Insights > Utilizing the OneSpot App Dashboard
Utilizing the OneSpot App Dashboard
This guide is to aid in the utilization of the OneSpot Dashboard. Feel free to reach out to your Account Manager or Professional Services contact with any additional questions.
Click on the Paper icon on the left side of the screen.
This is all the content that we have scraped from the site.
On the top right, you can use the search bar to search by the different categories of content.
- Recommendable – all content that is able to be injected into OnSite/InBox units (Note: The Recommendable section does not account for additional filter setup on the individual units.)
- Non Recommendable – all content that is not able to be injected into OnSite/InBox units
- All Pages – all pages we have scraped.
E.g. We are scraping and recommending articles, recipes, and products and you want to see all of the recommendable articles only.
- You would confirm you are under the Recommendable section.
- In the filters section on the left side, you would select og:type and then matches query and then you would type in article. All the displayed content would be articles.
Details on how to utilize the queries can be found on the Content Inventory Searches guide. You can also use the search bar in the top right of that support page for a more general search.
If you click on a specific piece of content, it will open a new page, showing details regarding that specific page that are explained below.
You will see the stats (based on a time range) on how many visitors, visits, views, and time has been spent viewing the page.
2.77K unique people (visitors) visited the page in 2.87K different sessions (visits) viewing the page a total of 4.48K times (views) and spent a total of 48 hours on the page (time).
On the top right you can see more details about the page:
Publish Date: Date the page was published
Author: If there is a designated author of the page
Word Count: Total word count on the page
Image Count: How many images are on the page
Est Read Time: Determined by the NLP for how long it takes to read the page
Avg Read Time: Average amount of time a viewer spends on the page
Video: If there is a video on the page or not
Scrape Date: Last scrape date
Some of the details above can be used to search in the content browser as well. A few examples are listed below:
E.g. 1. You are looking for articles published by a specific author. On the left side, you would select the Author filter and select contains and type the author’s name.
E.g. 2. You are looking for articles which were published in 2019. On the left side, you would select the Published Date filter and select after and set the date to January 1st 2019. Then click Add Filter. You would then select before and set the date to December 31st 2019.
E.g. 3. You are looking for articles published on a specific date. On the left side, you would select the Published Date filter and select on and select the specific date you are looking for..
This is a quick view analytical data at the top to provide a quick overview of performance and more detailed analytics.
The Traffic Sources graph shows how users navigated to the page and is broken down by the percentage of traffic being sent from each source. This can be filtered by Week, Day, or Hour.
The Location Map shows where this page has most commonly been viewed. The darker the state, the more views and you can toggle between a map of the US and Canada. You can also see what devices were used to view the page and if the viewers were returning or new.
This tab provides details on viewer browsing habits and recirculation.
Lists content based on what users who viewed the current page have also viewed so you can see the association of content for page viewers.
Lists content which is similar to the page you are currently looking at.
List content based on what a percentage of viewers were on before the current page. (E.g. 41% of views (1.84K) came from clicks on these content pages.)
The topics at the top of the page are determined by the NLP (Natural Language Processing) based on the content. This could be based on direct keywords or within context.
The topics and color palate on the right side are determined by the NLP based off of the image.
The page also includes the extracted content from the page, excluding images.
Underneath the extracted content are all the tags that have been scraped from the page. This information helps us drive the business logic. The URL is a big piece as, in a well structured website, products will be under /products or something similar so we can use that in filtering rules. This tells you what we are seeing and how we can work with your data when it comes to recommendations. This also is a clear indicator of what sites like Google see.
Click on the bar graph icon on the left side of the screen.
This provides you a general overview of analytics. You might see similar data within Google Analytics.
All the topics are determined by the NLP. You can curate to remove specific topics that don’t necessarily fit (E.g. your business name) so you can sort your topic curation so you are seeing more relevant topics.
If you click on a topic, it will realign the total views with it and sometimes you might see topics that correlate with each other (E.g. Hair and Red Hair Dye)
The best quality topics will be the upper right and the lower quality topics will be the lower left.
If you go to select chart, you have other views as well. The most commonly used is Time Series: Traffic Sources. It helps you see where users are coming through and align charts according to the data you would like to see.
Under the Engagement map, it has the top (up to 20) articles based on the selected ranking and you can customize the report based on the data available (on the left and right sides). For specific search queries, you can reference the Insights Dashboard Searches guide.