Attribution Strategies and Return on Keyword Investment in Paid Search Advertising
نویسندگان
چکیده
Firms use different attribution strategies such as last-click attribution or first-click attribution to assign conversion credits to search keywords that appear in their consumers’ paths to purchase. These attributed credits impact a firm’s future bidding and budget allocations among keywords and, in turn, determine the overall return-on-investment of search campaigns. In this paper, we model the relationship among the advertiser’s bidding decision for keywords, the search engine’s ranking decision for these keywords, and the consumer’s click-through rate and conversion rate on each keyword, and analyze the impact of the attribution strategy on the overall return-oninvestment of paid search advertising. We estimate our simultaneous equations model using a six-month panel data of several hundred keywords from an online jewelry retailer. The data comprises a quasi-experiment as the firm changed attribution strategy from last-click attribution to first-click attribution half-way through the data window. Our results show that returns for keyword investments vary significantly under the different attribution strategies. For the focal firm, first-click attribution leads to lower returns in terms of revenue and the decrease is more pronounced for the more specific keywords. Our policy simulation exercise shows how the firm can increase its overall returns by better attributing the real contribution of keywords. We discuss how an appropriate attribution strategy can help firms to better target customers and lower acquisition costs in the context of paid search advertising.
منابع مشابه
Attribution Strategies and Return on Keyword Investment in Paid Search Advertising ( Forthcoming at Marketing Science )
Firms use different attribution strategies such as last-click attribution or first-click attribution to assign conversion credits to search keywords that appear in their consumers’ paths to purchase. These attributed credits impact a firm’s future bidding and budget allocations among keywords and, in turn, determine the overall return-on-investment of search campaigns. In this paper, we model t...
متن کاملA Model of Individual Keyword Performance in Paid Search Advertising
In paid search advertising on Internet search engines, advertisers bid for specific keywords, e.g. “Rental Cars LAX,” to display a text ad in the sponsored section of the search results page. The advertiser is charged when a user clicks on the ad. Many of the keywords in paid search campaigns generate few, if any, sales conversions – even over several months. This sparseness makes it difficult ...
متن کاملModeling Indirect Effects of Paid Search Advertising: Which Keywords Lead to More Future Visits?
M online shoppers initially acquired through paid search advertising later return to the same website directly. These so-called “direct type-in” visits can be an important indirect effect of paid search. Because visitors come to sites via different keywords and can vary in their propensity to make return visits, traffic at the keyword level is likely to be heterogeneous with respect to how much...
متن کاملAds Keyword Rewriting Using Search Engine Results
Paid Search (PS) ads are one of the main revenue sources of online advertising companies where the goal is returning a set of relevant ads for a searched query in search engine websites such as Bing. Typical PS algorithms, return the ads which their Bided
متن کاملAdvertising Keyword Suggestion Using Relevance-Based Language Models from Wikipedia Rich Articles
When emerging technologies such as Search Engine Marketing (SEM) face tasks that require human level intelligence, it is inevitable to use the knowledge repositories to endow the machine with the breadth of knowledge available to humans. Keyword suggestion for search engine advertising is an important problem for sponsored search and SEM that requires a goldmine repository of knowledge. A recen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Marketing Science
دوره 35 شماره
صفحات -
تاریخ انتشار 2016