Affiliate Hub/Center Traffic Hub/Center Click Hub/Center

Place that all offers meets from various affiliate networks

campaigns // id, currency_id campaigns_pixels campaigns_languages campaigns_countries campaigns_sources // id, campaign_id, source_id, payment campaigns_networks campaigns_payouts // id, campaign_id, default_payout, payout_type

payouts // id, title, pp1, pp2, pp3

sources

networks networks_offers offers

roles permissions roles_permissions

users users_clicks users_offers users_networks users_sources

currencies

conversions // id, campaign_id, hash

targeting // id, user_id, default_campaign_id

targeting_campaigns // id, targeting_id, weight targeting_countries

// Sale pixel http://3213(campaignId).t.clickroyale.io/conversion?hash=323&payout=232&

Affiliate Advertiser Master

Affiliates Advertisers advertisers_affiliates Affiliate -> Request to join advertiser {ADVNAME} affiliate network -> Advertiser -> Pending Affiliates

Advertiser -> Invite affiliate {AFFNAME} to your affiliate network -> Affiliate -> You receive an invite from {ADVANME} to join his affiliate network

Pay after you earn! you only pay AFTER you earn, the price is fixed per clicks

a Place where affiliate and advertisers meet.

(?) How to attract advertisers?

• Upsell tools such as Email/Push Notifications (?)
• Full analytic and invoices system
• Geo targeting / Split AB Testing to offers and landers

Social network for affiliates, advertisers and between a must have system for anyone who works with internet marketing

Business Plan

• Pay per click (1m, 5m, 20m, 50m, 50m+) ** Price slider for custom clicks plan

• Free for first 6 months, No credit required
• Plan for 10/20/50+ affiliates
• Plan for basic/Premium/Business
• Google Optimizer - like system (Click Hub Optimizer) that will allow ab testing of replacing texts

users users_networks // id, network_id, np1, np2, np3 users_sources // id, source_id, sp1, sp2, sp3 offers // id, user_id, title, description, network_id, networks // id, title, integrated:0,1 sources // id, title, integrated:0,1 offers_payouts // id, offer_id, payout_type_id, default_payout, divide_revenue, revenue payouts_types // id, title ## CPA/CPL, CPS, revshare

offers_conversions // id, offer_id, title, conversion_payout, payout_type, is_confirmation_required offers_conversions_payouts // id, title, amount, payout_type

campaigns // id, user_id, title, default_offer_id, test_mode, created, modified, deleted campaigns_sources // id, source_id, click_price_gross, budget

campaigns_events // id, campaign_id, event, created, deleted campaigns_custom_fields // id, campaign_id, field_name, field_default_value

campaigns_targeting_countries // id, campaign_id, geo_country_id, weight, offer_landing_id campaigns_targeting_states // id, campaign_id, geo_state_id, weight, offer_landing_id campaigns_targeting_cities // id, campaign_id, geo_city_id, weight, offer_landing_id

campaigns_targeting_offers // id, campaign_id, weight, offer_landing_id campaigns_targeting_days // id, campaign_id, targeting_day, weight, offer_landing_id campaigns_targeting_hours // id, campaign_id, targeting_hour, weight, offer_landing_id

• p1, p2, p3, p4, p5, source

clicks conversions // click_uid, created, modified, deleted events // Browser / Device / Ip / Time / Location statistics // campaigns_statistics // id, source_id, clicks, spent, avg_click_price

http://clickhub.co/conversion?c=323&cid=2384723894&payout=40 http://clickhub.co/event?c=323&cid=2384723894&e=upsell

Campaign #354

Default Offer - Crypty Crypto Weights - 30% Cryptomania 50% Crypto Crypty 20% Bitcoin World

Countries - USA - 100% Bitcoin World Netherland - 50% Bitcoin World, 50% Crypto Crypty

Device - Mobile - 80% Bitcoin World, 50% Crypto Crypty IOS - 100% Crypto Crypty

Research methods to do auto complete in input fields for big data (1m, 5m, 10m) currently methods list to check: Redis ZRANK/ZSET Redis Radix Tree

• Mysql Nested Set Model ** Mongo Nested Set Model Mongo Radix Tree
• If proven to be faster then mongo, will also test radix tree ** Only if mongo radix tree will be proven efficient All methods should be tested on 8gb memory/4 cores machines Each methods should have its own server.