Microsoft bid history

In recent years the firm has pushed its Azure cloud computing product, launched in via a partnership with local data service company 21Vianet.

China's cyber-security law limits Microsoft to providing Azure's software and services while 21Vianet runs associated data centres. Microsoft operates both its Bing search engine and LinkedIn social network in China, though again is a small player compared with local giants. Its most important China operation is arguably Microsoft Research Asia, famous as a leader in artificial intelligence AI.

Bing and LinkedIn in China appear similar to their global counterparts but Microsoft censors search results and content the Chinese government considers sensitive. Upon LinkedIn's China launch in , two years before the company was bought by Microsoft, then-Chief Executive Jeff Weiner said censoring content would be "necessary" for the firm to grow in the country.

In , free speech advocates criticised LinkedIn's position on censorship after human rights activist Zhou Fengsuo said his profile was not viewable in China. LinkedIn blamed an "error" and restored its visibility. Software development website GitHub, which Microsoft purchased in , is also accessible from China.

Choose the types of data you want to clear see the table below for descriptions. For example, you may want to remove browsing history and cookies but keep passwords and form fill data. To manage and delete data saved in the Microsoft cloud, see the privacy dashboard. On the privacy dashboard you can view or delete your data.

To learn more about how to stop sharing your data with Microsoft, see Microsoft Edge browsing data and privacy. The list of files you've downloaded from the web. This only deletes the list, not the actual files that you've downloaded. Info that sites store on your device to remember your preferences, such as sign-in info or your location and media licenses.

Copies of pages, images, and other media content stored on your device. The browser uses these copies to load content faster the next time you visit those sites. Autofill form data includes forms and cards. Info web apps store on your device. This includes data from the Microsoft Store. Use this list to figure out which negative keywords to delete. Search term What it shows: The impressions, clicks, and click-through rate based on the search terms that have triggered your ads.

This data can be filtered for search campaigns and for shopping campaigns. Why run it: To get insight into what your audience is searching for when your ads are shown, as well as ensure that your product titles are relevant to search queries. This data can be sorted by keyword, keyword ID, landing page experience, and quality score. Destination URL What it shows: The impressions, clicks, spend, and average cost-per-click for your landing pages.

This data can be sorted by destination URL, account, campaign, and ad group. Note that only the first URL in the list ad, keyword, or criterion is reported.

Why run it: To identify landing pages that met audience expectations, resulting in high click or conversion ratios. This data can be sorted by website URL, account, campaign, and ad group. For example, if ad impressions at those URLs yield a low click-through-rate, then you might decide to exclude those websites from your campaign.

Ad dynamic text What it shows: The impressions, clicks, spend, and average cost-per-click of your dynamic text strings. This data can be sorted by ad title, destination URL, or the param dynamic text placeholders. Why run it: To identify which dynamic text strings are performing well and which strings you might consider changing.

Rich ad component What it shows: The component clicks and component click-through rate of your rich ads. This data can be sorted by rich ad subtype, ad title, and component. Audiences What it shows: The impressions, clicks, revenue, and conversions for your audiences. Why run it: To evaluate performance of remarketing campaigns.

Goals What it shows: The spend, revenue, assists, conversions, and conversion steps of your websites. This data can be sorted by account, ad group, campaign, keyword, and goal. Why run it: To discover whether visitors who arrive at your website via an Ad click, complete the steps on conversion pages of your website.

Conversions What it shows: The conversions, assists, revenue, and revenue per conversion for your campaigns. This data can be sorted by account, ad group, campaign, keyword, and device type.

Why run it: To understand which campaigns and keywords are leading customers to complete conversion actions. Ad extension by keyword What it shows: The impressions, clicks, spend, and average cost-per-click of your extensions for each keyword. This data can be sorted by keyword, keyword ID, ad extension type, and ad extension version. Why run it: To compare how well different versions of your ad extensions are performing for each keyword.

Ad extension by ad What it shows: The aggregated extension impressions, clicks, spend, and average cost-per-click by ad. This data can be sorted by ad ID, ad title, ad extension type, and ad extension version.

Why run it: To compare how well different versions of your ad extensions are performing with each ad. Ad extension details What it shows: The impressions, clicks, spend, and average cost-per-click of individual extension items.

This data can be sorted by the individual ad extension property value, ad extension ID, and ad extension type. Why run it: To discover the effectiveness of individual ad extension items, for example, each link of a sitelink extension. Call forwarding detail What it shows: Duration for each forwarded call that originated from a call ad extension.

Why run it: To discover which accounts, campaigns, or ad groups are driving the most completed phone calls. Product partition What it shows: The impressions, clicks, spend, average cost-per-click and average conversion for each product group in your Microsoft Shopping Campaigns. Why run it: To see the performance data for the product groups in your shopping campaigns and to optimize your campaigns accordingly.

Product partition unit What it shows: The impressions, clicks, spend, average cost-per-click, and average conversions for each product group in your Microsoft Shopping Campaigns.

Depending on the report time and columns you choose, the report may include more than one row per product group. Product dimension What it shows: The impressions, clicks, spend, average cost-per-click and conversion for each product in your catalog each line item in Microsoft Merchant Center catalog. Why run it: To figure out which of your products are triggering ads and getting the most clicks, and optimize the ones not performing so well.

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