We now see all local teams using the same product to drive their marketing …
Also, marketing teams are starting to focus more on Consumer Data to pick up insights and details about audiences before launching …
All this is achieved using native segmentation tool and computation of metrics which are heavily relying on data availability.
The rules to compute the …
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- Tech Details
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|Supported Languages||English, Japanese|
|Small Businesses (1-50 employees)||10%|
|Mid-Size Companies (51-500 employees)||50%|
|Enterprises (more than 500 employees)||40%|
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- It helps a lot on data capture and availability.
- Helps on data visualization for all the marketers in the world.
- It is pretty fast working with big data.
- I think maybe the structure, like its not possible to create tables with specific fields.
- Positive on storing and showing data insights for the marketers.
- Creating dashboards, in treasure insights.
- Data availability
- God support, answers pretty quickly
- Scalable platform, supports well new amount of data
- Maybe for big python implementations
- Use it to run complex machine learning projects
- Product Features
- Product Usability
- Prior Experience with the Product
- Don't know
- I guess find good ways to work the data inside the platform
- Zones adoption
- in-person training
- Master segment, where you can easily filter data
- A huge catalog of integrations
- Easy way to export data
- using python in treasure data could be a challenge
- Create tables with different columns formats
- Export more than 2 Billion records
And also the master segment usability is awesome, as we can filter a lot of data the way we want.
- Amazon redshift
- Google sheet
- Google bigquery
- Amazon s3
- Not really, all the integrations that I need to develop, treasure data already had the connector
- File import/export
- Single Signon
- API (e.g. SOAP or REST)
- ETL tools
- I am not aware of the new upgrade, only by the contract upgrade
- I would like if the workflows could load the logs faster
- And sometimes the loading from the workflows could take a while, so it would be nice to fix that as well
- Knowledgeable team
- Helpful in setting up platform
- Insightful tools, platform, and people
- Great at strategic planning in our use cases
- Training has been great. We've had many training sessions across the org that were held by the ATD team.
- Hard to use if you're not heavily involved in data and analytics. We are hoping for an easier way for the marketing teams to utilize.
- Dashboards aren't super intuitive, but just require some additional walk-throughs.
- Need more resources
- We've run into some memory issues on the platform, but the ATD team is making improvements to fix these.
- We've been driving incremental revenue within our current use cases.
- Allows us to bring many 3rd-party tools in-house, which is a cost-saver and allows the platform to pay for itself.
- Brings our data together in a way we didn't realize was possible.
- A better understanding of our customer
- Increased personalization via various marketing campaigns, in new ways
- A holistic look at our customers and engagement with the company and our brands
- Scoring of our customers, active and inactive
- Increase personalization within our current campaigns
- Bringing in tools that are sourced from outside vendors, in-house by utilizing the data we store within Treasure Data
- Customer and engagement scoring
- Bringing in potentially more vendor products in-house to reduce costs and make them more personalized
- Additional audience building within media campaigns
- Tapping into our dealer's internal systems to gather more information
- Query finding and loading
- Reading the data
- Interface is intuitive to use
- The dashboards aren't very intuitive (for reporting)
- Building actual queries
- Audience segmentation in a way that makes sense to marketers
- Customer Service
- Realizing return on investment quickly
- Robust capabilities (younger company)
- We have seen significant return on investment
- Expanding into 3P audiences and leveraging the CDP to retarget them
- Integrate into multiple walled gardens to activate 1P LAL and overlap interest audiences
- Stand up an integration with SalesForce marketing cloud to set up 'nudge' emails to push people down the funnel
- Post-sales enrollment communications
- Email - client newsletters
- Email - automated reviews
- Product Features
- Product Usability
I have found the step-by-step workflow in building multiple segments very useful, which can be either run on-demand or scheduled for automated execution and campaign activations. The next steps are to leverage machine learning models for additional use cases like predictive scoring, etc.
- Providing omni-channel view of customer behavior
- Data ingestion including batch and near real-time data
- Campaign activation including email and social media
- Great UI, Flexible Data Model to work with given enterprise data
- Documentation could be better for the workflows & any custom logic implemented. Seems to be improving with the new approach using Markdown.
- API key management can be improved further
- Better customer engagement levels
- Reducing churn and increasing customer LTV
- Campaigns are now more effective resulting in higher RPU (revenue per user), better CTO rates, etc.
- Calculating the inferred product gender
- Leveraging the PySpark API to get the curated/profiled data back from Treasure Data for the purpose of integrating with the data lake
- Agilone and Acquia Platform
Agilone (now part of Acquia) has a very hard/strict requirement for integration with the source systems as we need to conform/adhere to their canonical/existing data model while Treasure data is quite flexible in being able to work with the respective source data as long as the relevant data was present. Overall, this has translated into a faster time to market in the case of Treasure Data and flexibility in incorporating changes/enhancements.
- Customer Data Platform for maintaining the 360-degree view of the customer
- Activating email and social media campaigns
- Tracking RFM scores & increasing Customer LTVs
- Enhanced reporting and dashboarding
- Building propensity models
- Better retention of lapsing guests and win back of churned guests
- Treasure Data is excellent in integration with various software and services.
- Implementation of the their SDK is also very easy.
- Treasure Data SDK works well in our applications and does not crush.
- Data management is very challenging with Treasure Data (can't delete records, update tables, create indexes, etc.).
- Analyzing and queries tables with very large number of records is near impossible or takes a very long time.
- To effectively visualize data we need to first export it to SQL and the run our viz tools due to the reason above.
- Treasure Data allowed us to start measuring metrics in our apps which we never been able to before.
- I would say that at this point Treasure Data is most likely ROI positive, although we haven't done extensive analysis.
- We schedule a lot of our data aggregation in Treasure Data and push the data to MS SQL for faster analysis and visualizations.
- We are looking into utilizing Treasure Data's API to do two-way communication and data passing.
- Ad Hoc Queries
- Aggregation of Daily KPIs
- Integration with various other tools
- Two-way communication with Treasure Data's API
- Product Features
- Product Usability
- Implemented in-house
- Naming conventions in the mobile SDK were not followed, so column names in the tables can be different across games.
- Running AdHoc Presto queries on relatively small data sets.
- Scheduling queries and workflows are very easy.
- Running Hive queries on very large data sets.