# Plan your next seasonal promotion from last season’s evidence. When demand peaks and what competitors offered A seasonal promo plan times your offer to demand and positions it against what competitors did last year. With Agentik, your AI reads five years of Google Trends with DataForSEO, finds and reads competitors’ pages from last season with the Wayback Machine and Firecrawl, and reads their promotion ads with Adspy.sh. - For: E-commerce and retail marketers - Providers: 4 (DataForSEO, Internet Archive, Firecrawl and Adspy.sh), 4 tools - Example (Five years of Google Trends for 5 terms, 6 archived pages found and read, Black Friday ads from 3 competitors): at most $0.11, computed from the live catalog - Updated: 2026-10-10 ## Each provider does one part No single provider covers this job. Through Agentik your AI calls each one for its part, from one connection and one prepaid balance. - **DataForSEO** (1 tool, at most $0.04): Five years of Google Trends, to time the peak. - **Internet Archive** (1 tool, free): Competitors’ pages as they were last season, from the Internet Archive. - **Firecrawl** (1 tool, at most $0.02): Those archived pages as text: offers, thresholds and wording. - **Adspy.sh** (1 tool, at most $0.06): Competitors’ promotion ads from Meta and Google. ## Give this to your agent ```text Use my connected Agentik MCP server for this job: seasonal promo plan. Plan my next seasonal promotion. First ask me for my category, the season (for example Black Friday), my country and three competitors. Read five years of demand with dataforseo/google-trends. Find competitors’ home and promo pages from last season with wayback/availability and read them with firecrawl/scrape. Find their promotion ads with adspy/search-creatives. Finish with the demand curve and peak dates, what each competitor offered and when, and a calendar for my promotion (dates, offer, channels, creative angles). Before running anything, inspect each tool with inspect_tool, ask me for any input you don’t have instead of inventing it, and tell me the total price. Wait for my go. At the end, tell me what Agentik charged. ``` ## You provide - Your category - The season - Country - Three competitors ## What you get: a dated promotion calendar - The demand curve and peak dates - What competitors offered last season, and when - Their promotion ads - A dated promo calendar for you ## How to plan a seasonal promotion in Claude or ChatGPT Prices are the most each call can reserve for this example: Five years of Google Trends for 5 terms, 6 archived pages found and read, Black Friday ads from 3 competitors. ### 1. Time the demand Google Trends over five years shows when demand for your category rises and peaks. - [Google Trends interest over time and by region](/tools/dataforseo/google-trends.md) `dataforseo/google-trends` (DataForSEO, 5 terms): at most $0.04 ### 2. Read last season’s offers The Wayback Machine finds competitors’ home and promotion pages from last season, and Firecrawl reads them. - [Wayback Machine snapshot lookup](/tools/wayback/availability.md) `wayback/availability` (Internet Archive, 6 pages): free - [Scrape a web page to markdown](/tools/firecrawl/scrape.md) `firecrawl/scrape` (Firecrawl, 6 archived pages): at most $0.02 ### 3. Read their promotion ads Adspy.sh finds the promotion ads your three competitors ran. - [Search ad creatives on Meta, Google and TikTok](/tools/adspy/search-creatives.md) `adspy/search-creatives` (Adspy.sh, 30 ads): at most $0.06 ### 4. Build the calendar Your AI writes the calendar with dates, offers, channels and creative angles. Example total: at most $0.11. Each call is billed for measured usage; unused reservations are released. ## Ask it your way - When should I start my Black Friday promotion for air fryers? - What did my competitors offer last Black Friday? - Which promotion ads did my competitors run last season? - Plan my holiday promotion calendar from last year’s evidence. ## Why through Agentik - Trends, archived pages and competitors’ ads come from four providers through one connection. - The archive is free; the whole example costs about ten cents. ## Good to know - The archive keeps pages it happened to crawl; some days may be missing. - Ad dates show when Adspy observed an ad, not its whole schedule. ## When to use something else For promotion management and discount codes in your store, use your e-commerce platform. This playbook decides when and what to offer, from last season’s evidence. ## Seasonal promo plan: questions ### What if the archive missed a page? The Wayback Machine keeps the pages it crawled; your agent takes the nearest copy and says so. ### Does it work for any season? Yes: Black Friday, back to school, summer sales or a local holiday. Your agent asks for the dates. ### What does the example cost? At most $0.11, reserved before each call and settled at the measured usage. ## Keep going - [Competitor ad research](/competitor-ad-research.md): Their longest-running Meta and Google ads, why they work, where they send people, and how those offers changed. - [Competitor price check](/competitor-price-check.md): Every seller of your products on Google Shopping and Amazon with today’s price, competitors’ shipping and promotions read on their own pages, and the coupon codes in circulation. - [Monthly business review](/monthly-business-review.md): Last month across your ad accounts, GA4 and Search Console, explained with what happened outside them: category demand, competitors’ ad activity and the news. - [E-commerce tools for your agent](/tools/ecommerce.md) - [Advertising tools for your agent](/tools/advertising.md) - [SEO tools for your agent](/tools/seo.md) [All playbooks](/playbooks.md) · [Connection guides](/docs/clients.md) · [Billing](/docs/billing.md) --- [HTML page](/seasonal-promo-plan) · [Agent index](/llms.txt)