Evaluate internal linking updates on page rank
Evaluate how good the site structure is at maximising page demand. We might do this with the iterative random surfer for page rank, and look at the overlap with of IPR with money pages. Use this to show relative benefits of different internal linking updates.
Summarise the impact of templates
On the overview of live templates, summarise the impact from dashboard. Show whether the impact is positive, negative or inconclusive. Which metrics we might use are likely to depend on the templates. For instance, an FAQ content block is likely to increase the average page rank, CTR and number of keywords for which a page ranks.
Calculate the Keyword Golden Ratio (KGR) for a topic
See https://sirlinksalot.co/keyword-golden-ratio/ for more details.
Focus in on new keywords
When a test group is ranking for more keywords, allow the user to download the keyword, URL, CTR, clicks, impressions and other data specifically for the new keywords.
Let users create variables
Variables are fields calculated from other fields, much like a cell formula in a spreadsheet. These could be used in recipe rules. Variables, once saved, are computed for all pages on the site. Variable could output different types such as: * a number such as a new traffic estimation for a site (perhaps using internal CTR data for certain topics) * a selection from a list or multiple selections, such as which question words are found in the topic keywords * a keyword
Improve listing relevance recall
Right now listing relevance is a very precise measure: a high listing relevance means a category page is a relevant result for the topic. In the SEA words, it will have a very high Quality Score (QS). However, a low listing relevance doesn't mean it has a poor QS, just that it might. Improve listing relevance recall without impacting precision, or at least impacting precision as little as possible. This would allow us to use listing relevance to clean-up low relevance pages. For instance, we might match singular and plural versions or match to other common n-grams for the topic or on the SERP.
Show the histogram summary by category level
Add a new 'by' to the histogram to show (e.g.) listing relevance by L1 or L2 category.