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.
As an advanced, high-speed data analytics platform, Mode helps you understand the information in your data warehouses. As a hybrid solution Mode lets (1) data teams customize queries and visualizations in Python, SQL, or R; and (2) empowers non-tech-savvy users to dive into visualizations and explore live-updating reports to get the data they need.
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
Bring all your Mode data to Amazon Redshift
Load your Mode data to Google BigQuery
ETL all your Mode data to Snowflake
Move your Mode data to MySQL
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.
Mode's SQL editor features a schema browser to explore the tables and columns of your connected data sources. It also has an autocomplete function to assist with query writing, a query history to browse and reuse old queries, and advanced logic tools for creating loops, IF statements, and more.
The technology behind Mode's analytics solution is Helix, a high-performance in-memory data engine that combines modern drag-and-drop business intelligence tools with a code-first (SQL, Python, R) data science platform to offer an instantly responsive user experience. Mode streams query results into the Helix data engine to reduce database load, provide quick responsiveness, and give users the ability to visually navigate as much as 10 gigabytes of data.
Powered by SQL, Python, and R, Mode dashboards display automatically-refreshing metrics without the need for proprietary tools. Customize your dashboards the way you want, with on-brand reporting and interactive features to facilitate collaboration with others across your organization.
Mode features native Python and R Notebooks. This allows you to query in SQL, send the results to a dataframe in R or pandas, and conveniently access them in the platform's native Notebook. At the same time, a sidebar provides tips, shortcuts, and documentation to help you get the most of these features.