Analyzing changes in web analytics metrics
First Claim
1. A computer-implemented method comprising:
- obtaining, by one or more data processing apparatus, from a data store, and over a network, visitor data collected from one or more client devices accessing, over the network, one or more remote servers that manage websites visited by the one or more client devices;
generating, by the one or more data processing apparatus, multiple instances of a web analytics metric for a given website over a period of time based on the visitor data;
identifying, by the one or more data processing apparatus, a change in a web analytics metric for the given website over the period of time based on a comparison of the multiple instances of the web analytics metric;
determining, by the one or more data processing apparatus for each segment of two or more segments, a contribution score specifying a level of contribution to the change in the web analytics metric over the period of time that is attributed to a change in a value of the segment over the period of time, wherein the determination includes, for each segment;
determining a first comparison between (i) a value of the web analytics metric at an earliest time in the period of time and (ii) a value of the segment at the earliest time in the period of time,determining a second comparison between (iii) a value of the web analytics metric at a latest time in the period of time and (iv) a value of the segment at the latest time in the period of time,adjusting the first comparison using a value of a weight time series of the segment at the earliest time,adjusting the second comparison using a value of the weight time series of the segment at the latest time, andcomputing the contribution score for the segment based on a difference between the adjusted first comparison and the adjusted second comparison.
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Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for analyzing changes in web analytics metrics. In one aspect, a method includes identifying a change in a web analytics metric for a website over a period of time, the web analytics metric being based at least in part on visitor data for the website over the period of time; computing a respective segment contribution score for each of a plurality of segments of the web analytics metric, wherein a segment contribution score for a particular segment is based at least in part on a comparison between a value of the web analytics metric and a value of the particular segment during the period of time; and identifying one or more of the plurality of segments as contributing to the change in the web analytics metric based on the respective segment contribution scores.
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Citations
20 Claims
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1. A computer-implemented method comprising:
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obtaining, by one or more data processing apparatus, from a data store, and over a network, visitor data collected from one or more client devices accessing, over the network, one or more remote servers that manage websites visited by the one or more client devices; generating, by the one or more data processing apparatus, multiple instances of a web analytics metric for a given website over a period of time based on the visitor data; identifying, by the one or more data processing apparatus, a change in a web analytics metric for the given website over the period of time based on a comparison of the multiple instances of the web analytics metric; determining, by the one or more data processing apparatus for each segment of two or more segments, a contribution score specifying a level of contribution to the change in the web analytics metric over the period of time that is attributed to a change in a value of the segment over the period of time, wherein the determination includes, for each segment; determining a first comparison between (i) a value of the web analytics metric at an earliest time in the period of time and (ii) a value of the segment at the earliest time in the period of time, determining a second comparison between (iii) a value of the web analytics metric at a latest time in the period of time and (iv) a value of the segment at the latest time in the period of time, adjusting the first comparison using a value of a weight time series of the segment at the earliest time, adjusting the second comparison using a value of the weight time series of the segment at the latest time, and computing the contribution score for the segment based on a difference between the adjusted first comparison and the adjusted second comparison. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system comprising:
one or more computers and one or more storage devices storing instructions that, when executed by the one or more computers, to cause the one or more computers to perform operations comprising; obtaining, by one or more data processing apparatus, from a data store, and over a network, visitor data collected from one or more client devices accessing, over the network, one or more remote servers that manage websites visited by the one or more client devices; generating, by the one or more data processing apparatus, multiple instances of a web analytics metric for a given website over a period of time based on the visitor data; identifying, by the one or more data processing apparatus, a change in a web analytics metric for the given website over the period of time based on a comparison of the multiple instances of the web analytics metric; determining, by the one or more data processing apparatus for each segment of two or more segments, a contribution score specifying a level of contribution to the change in the web analytics metric over the period of time that is attributed to a change in a value of the segment over the period of time, wherein the determination includes, for each segment; determining a first comparison between (i) a value of the web analytics metric at an earliest time in the period of time and (ii) a value of the segment at the earliest time in the period of time, determining a second comparison between (iii) a value of the web analytics metric at a latest time in the period of time and (iv) a value of the segment at the latest time in the period of time, adjusting the first comparison using a value of a weight time series of the segment at the earliest time, adjusting the second comparison using a value of the weight time series of the segment at the latest time, and computing the contribution score for the segment based on a difference between the adjusted first comparison and the adjusted second comparison. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:
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obtaining, by one or more data processing apparatus, from a data store, and over a network, visitor data collected from one or more client devices accessing, over the network, one or more remote servers that manage websites visited by the one or more client devices; generating, by the one or more data processing apparatus, multiple instances of a web analytics metric for a given website over a period of time based on the visitor data; identifying, by the one or more data processing apparatus, a change in a web analytics metric for the given website over the period of time based on a comparison of the multiple instances of the web analytics metric; determining, by the one or more data processing apparatus for each segment of two or more segments, a contribution score specifying a level of contribution to the change in the web analytics metric over the period of time that is attributed to a change in a value of the segment over the period of time, wherein the determination includes, for each segment; determining a first comparison between (i) a value of the web analytics metric at an earliest time in the period of time and (ii) a value of the segment at the earliest time in the period of time, determining a second comparison between (iii) a value of the web analytics metric at a latest time in the period of time and (iv) a value of the segment at the latest time in the period of time, adjusting the first comparison using a value of a weight time series of the segment at the earliest time, adjusting the second comparison using a value of the weight time series of the segment at the latest time, and computing the contribution score for the segment based on a difference between the adjusted first comparison and the adjusted second comparison. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification