GrammAds: Keyword and Ad Creative Generator for Online Advertising Campaigns Author : Stamatina Thomaidou, Konstantinos Leymonis, and Michalis Vazirgiannis.

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Presentation transcript:

GrammAds: Keyword and Ad Creative Generator for Online Advertising Campaigns Author : Stamatina Thomaidou, Konstantinos Leymonis, and Michalis Vazirgiannis Presenter: Wayne Yang

Agenda Introduction Related Work Keyword Generation Ad Creative Generation Campaign Organization and Use Cases System Architecture and Communication Experimental Evaluation Conclusion and future work

Introduction - Baseline Campaign Creation Process Product A landing web page (price, buy) Finding keyword Advertising text

Introduction - Motivation for an Automated Application An advertiser decides Usually choose specific 1-3 keywords per product Short headline and ad text maximum cost-per-click of each keyword =>effective keyword selection is one of the most important success factors for online advertising

Related Work Google Adwords - They start from an ini- tial key phrase and they are based on past queries that contain these search terms. Other commercial tools - determine an advertiser’s top competitors and then actively search for the keywords they are targeting. TermsNet and Wordy - With their methods they find other semantically similar terms.

Keyword Generation Keyword Extraction Landing page parsed => stop words removed => trigram, bigrams, unigram => calculate relevance keyword Keyword Suggestion Seed keywords => top 30 result pages => corpus => lucene score

Ad Creative Generation generic summary - shows the main topics and key contents covered in the source text query-relevant summary - locates the contents pertinent to user’s seeking goals(our system provided) extract text => Bayesian classifier to summarize

Campaign Organization and Use Cases Step 1 – initial settings 1.no optimization - where the system just uploads automatically the generated keywords, ad-texts, and bids along with their organized structure without continuing to be responsible for an automated optimization strategy 2.traffic optimization - where the advertiser considers the profit to be the amount of clicks at the ad-texts 3.profit optimization - where the profit is the actual monetary profit from offline product sales or online conversions to a specific landing page that is defined in a next step Step 2 – Crawler module Step3 – select keyword

Campaign Organization and Use Cases Step 4 - Automatically generated keywords and recommended bids Step 5 - the user can see through the Google AdWords interface the uploaded settings of his constructed campaign.

System Architecture and Communication The proposed system structure resulted as a need for an appropriate user inter- face interaction of the Adomaton subsystem, which optimizes Google AdWords Campaigns through a novel bidding strategy. Adopt model view controller for information managment

System Architecture and Communication

Experimental Evaluation

Conclusion and future work Automating the task of finding the appropriate keywords Recommending multiword terms (n-grams) with high specificity without the need to capitalize on usage data such as query and web traffic logs Generating fast snippets of ad texts An automated and fast way of uploading campaign and AdGroup settings (keywords and ad-texts per AdGroup) into the AdWords service A developed web application with an initial experimentation on real world campaigns