Description:
About Clootrack Platform:
- Clootrack is a real-time customer experience analytics platform. It helps brands to understand "why" customer experience drops.
- Clootrack reduces response time to CX trends by 88%, and our clients see a reduction in churn from 5-6% to 3-4% within three to six months of onboarding.
- Clootrack obtains qualitative insights from customer conversations, feedback and reviews.
About this Data share:
- This data share includes themes of discussion, consumer sentiments, category drivers, delighters and concerns of consumers.
- This data can be segmented by brands, categories, subcategories, price, SKUs, star ratings and date range.
- The changing consumer experience can be analyzed as a trend over time. All eCommerce categories under Electronics along with brands, products, sub-products can be compared against each other.
- The data set also includes actual customer verbatim.
- The data can be used to assess customer experience or to train your internal machine learning engines.
- A data dictionary, a list of all available tables and SQL queries are available in the documentation.
- This is a sample dataset with one month data. If you would like the full dataset, please find our full offering on the Snowflake Data Marketplace.
Tables Included:
1. SENTIMENTS_VIEW
- This table shows the consumer sentiment towards a brand over the last month with limited rows for each day.
- Customer experience trend changes over time.
- Progression in positive/negative experience based on various themes.
- Comparison of a brand against other competition for a sub-category.
- Actual Sentences & Reviews and their respective sentiments.
- Product description(SKU), Category, sub categories(L1, L2, L3..), Star ratings and respective sources.
2. DRIVER_SCORES_VIEW
- This table shows Category Driver and Delighters & Concerns of brands over last months time data.
- The Popularity scores is out of 1500 which compared and calculated for each brand for that Category driver.
- All the data is represented in Month-wise Category popularity for each brand and the number of additional fields available.
SENTIMENTS_VIEW: These are the Sentiments table view fields
- Main Theme
- Main Theme Sentiment
- Sub Theme
- Sub Theme Sentiment
- Sub Theme Group
- Sub Theme Group Sentiment
- SKU
- Date
- Brand Name
- Location
- Price
- Source
- L1
- L2
- L3
- L4
- Sentence
- Sentence Sentiment
- Sentiment Confidence
- Product Rating
- Max Product Rating
- Review
- Review Rating
- Max Review Rating
- Clustering Confidence
DRIVER_SCORES_VIEW:
- Driver
- Driver Type [Delighters, Concerns]
- L1
- L2
- L3
- L4
- Brand
- Month
- Popularity Score
- Source
Customer Testimonials:
"We offer a lot of mediums for our customers to make their voices heard: product reviews, surveys, and a section where customers can write about their experience. We were looking for a platform that could create a more structured output from these channels. We had interactions and POCs with multiple vendors and Clootrack stood out with their ability to get meaningful output from the various unstructured customer input channels."
- Assistant Manager for Process Excellence, eCommerce brand of an Indian conglomerate.
"Our main challenge was decoding the conversation going on in Indian e-commerce across multiple languages. Clootrack provided us a machine learning tool that can decode the sentiments of various conversations and classify those. Clootrack crawled through one-years’ worth of data and segregated sentiments into different categories. They did a mapping of our brand equity, producing both quantitative and qualitative data."
- General Manager, Leading electrical appliances firm.