Bing Ads is a search engine marketing platform that includes several tools to improve conversion rates for search engine ads. For example, Bing Ads can generate a list of relevant keywords, use ad extensions to provide additional information to specific customers, and design retargeting campaigns, all of which can help increase the conversion rate of website visitors. In addition, Bing Ads also offers ad analytics, which can help detail the relationship between a number of metrics, such as website visits, click-through rates, and conversion rates.
Mixpanel gathers product usage data, including metrics like what features are being used most frequently, the number of active users, and when user engagement rises or drops. It also automatically collects data on all user actions and uses that data to provide a variety of useful insights, such as automatic suggestions for how to improve customer retention and lead acquisition. Since usage data is collected from the start, Mixpanel can also track newly defined metrics using historical data.
Bring all your Bing Ads data to Amazon Redshift
Load your Bing Ads data to Google BigQuery
ETL all your Bing Ads data to Snowflake
Move your Bing Ads data to MySQL
Bring all your Mixpanel data to Amazon Redshift
Load your Mixpanel data to Google BigQuery
ETL all your Mixpanel data to Snowflake
Move your Mixpanel data to MySQL
Monitor your requests to upload product offers to the Bing Ads catalogs so that you can see when and why they are accepted or rejected by Bing Ads review process. This endpoint also lets you see how many total offers were accepted or rejected, allowing you to evaluate your products and improve your acceptance rate.
Track data for a specific product or list of products in a store and run market analytics on those products to monitor their performance. You can also use this endpoint to manage product properties, such as age group, product type, condition and more, allowing you to segment your ad campaigns and conduct market analysis for that product.
Create or retrieve product catalog data, such as the name of an associated store, the store’s market, and the catalog’s ID. This information can be used to insert products directly into that catalog and/or to track the catalog’s performance using other endpoints.
Get any or all raw event data that has been collected by Mixpanel, including what events have occurred, when they happened, and any relevant properties about those events. Then, integrate this raw data with other data sources to get new or deeper usage analytics.
Retrieve data about a customer’s journeys through your funnel. This data contains the customer’s timeline from start to finish - including how many steps in the funnel the customer completed during that time - which can be used to identify which steps during a funnel most commonly include specific events, such as losing a customer.
Gather event data that is filtered into segments by an array of properties, such as date range, country, and specific search terms. Then, use that filtered Mixpanel data to get deeper, more detailed analytics into your product performance.
Track customer engagement data, including a customer’s name and email address, as well as the date and time they last accessed your product. This allows you to run predictive analytics, which can show when engagement will likely drop or increase based on historical engagement data.
Get retention data for a specific cohort of customers by tracking signups and other relevant events during a specified date range. Then, you can feed that Mixpanel data into your analytics to provide a more comprehensive view of your retention trends over time.