Methods and systems are described for selecting an engaging ad campaign among advertising campaigns having different types of bid strategies. In one embodiment, an advertising system designed for selecting relevant and engaging ad campaigns for delivering to a device of a user includes an adaptive decision unit having filter logic for filtering eligible ad campaigns, a storage medium to store instructions of the system, and processing logic coupled to the storage medium. The processing logic is configured to execute the instructions of the system to receive and process an ad request from the device upon initiation of a software application on the device, filter eligible ad campaigns, convert each bid strategy of the filtered ad campaigns into an effective cost-per-mille (CPM) strategy, compare effective CPM strategies for the filtered ad campaigns, and select an ad campaign based on the comparison of the effective CPM strategies.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automated management of campaigns using scripted rules.

A social media influencer advertising platform uses a feedback mechanism to help influencers manage the effectiveness of their advertisements. The feedback mechanism may be various components of an influencer's dashboard that report conversion statistics. An influencer may be able to judge their effectiveness individually or against other influencers, where effectiveness may be on downstream actions, conversions, product sales, or other activities performed by viewers of the influencer's posts. With this feedback, the influencer may be able to tune, adjust, or change their posts to improve their conversion rate and become more effective advertisers. Through the platform, brands may pay for performance, and by giving feedback to the influencers, the influencers may be able to track their performance.

There are disclosed marketing analytics apparatus and processes. There is a data store of interactions between a plurality of customers and one or more vendors over a plurality of channels. Pathing and attribution of these interactions may be obtained as marketing analytics. Pathing may be obtained in part with a match programming statement which identifies all of the paths in the data store matching criteria specified in the match programming statement. Pathing may be obtained in part with a split programming statement which splits all of the journeys in the data store into paths. After pathing, an attribution pathing statement may be used to attribute conversions to other events.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automated management of campaigns using scripted rules, and managing the execution of the rules.

Disclosed are methods and systems for generating targeted advertising campaigns for a business-to-business (B2B) company. The method comprises first retrieving an ideal customer profile (ICP), and generating candidates leads that match the ICP. Next, generating test campaigns, scoring each test campaign based on a number of acquired leads and a campaign cost per lead (CPL), where the number of acquired leads is calculated based on feedback information received from each test campaign, and where each test lead who responds affirmatively to one of the test campaigns is marked as an acquired lead, and generating a targeted advertising campaign to a larger subset of the candidate leads based on the test campaign scores. The present invention utilizes a closed-loop approach to customize campaign audiences, to optimize targeted advertising campaigns and ICPs, and as a result, to produces high-quality, low-cost, targeted advertising campaigns for B2B companies.

Techniques for allocating test offers to determine a best offer in a set of offers with a desired confidence level. An allocatiton of additional test offers is determined by allocating the additional test offers unevenly, e.g., allocating more additional test offers to offer A than to offer B, etc. The test offers are allocated to test the offers in the set of offers to attain the desired confidence level that one of the offers is the best offer for the campaign. For example, this can involve allocating test offers in a way that is expected to minimize the number of additional test offers needed to attain the desired confidence level in the best offer. Additional test offers are made until a best offer is identified with the desired confidence level based on the outcome information.

A system and method for unifying user-level data across a plurality of media platforms are provided. The method includes receiving user-level data events from the plurality of media platforms, wherein each event relates to at least one online advertisement viewed by a plurality of users; processing the received user-level data events to detect a group of user-level data events related to the same user of the plurality of users; combining user-level data from each group of user-level data events related to the same user; assigning a unique user identifier to the combined user-level data to result in a unified user-level data related to a particular user; and storing the unified user-level data in a database, thereby providing consistent user-level data across the plurality of media platforms.

In one aspect, a request for web content is received from a user device communicatively coupled to the processing device via the network. In response to receiving the request, user information associated with the user is determined. Predicted responses of the user to each variation of a plurality of variations of the web content are determined using prediction models and the user information. The prediction models include one or more decision trees generated using a splitting criterion requiring a minimum number of positive responses to a variation and a minimum number of negative responses to the variation as a condition of considering the possible split. The variation determined to have a threshold likelihood of yielding a predicted positive response of the predicted responses is selected based on the user information. The variation is transmitted to the user device via the network.

An embodiment may involve repeatedly receiving, from one or more online advertising service devices at which one or more web-based display advertising campaigns are operated, updates to information related to display advertisement placement and display advertisement performance associated with the one or more web-based display advertising campaigns. The information may include a plurality of metrics. The embodiment may further involve receiving, via selectable controls on a graphical user interface of a client device, a selection of two of the plurality of metrics. The embodiment may also involve transmitting, for display on the graphical user interface, data representing values of the selected two metrics over a pre-defined period of time. Reception of the data may causes the client device to plot a graph indicating the values of the selected two metrics over the pre-defined period of time, where the values as shown in the graph for each of the selected two metrics are normalized to one another.