Abstract: A method for generating bids for a group of keywords includes accessing, over a computer network, budget data and historical spend data for at least two groups of keywords. The method also includes determining a baseline portion of a budget to be allocated to a first group of keywords. The method also includes predicting, with reference to the historical spend data and the historical budget allocation data, an unspent amount. The method also includes calculating, based upon at least one adjustable allocation parameter, a first portion of the unspent amount to be allocated. The method also includes allocating the baseline portion and the first portion of the unspent amount to the first group of keywords. The method also includes allocating a second portion of the unspent amount to the second group of keywords. The method also includes generating bids for the first group of keywords.

Abstract: Methods and systems for establishing a web presence, a mobile-optimized web presence, a marketing campaign and a mobile-optimized marketing campaign. Various embodiments of the methods and systems disclosed herein may permit independently generating mobile-optimized and desktop versions of one or more web presences, landing pages and marketing campaigns based on business information and taxonomies. Computer systems implementing methods of establishing mobile-optimized web presences and marketing campaigns are also disclosed.

Abstract: Methods and systems for establishing a web presence, a mobile-optimized web presence, a marketing campaign and a mobile-optimized marketing campaign. Various embodiments of the methods and systems disclosed herein may permit independently generating mobile-optimized and desktop versions of one or more web presences, landing pages and marketing campaigns based on business information. Computer systems implementing methods of establishing mobile-optimized web presences and marketing campaigns are also disclosed.

Abstract: A method for generating bids for a group of keywords includes accessing, over a computer network, budget data and historical spend data for at least two groups of keywords. The method also includes determining a baseline portion of a budget to be allocated to a first group of keywords. The method also includes predicting, with reference to the historical spend data and the historical budget allocation data, an unspent amount. The method also includes calculating, based upon at least one adjustable allocation parameter, a first portion of the unspent amount to be allocated. The method also includes allocating the baseline portion and the first portion of the unspent amount to the first group of keywords. The method also includes allocating a second portion of the unspent amount to the second group of keywords. The method also includes generating bids for the first group of keywords.

Abstract: A method and related system for determining the weighted average conversion (or click-through) probability (WACP) associated with an activity, such as an internet advertising bid activity. The method involves gathering information associated with prior actions relevant to future actions, such as bidding on internet advertisement placement, for example. The gathered information, such as clicks, impressions and conversions resulting from an advertisement placement, is used in an algorithm to calculate the WACP. The method may be carried out as part of a system including one or more computing devices and the execution of instructions embodied in computer-readable media. The algorithm may include the option of weighting the data used, such as by valuing recent data more than older data.

Abstract: A method for managing online advertising placements includes associating a plurality of textual metadata tags with at least one advertising placement, and generating a bid recommendation for the at least one advertising placement associated with the plurality of textual metadata tags.

Abstract: A method for valuing a link-hosting webpage is provided. The method includes the act of receiving, on a computer system, at least one keyword. The method also includes the act of receiving, on a computer system, at least one identifier of a webpage, the webpage having been previously identified as a link-hosting webpage. The method also includes the act of accessing information about the webpage over a computer network. The method also includes the act of determining an importance of the webpage based on the at least one keyword and the information about the webpage. The method also includes the act of displaying the importance on a computer-based user interface.

Abstract: A method is provided for identifying and crediting interactions leading to a conversion, comprising acts of for each of at least one defined time interval, defining a recency factor used to scale a credit amount given to an influencing event occurring during the defined time interval; identifying at least one influencing event that influenced a conversion event; for each of the at least one influencing events, identifying a defined time interval in which the influencing event occurred and accessing the recency factor for that defined time interval; and apportioning the credit amount given to the conversion event among the at least one influencing event according to the recency factor for each influencing event.

Abstract: A method and related system for determining the weighted average conversion (or click-through) probability (WACP) associated with an activity, such as an internet advertising bid activity. The method involves gathering information associated with prior actions relevant to future actions, such as bidding on internet advertisement placement, for example. The gathered information, such as clicks, impressions and conversions resulting from an advertisement placement, is used in an algorithm to calculate the WACP. The method may be carried out as part of a system including one or more computing devices and the execution of instructions embodied in computer-readable media. The algorithm may include the option of weighting the data used, such as by valuing recent data more than older data.

Abstract: A gas distributor distributes a gas across a surface of a substrate processing chamber. The gas distributor has a hub, a baffle extending radially outward from the hub, a first set of vanes and a second set of vanes. In one version, the hub has a gas inlet and a gas outlet. The baffle has an opposing first and second surfaces. First vanes are on the first surface of the baffle and direct gas across chamber surfaces. In one version, the first vanes comprise arcuate plates that curve and taper outward from the hub. Second vanes are on the second surface of the baffle and direct gas across the second surface of the baffle. In one version, a gas feed-through tube in the hub can allow a gas to bypass the first and second set of vanes.

Abstract: A gas distributor distributes a gas across a surface of a substrate processing chamber. The gas distributor has a hub, a baffle extending radially outward from the hub, a first set of vanes and a second set of vanes. In one version, the hub has a gas inlet and a gas outlet. The baffle has an opposing first and second surfaces. First vanes are on the first surface of the baffle and direct gas across chamber surfaces. In one version, the first vanes comprise arcuate plates that curve and taper outward from the hub. Second vanes are on the second surface of the baffle and direct gas across the second surface of the baffle. In one version, a gas feed-through tube in the hub can allow a gas to bypass the first and second set of vanes.

Abstract: Embodiments of the present invention are directed to a search engine system, method and apparatus comprising a search engine, a participant management system, at least one storage database, a listing database and at least one feedback mechanism. The search engine accepts input data and utilizes the input data to search for information related to the search terms. Upon retrieval of relevant information, the data analysis module organizes the data related to the search terms into a search results list. To determine the placement of listings upon a search request, the data analysis module determines the probability, for each relevant listing, that the user will ultimately complete the desired action if the listing is shown, wherein the probability of action is determined by a plurality of factors. This probability is then combined with the specific CPA for the advertiser.