Goldman's Nails. Part 5.

Working with GSCs and Intents (Transactional Intents).

Transactional intents - requests where the user is ready to take an action (purchase, registration, download), often at the BOFU stage of the funnel. By Broder Classification (2002) and 2025 updates, they are 10-20% searches, with high conversion rates (5-15%) focusing on actions. In SEO, they are critical for commercial sites, where tokens (buy, buy) signal readiness for a transaction.

The patterns in GSC help filter such queries to optimize lendings, forms and CTAs, increasing ROI by 20-50%.

English version:

(?i)b(buy|purchase|order|shop|book|reserve|download|sign up|register|subscribe|join|apply|free trial|trial|demo|quote|pricing|price|cost|cheap|discount|coupon|promo|sale|sale|get|obtaintaintain|acquire|acrent|hire|book now|reserve now|add to cart|checkout|pay|payment|invoice|bill|receipt|refund|return|exchange|warranty|guarantee|shipping|delivery|pickup|in store|online|deal|offer|bargain|clearance|sale price|best price|lowest price|limited time offer|flash sale|bundle|package|subscription|membership|enroll|sign in for|access|unlock|upgrade|renew)b

Russian version:

(?i)b(buy|order|add to order|to order|skip|register|refund|return|order|add to cart|free|delivery|delivery|delivery|withdrawal|withdrawal|refundable|cost|charge|free shipping|receive|rental|reserve|booking|subscription|subscription|trial|subscription|prescription|trial|complete|pocket|access|access|unlock|upgrade|renew|extend)b

Expand and supplement independently. I left the endings in the Russian version of the query alone. You can fix it.

Next, export the queries from GSC and shove them into LLM

Prompts:

Baseline for classification:

«Classify these requests [list from GSC] into transactional intent subtypes: ‘buy’ (buy/order), ‘sign up/subscribe’ (sign up/subscribe), ‘download/demo’ (download/trial), ‘book/apply’ (book/apply); for each, suggest 3 page optimization ideas (CTAs, forms).»

For data processing:

«Clean and group transactional queries [CSV list] by subtype, remove duplicates, calculate average CTR/conversions; derive top 10 by sales potential.»

Expanded with analysis:

«Analyze [list] requests for transactional intent, categorize by subtype, account for seasonality (e.g., ‘Black Friday 2025’); propose A/B tests of CTAs and landing pages.»

For a Russian:

«Classify Russian queries [list] by transactional intent: ‘purchase’, ‘registration’, ‘download’; add examples of optimization in Russian (buttons, forms).»

Utilization Scenarios:

• Direct Purchase Landings: Patterns reveal «buy iPhone» for shopping cart pages.
• Registration/subscription forms: For «sign up free trial» - modal forms.
• PPC campaigns with low CPC: Targeting transactional for ads.
• Optimize cart and payment: For «add to cart» to simplify the process.
• Lead generation on infosites: Transactional in form guides.
• Remarketing and email
• Local services with reservations
• Downloads and demos
• Promotions and discounts: For «promo code» - sales pages.
• A/B testing of CTAs: Button tests for patterns.

et cetera

Transactional intents yield low traffic volume (10-20%) but high conversions. Patterns increase ROI by 20-50%. Based on case studies, traffic impact: +10-30% qualified.

Overall evaluation of pattern usage: 10-25% sales growth!!!

Impact on case study ranking: +5-15 positions due to relevance.