hypothesis generation 3–4 weeks research time saved
43 Mine support tickets High-volume support operations 15–25% return reduction
44 Extract JTBD from reviews Product teams planning features 25–40% lift on targeted segments
45 Segment customers behaviorally Any recurring-revenue business Reactivation CAC 70–80% below acquisition
46 Map buyer journeys in 30 minutes Content teams planning quarters MoFu conversion 2–3x
47 Run social listening → action Consumer and prosumer brands Ride emerging trends early
48 Identify lookalike audiences with AI B2B paid targeting CAC 30–50% lower
49 Detect emerging customer trends Content/SEO-led growth Category thought-leadership
50 Run pricing sensitivity analysis Pricing review or repricing 5–15% net revenue per visitor
51 Build an ICP scorecard Sales-marketing alignment 3x close rate on top-scored leads
52 Analyze churn reasons from exit surveys Subscription/membership businesses 15–20% churn reduction
53 Map the problem-awareness ladder ToFu content expansion 3x top-funnel capture
54 Research decision committees (B2B) Enterprise B2B deals 20%+ win rate lift
55 Analyze review site trends over time Review-driven categories Detect perception drops in <30 days
56 Build a voice-of-customer library Any content-producing team 30–40% ad copy CTR lift
57 Stated vs revealed preference analysis Consumer DTC decisions 15–25% conversion lift from truth
58 Map cultural and generational shifts Long-cycle consumer brands 60%+ email engagement lift
59 Audit audience across platforms Multi-channel marketing teams 40%+ channel ROI lift
60 Build empathy maps at scale Agencies and creative teams 50%+ fewer brief rewrites

Highlights — The Plays Most Teams Should Run First

Mine Support Tickets

Export 90 days of tickets. Cluster by theme with verbatim quotes. A DTC apparel brand mined 2,000 tickets and discovered “is this true to size?” was the top theme — adding sizing clarity and a fit-finder dropped returns 18%, saving ~$340K annually.

Extract JTBD from Reviews

Scrape 50–200 reviews (yours + competitors’). Extract jobs in “When ___, I want to ___, so ___” format. A fitness app discovered “when I’m traveling I want a consistent routine” — launched travel mode; in-app purchases from travelers grew 38%.

Build a Voice-of-Customer Library

Centralize calls, tickets, reviews, social into a searchable RAG-enabled database. Use in every content brief. One brand swapped a marketing phrase for a verbatim customer quote — CTR lifted 41%.

Stated vs Revealed Preference Analysis

Compare what customers say (surveys) with what they do (behavior). One DTC brand’s survey said sustainability was top priority; behavior data said price was 8x more impactful. Simplifying to price+quality lifted conversion 22%.

Frequently Asked Questions

Why do most personas underperform?

They’re built from gut, not data. Real audience understanding requires specificity built from behavior, not demographics. AI mining of tickets, reviews, and calls produces personas sales actually use — adoption typically jumps from 10–20% to 80%+.

What’s the difference between stated and revealed preference?

Stated = what customers say in surveys. Revealed = what they actually do. They often diverge. Survey says “I value sustainability”; purchase data says price wins 8 of 10 times. Trust behavior over statements when they conflict.

How is JTBD different from personas?

Personas describe who; JTBD describes the job they’re hiring your product to do. The format “When ___, I want to ___, so ___” focuses on the situation and outcome. Both are useful — JTBD often reveals product opportunities personas miss.

What’s the highest-leverage audience research play?

Building a voice-of-customer library — it’s a force-multiplier for every other content team activity. Briefs get sharper, copy gets more authentic, ads perform better. The compounding effect over 12 months is enormous.

Should I segment by demographics or behavior?

Behavior wins for most marketing decisions. Demographics tell you who; behavior tells you what they’ll do. AI makes behavioral segmentation finally affordable — ditch demographic-only segmentation if you’re not in a regulated targeting context.

How often should personas be updated?

Continuously. AI-driven personas update as new tickets and reviews flow in. Static documents update once and rot. The shift to living personas is one of the highest-ROI process changes a content/PMM team can make in 2026.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Clayton Christensen — Competing Against Luck (JTBD framework)
  • Indi Young — Practical Empathy (deep audience research)

Work With Riman Agency

Riman Agency builds living persona systems and voice-of-customer libraries. Get in touch for a 30-day audience-research sprint.

Part 3 of our 25-part 500 Ways AI Marketing series. Previous: Market Research. Up next: Content Strategy & Planning.

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Market Research and Competitive Intelligence: 20 AI Plays for Real-Time Insight

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Quarterly market research is a relic. Your competitors are operating on real-time intelligence — and if you aren’t, you’re fighting blind. AI agents can monitor every signal competitors emit publicly: blog posts, pricing changes, job postings, ad library entries, review sentiment shifts, press releases, patent filings. Tools that cost $50K/year five years ago are now under $500/month. 20 practical moves for continuous market and competitive intelligence.

Key Takeaways

  • Quarterly market research is strategic malpractice in 2026. Continuous intelligence is the new baseline.
  • Job postings, pricing pages, and review sentiment shift weeks before press releases.
  • Bottom-up market sizing replaces $40K consulting engagements — defensible numbers in hours.
  • Whitespace mapping and trend forecasting unlock first-mover advantage in adjacent categories.
  • Start with #21 (automated competitor monitoring) and #25 (job post signals) — they build the always-on foundation.

20 Practical Moves at a Glance

#21 — Automated Competitor Monitoring

Always-on AI agent watching 3–5 competitors weekly. Format as Slack digest with so-what. Result: 1–3 competitive wins/quarter from earlier intel.

#22 — Track Competitor Pricing Continuously

Pricing changes signal strategy shifts. Visualping or custom scraping; review monthly. Result: Pre-empt pricing plays.

#23 — Analyze Competitor Ads Library

Cluster Meta/Google/LinkedIn ads by hook, visual, offer. Test counter-creative against their top angle. Result: 30–50% lower CPA possible.

#24 — Track Competitor Content Cadence

Frequency reveals priority. Spot acceleration or pivots. Result: Rank ahead of competitor pivots.

#25 — Monitor Competitor Job Posts for Signals

Hiring reveals strategy before press releases. Cluster by function, infer priorities. Result: 3–6 month strategic lead.

#26 — Analyze Competitor SEO Footprint

Cluster their ranking keywords by topic. Find authority areas vs gaps. Result: 40+ new page-1 rankings.

#27 — Review Competitor Customer Complaints

G2/TrustPilot complaints are your positioning opportunities. Map each to your strength. Result: 2–3x conversion on comparison pages.

#28 — Map Competitor Partnership Networks

Their partners reveal strategic anchors. Find whitespace. Result: Own uncontested territory.

#29 — Track Competitor Event Presence

Conferences signal audience priorities. Compete or avoid. Result: Find 3–5x ROI events.

#30 — Analyze Competitor Product Launches

Launch themes telegraph roadmap. Predict next 3 launches. Result: Out-ship competitor launches.

#31 — Research Market Size with AI

TAM/SAM/SOM bottom-up + top-down with cited assumptions. Result: $40K+ consulting fees saved.

#32 — Identify Emerging Market Segments

Find pockets before they’re obvious from your customer data + category trends. Result: 6–12 month first-mover advantage.

#33 — Monitor Regulatory Changes

Regulation creates risk and opportunity. Weekly digest with marketing implications. Result: Avoid compliance crises.

#34 — Track Industry Analyst Coverage

Gartner/Forrester/IDC coverage of your category. Result: Enter analyst reports earlier.

#35 — Analyze Investment and M&A Signals

Money moves before strategy. Spot patterns in funding/M&A. Result: Pivot before price wars hit.

#36 — Map Whitespace Opportunities

Plot competitors on two axes that matter. Find empty quadrants. Result: Uncontested market position.

#37 — Run Category Trend Forecasting

Synthesize analyst, social, search signals into 10 predictions. Result: Content that ages well.

#38 — Identify Adjacent Categories to Enter

From your capabilities, find 10 adjacent markets with fit/size/cost scores. Result: 15–25% revenue from adjacencies.

#39 — Build a Bottom-Up Market Model

Real numbers: customer count × ARPA × penetration with stress-tested assumptions. Result: Defensible numbers in hours.

#40 — Monitor Patent Filings for Innovation Signals

Patents predict product roadmaps. Spot unusual cluster filings. Result: 12–24 month innovation lead.

At a Glance — Market Research & Competitive Intelligence

# Play Best when Expected result
21 Run automated competitor monitoring Category with 3+ close competitors 1–3 wins/quarter from earlier intel
22 Track competitor pricing continuously SaaS and subscription businesses Pre-empt competitor pricing plays
23 Analyze competitor ads library When competitors are paid-active 30–50% lower CPA possible
24 Track competitor content cadence Content-led competitive moats Rank ahead of competitor pivots
25 Monitor competitor job posts B2B with known competitor set 3–6 month strategic lead
26 Analyze competitor SEO footprint SEO-led growth motion 40+ new page-1 rankings
27 Review competitor customer complaints Review-rich categories (SaaS, DTC) 2–3x conversion on comparison pages
28 Map competitor partnership networks Partnership-led growth strategies Own uncontested territory
29 Track competitor event presence Events-heavy industries Find 3–5x ROI events
30 Analyze competitor product launches Product-led B2B Out-ship competitor launches
31 Research market size with AI Fundraising or board presentations $40K+ consulting fees saved
32 Identify emerging market segments Any growing or adjacent category 6–12 month first-mover advantage
33 Monitor regulatory changes Regulated industries Avoid compliance crises
34 Track industry analyst coverage Enterprise or mid-market B2B Enter analyst reports earlier
35 Analyze investment and M&A signals Funded/competitive categories Pivot before price wars hit
36 Map whitespace opportunities Crowded categories needing positioning Uncontested market position
37 Run category trend forecasting Content and editorial planning Content that ages well
38 Identify adjacent categories to enter Core market saturation 15–25% revenue from adjacencies
39 Build a bottom-up market model Board/investor conversations Defensible numbers in hours
40 Monitor patent filings Patent-heavy industries 12–24 month innovation lead

Frequently Asked Questions

Is automated competitor monitoring worth it for small teams?

Yes — especially for small teams. The main cost was always headcount; AI cuts that to ~$200/month in tooling. A single PMM with the right monitoring catches more competitive signals than a 5-person research team did in 2019.

Can AI really replace consulting-firm market sizing?

For most decisions, yes. Bottom-up models with cited assumptions and stress-tested sensitivity analysis are defensible enough for board and investor conversations. The remaining 5% (genuinely novel categories, complex regulatory contexts) still benefit from specialist consultants.

Why are competitor job posts so valuable?

Hiring reveals strategy 3–6 months before press releases. A competitor posting 7 API engineer roles is signaling an API product. A competitor hiring in LATAM is signaling regional expansion. Job-post monitoring is the highest-leverage public-signal source most teams ignore.

How often should I run market research now?

Continuously, not quarterly. With AI agents handling monitoring, the marginal cost of always-on intelligence is low. Static “annual market reports” are increasingly stale by the time they’re delivered.

What’s the most common competitive-intel mistake?

Reading without acting. Most intel goes into reports nobody uses. Build a 20-minute Monday standup ritual where the digest is reviewed and one action is decided — that’s where the value lives.

How do I find whitespace in a crowded category?

Plot competitors on two axes that matter to your buyers. Empty quadrants are your candidates. Test the most promising with a 90-day pilot before committing budget.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Tools: Crayon, Klue, Perplexity Spaces, Visualping, Apify
  • Patent search: Google Patents, USPTO, EPO

Work With Riman Agency

Riman Agency stands up always-on competitive intelligence systems. Get in touch for a 30-day intel-program install.

Part 2 of our 25-part 500 Ways AI Marketing series. Previous: Strategy & Planning Foundations. Up next: Audience Research & Personas.

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Strategy and Planning Foundations: 20 AI Plays for Modern Marketing Teams

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In a world where execution has been commoditized by AI, strategy is the only defensible asset left. AI compresses strategic work that used to take weeks into hours — competitor research, scenario planning, positioning stress-tests, SWOT analysis. The plays in this chapter make sure you’re amplifying the right things, not just amplifying faster. Twenty concrete plays across briefs, OKRs, positioning, intel, prioritization, planning, pre-mortems, and team workflow audits.

Key Takeaways

  • The execution gap closed in 2026. Strong strategy amplified by AI is the moat; weak strategy amplified is just faster failure.
  • Strategy becomes a living practice, not an annual offsite — pressure-tested weekly, updated quarterly.
  • Senior strategic thinking is no longer gated by experience alone — AI gives any marketer access to consultancy-grade frameworks.
  • Start with brief, OKRs, and 90-day plan if you’re rebuilding. Use #2, #6, #11 to sharpen positioning.
  • Don’t implement all 500 ways. Pick 15. Then 15 more. That is how real change compounds.

20 Practical Moves at a Glance

#1 — Build an AI-Powered Strategic Brief

Turn fuzzy requests into structured briefs with SMART objectives, audience, channel mix, KPIs, and risks. Prompt: “Act as a senior strategist. From this context, produce a one-page brief with SMART objective, audience, core message, 3-channel mix, KPIs, and top 3 risks.” Typical result: 70–80% time savings on briefs.

#2 — Run an Evidence-Based SWOT

Replace opinion-based SWOT with one grounded in your data + competitor positioning + cited evidence. Typical result: Consultancy-grade SWOT in under 2 hours.

#3 — Generate Three 2026 Scenarios

Define three variables (budget, AI-search adoption, competitor aggression). Build a scenario per combination. Identify the bets robust across all three. Typical result: Plan robust to multiple futures, 1–2 strategic reallocations per cycle.

#4 — Map Your Marketing Moat

Map assets to Hamilton Helmer’s 7 Powers. Rate each as defensible, copyable, or commodity. Cut commodity spend; compound defensible. Typical result: 3x organic lead lift possible from refunding the moat.

#5 — Translate Business Goals to Marketing OKRs

Convert revenue targets into measurable marketing objectives with KRs. Cut anything you cannot actually measure. Typical result: OKRs approved on first review.

#6 — Pressure-Test Your Positioning

Have AI role-play three buyer personas and critique your positioning. Generate sharper alternatives. A/B test the top two. Typical result: 40–60% conversion lift possible from sharper positioning.

#7 — Build a Competitor Intel System

Replace one-off competitor decks with a Monday morning AI-generated digest covering blog, social, product, pricing changes. Typical result: 2–4 competitor-driven deal saves per quarter.

#8 — Prioritize Channels with an AI Matrix

Score every active channel on reach, fit, cost, and time-to-results. Cut the bottom third for 90 days. Typical result: 20–30% pipeline lift from reallocation.

#9 — Write a 90-Day Plan in One Afternoon

Go from blank page to capacity-checked, owner-assigned shippable plan in hours. Typical result: 2–3 weeks saved on planning; plan approved same week.

#10 — Run a Pre-Mortem on Every Launch

Have AI imagine the launch failing 3 months out. Generate 10 failure modes ranked by likelihood. Fix the top 3 before shipping. Typical result: 50–70% reduction in launch-related support tickets.

#11 — Develop a Category Point of View

Pressure-test your category beliefs. Pick one as your category POV. Publish it repeatedly across channels. Typical result: 2–3x inbound from POV content over 6 months.

#12 — Audit Your Marketing Tech Stack

Identify overlapping capabilities + low-usage tools. Consolidate or cancel. Typical result: 15–35% stack cost savings.

#13 — Build an AI-Readiness Assessment

Score capabilities across data, tools, skills, governance. Invest in the lowest-scoring layer first (often data, not tools). Typical result: Right investment sequence; 4x agent accuracy when data is fixed first.

#14 — Map Your Strategic Narrative Arc

Plan the year as a story (4 quarterly chapters), not a calendar. Align every campaign to one chapter. Typical result: 2x brand recall.

#15 — Define a Marketing North-Star Metric

Pick one stable, hard-to-game metric (often Qualified Pipeline Created). Review weekly. Typical result: Pipeline quality lift of 30–50%.

#16 — Forecast Competitor Responses

Before any move, predict each competitor’s likely response and plan counter-moves. Typical result: Competitor matches neutralized; market position preserved.

#17 — Build a Decision Journal

Log every major decision with options, rationale, prediction, review date. Quarterly review reveals systematic biases. Typical result: 20–30% better decision hit-rate over 12+ months.

#18 — Generate Quarterly Bets from Data

Turn the quarter’s strongest signals into 10 specific bets with budget and success criteria. Pick top 5. Typical result: ~20% CAC reduction from data-driven bet selection.

#19 — Design a Marketing Experiment Roadmap

Continuous testing program, not ad-hoc. One high-impact test per week prioritized by impact/effort. Typical result: 4x testing velocity, ~4x more wins per year.

#20 — Audit Team Workflows for AI Opportunity

Log team tasks for one week. Identify >5 hrs/week repetitive tasks. Pilot automation on one. Typical result: 40–60 hours/month reclaimed across a small team.

At a Glance — Strategy & Planning Plays

# Play Best when Expected result
1 Build an AI-powered strategic brief Launching any new campaign 70–80% faster briefs
2 Run an evidence-based SWOT Annual planning or repositioning Consultant-grade SWOT in 2 hrs
3 Generate three 2026 scenarios Before annual or board planning Plan robust to 3 futures
4 Map your marketing moat Long-term investment planning 3x organic lead lift possible
5 Translate business goals to OKRs Quarterly or annual planning OKRs approved in one review
6 Pressure-test your positioning Before or after any launch 40–60% conversion lift possible
7 Build a competitor intel system Fast-moving competitive categories No more launch blindsides
8 Prioritize channels with AI matrix Stretched across too many channels 20–30% pipeline lift
9 Write a 90-day plan in one afternoon New role or quarter kickoff Plan approved same week
10 Run a pre-mortem on every launch Before every major launch 50–70% support ticket reduction
11 Develop a category point of view Building thought leadership 2–3x inbound from POV content
12 Audit your marketing tech stack Annual budget review or M&A 15–35% stack cost savings
13 Build an AI-readiness assessment Before investing in AI tooling Invest in the right layer first
14 Map your strategic narrative arc Annual content strategy planning 2x brand recall
15 Define a marketing north-star metric Marketing-sales trust strained Pipeline quality lift 30–50%
16 Forecast competitor responses Before pricing or positioning move Competitor match neutralized
17 Build a decision journal Executive and senior leader use 20–30% better decision hit-rate
18 Generate quarterly bets from data Quarterly planning cycles ~20% CAC reduction
19 Design a marketing experiment roadmap Growth and CRO teams 4x testing velocity
20 Audit team workflows for AI opportunity Any 5+ person marketing team 40–60 hrs/month reclaimed

Frequently Asked Questions

Why does strategy matter more in 2026?

Because AI collapsed the cost of execution to near zero. Any team can produce 50 ad variants overnight or draft a 4,000-word pillar in an hour. Your competitors can too. The execution gap closed; the only remaining differentiator is strategy — which audience, which message, which channels, which bets.

What changed about strategic work itself?

AI compresses competitor research, scenario planning, positioning stress-tests, and SWOT analysis from weeks to hours. Work that justified $25K–$100K consulting engagements is now achievable by a single marketer with the right prompts. Strategy becomes continuous instead of annual.

Where should I start if I’m rebuilding strategic practice from scratch?

Plays #1 (strategic brief), #5 (OKRs), and #9 (90-day plan). They give you the operational scaffolding the rest of the plays sit on top of.

How do I prevent AI from amplifying weak strategy?

Pressure-test before you ship. Plays #2 (SWOT), #3 (three scenarios), #6 (positioning pressure-test), and #10 (pre-mortem) are designed exactly for this. Catch weakness in the planning phase, not the launch phase.

What’s the most common AI strategy mistake?

Implementing too many plays at once. Pick 15 over the next year, run them well, then pick the next 15. Real change compounds; scattered effort doesn’t.

Should I rebuild strategy annually or continuously?

Continuously. Strategy in 2026 is a living practice — pressure-tested weekly, updated quarterly. Annual offsite documents are increasingly stale by the time they’re approved. Teams treating strategy as continuous outcompete teams treating it as yearly.

Sources & Further Reading

  • Tarek Riman — 500 Ways to Use AI for Your Marketing Strategy in 2026
  • Hamilton Helmer — 7 Powers (moat framework)
  • Riman Agency AEO 2E series

Work With Riman Agency

Riman Agency builds AI-powered strategic operating systems for marketing teams — briefs, OKRs, intel, scoring, planning. Get in touch if you want to install three plays in 30 days.

Part 1 of our 25-part series adapted from 500 Ways to Use AI for Your Marketing Strategy in 2026 by Tarek Riman. Up next: Market Research & Competitive Intelligence.

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GEO — Generative Engine Optimization for Bloggers

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AEO is about being cited in answers. GEO is about being mentioned by name when no question is asked at all. GEO (Generative Engine Optimization) is the practice of becoming a brand or source that AI models name and recommend in their generated outputs — even without a citation. Three levers move GEO: brand entity strength, training-data presence, and structural prominence in your niche. GEO works on a multi-quarter timeline. It rewards consistency and original distinctive content over volume.

Key Takeaways

  • GEO is being mentioned in AI answers, not just cited as a source.
  • Three levers: Brand Entity Strength, Training-Data Presence, Structural Prominence.
  • Cross-surface participation — Reddit, podcasts, press, video — beats blog-only effort for GEO.
  • Name your frameworks. Publish original data. Be a recognized entity.
  • GEO is a 2–3 year compounding play. Start now; check progress quarterly.

GEO vs. AEO — What’s the Difference?

AEO is what gets you cited as a source in an AI answer. GEO is what gets you mentioned by name in the AI’s answer — sometimes with a link, sometimes without, sometimes as a recommendation, sometimes as an example.

Scenario What’s happening Discipline
A user asks ‘how does pricing work’ and the AI cites your post You’re cited as the source AEO
A user asks ‘best B2B pricing consultants’ and the AI lists you You’re named in the answer itself GEO
A user asks ‘explain SaaS pricing’ and the AI explains it your way Your framework is in the model’s knowledge GEO
A user asks ‘who writes about pricing’ and you’re mentioned You’re a recognized entity in the niche GEO

Smart Tip: AEO gets you traffic and citations today. GEO gets you brand recognition and inbound demand over the next 2–3 years — invest in both.

How AI Models Form Their ‘Knowledge’

Generative AI models develop a kind of default world knowledge from their training data. When they answer questions where they’re not retrieving live sources, they pull from this internal model. GEO is about influencing what’s in there.

Three inputs shape an AI model’s default knowledge of your niche:

  1. Training data — the public web, books, papers, forums, code, and licensed content the model was trained on.
  2. Live retrieval — in search-enabled chat, the model fetches live sources at query time.
  3. Reinforcement — patterns of what users accept, what gets fed back into training, and what gets cited in retrieved answers.

Myth Buster — Myth: I can submit my site directly to AI training datasets.
Reality: Mostly no. You can’t submit a feed to OpenAI or Anthropic. What you can do is be highly visible and cited across the public web — which is where the next generation of training data comes from.

The Three GEO Levers

Lever What it means How to move it
Brand Entity Strength AI engines recognize you as a real, distinct entity in your niche Wikipedia/Wikidata, consistent author bios, schema, podcast/press mentions
Training-Data Presence Your content shows up across the open web in places models train on Distribution: Reddit, Stack Exchange, Quora, GitHub, news, podcasts, YouTube
Structural Prominence Your content is the canonical or best example of something Original frameworks, named methods, original research with public datasets

Lever 1 — Brand Entity Strength

AI engines build entity graphs — maps of who’s who, what’s what, and how they relate. Six concrete moves:

  1. Get a Wikipedia article (notability required — don’t fake it). If not Wikipedia, then Wikidata.
  2. Maintain a consistent author bio across your blog, guest posts, social profiles, podcast pages, and About sections.
  3. Use Person and Organization schema with sameAs properties linking your site, social profiles, and external mentions.
  4. Get cited or interviewed in tier-1 publications in your niche.
  5. Maintain a LinkedIn presence with consistent description and a clear About section.
  6. Be a guest on niche podcasts. Transcripts become training data; the brand mention compounds.

Smart Fun Fact: AI engines treat ‘people who get interviewed in their niche’ as more authoritative than ‘people who only publish on their own site.’ Cross-site mentions are how entity recognition is bootstrapped.

Lever 2 — Training-Data Presence

Surface Why it matters How to participate
Reddit Heavily used in AI training; pulls into Google AI Overviews Genuine niche subreddit participation — not link-drops
Stack Exchange / GitHub Specific to technical niches; high-trust Answer questions; contribute to open source
YouTube Transcripts are training data; videos surface in AI answers Even modest YouTube presence compounds
Podcasts Transcripts make their way into training pipelines Be a guest; host if you can sustain it
News and trade publications Tier-1 sources weighted heavily Digital PR, original data hooks, expert quotes

Smart Tip: Spend one hour a week on Reddit in your niche — not promoting, just genuinely answering questions. Within 6 months, you’ll show up in AI Overviews via Reddit pages. It’s the highest-leverage hour you can spend.

Lever 3 — Structural Prominence

Models name things they have a clean, distinct concept for. If your content invents or owns a named framework, method, or term in your niche, models eventually attach your name to it.

  • Name your frameworks. Give specific methods specific labels (‘the X method,’ ‘the Y framework’).
  • Publish original research with a public dataset — a small benchmark or survey is enough.
  • Create canonical reference content — the post that becomes ‘the’ explainer for a topic.
  • Be early to define new categories. The first credible thinker on a new topic owns it for years.
  • Build a glossary or taxonomy on your blog. Engines cite well-organized definitional content disproportionately.

Measuring GEO

GEO measurement is more qualitative and longer-term than AEO. Three things to track:

  • Mention rate — in tracked AI engines, how often does your name appear in answers without a citation? Test 25 queries monthly.
  • Branded search volume — the trend line in Search Console for queries containing your name.
  • Inbound ‘where did you hear about us’ attribution — ask new email subscribers, customers, or leads how they found you.

Common Mistakes

  1. Treating GEO as something you do this quarter — it’s a 2–3 year compounding play.
  2. Trying to game training data — AI labs detect spammy patterns. Real participation in real communities is the only durable strategy.
  3. Building only on your own blog — your domain is one signal among hundreds. Cross-surface presence is the moat.
  4. Skipping Wikipedia / Wikidata when notability is real — it’s the highest-leverage entity move available.
  5. Naming a framework you can’t actually defend — the framework has to be useful enough that other people use the name too.

90-Day GEO Build

  1. Days 1–10 — Audit your entity strength: author page, schema, sameAs links, consistency across profiles. Fix gaps.
  2. Days 11–20 — Identify three off-blog surfaces to participate on regularly.
  3. Days 21–40 — Establish weekly cadence on those three surfaces. Genuine contributions, not promotion.
  4. Days 41–60 — Pitch one tier-1 publication and three niche podcasts.
  5. Days 61–75 — Identify one named framework or original analysis you can publish.
  6. Days 76–90 — Set up baseline tracking: branded search trend, AI engine mention check, inbound attribution.

Frequently Asked Questions

What’s the difference between AEO and GEO?

AEO is being cited as a source inside an AI answer. GEO is being named or recommended inside the AI’s answer — sometimes without a link. AEO is short-term traffic; GEO is long-term brand recognition.

What are the three GEO levers?

Brand Entity Strength (Wikipedia, schema, consistent bios), Training-Data Presence (Reddit, podcasts, YouTube, press), and Structural Prominence (named frameworks, original data, canonical reference content).

Can I directly submit my site to AI training data?

No — major AI labs don’t accept direct submissions. The path to training data is being highly visible and cited across public surfaces (Reddit, YouTube transcripts, news, podcasts) that get included in the next round of training.

Why does Reddit matter so much for GEO?

Reddit content is heavily used in AI training and pulls directly into Google AI Overviews. One hour per week of genuine niche subreddit participation typically produces AI Overview mentions within 6 months.

How long does GEO take to show results?

2–3 years for full compounding. You’ll see early signals (branded search lift, AI mention rate) at 6–12 months. The real recommendations-without-citations effect typically appears at 18–36 months.

How do I measure GEO?

Three signals: mention rate in AI engines on niche queries (test 25 queries monthly), branded search trend in Search Console, and inbound attribution from new subscribers (“where did you hear about us”). “ChatGPT recommended you” is now a real answer.

Sources & Further Reading

  • Aggarwal, P. et al. — “GEO: Generative Engine Optimization” (arXiv:2311.09735)
  • Riman Agency AEO 2E series
  • OpenAI, Anthropic — official documentation on training data sources

Work With Riman Agency

Riman Agency builds GEO programs that compound over years — entity strength, cross-surface presence, structural prominence. Get in touch for a 90-day GEO build.

Part 9 of our 16-part Blogger Guideline series. Previous: AEO for Bloggers. Up next: Keyword Research, Topical Authority & Linking.

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