Integrate Mention with Delighted
Mention monitors conversations about a brand by tracking any time that the brand is mentioned on a range of online platforms, including social media, blogs, or news outlets. Mention can then analyze the sentiment of those conversations and send that information to users in the form of alerts. This data also allows Mention to gauge overall public sentiment and reputation of a brand. If those metrics seem particularly unusual - i.e. if there is a spike in negative public sentiment - they can send notifications immediately so that changes can be made.
Delighted is a service that employs single question surveys to provide businesses with real-time customer feedback. Each survey question can have a rating scale for customers to select from as well as a section where customers have the option to leave a free-form comment. This provides both a numerical score - that can be collected to create a Net Promoter Score (NPS) - and useful customer feedback that Delighted can filter and search to retrieve the most useful responses for a given purpose.
Popular Use Cases
Bring all your Mention data to Amazon Redshift
Load your Mention data to Google BigQuery
ETL all your Mention data to Snowflake
Move your Mention data to MySQL
Bring all your Delighted data to Amazon Redshift
Load your Delighted data to Google BigQuery
ETL all your Delighted data to Snowflake
Move your Delighted data to MySQL
Integrate Mention With Delighted Today
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Mention's End Points
Create or modify a Mention user account, including the user’s contact info, how often they receive alerts and what kind of access they have to the data on Mention. This allows you to ensure that users can operate as efficiently as possible and interact with Mention in a way that creates the best workflow for them.
Retrieve a list of mentions that have been tracked by your alerts, which can be filtered by a number of parameters including source, date range and tone. This query then returns details - like description, source and author’s influence score - about the relevant mentions, allowing you to gauge if the mention warrants a response.
Define the parameters of an alert, such as the alert’s name, query terms and tracked sources. Then, retrieve data about the mentions that have triggered the alert, including how many mentions there are and how important it is to respond to them.
Design tags, which can be used to filter responses generated by your alerts. Once a tag is created, you can either fetch all the Mentions with that tag in them or use the tag as one of many parameters to filter queries about the mentions in an alert.
Delighted's End Points
Create a survey recipient, including their customer ID, email address and phone number. Then, you can customize your survey delays based on your customers’ needs and preferences, specifying how you want the surveys sent - via SMS or email - and how frequently you want them sent.
Retrieve data from customer responses, including the score they selected, any comments they left in response to the survey and the person ID for the customer (which allows you to continue to track their responses). Additionally, use this data to create and update your Net Promoter Score, which can help provide customer analytics both within Delighted and in other data sources via integration.
View important metrics for your account like your NPS and the percentage of your respondents that identified as promoters, passives, or detractors. This provides a broader view of your survey performance that can help you determine your overall business performance.
When someone unsubscribes, you can maintain their previous survey response data and view their old emails. When integrated with other user data, this information can provide key business insights. It can also be used to run an array of business analyses, including predictive analytics.