How to visualize Ploomes data in Tableau? Kondado provides a direct connection that replicates your CRM, sales, and automation data into Tableau without complex setup or intermediate databases. Business teams can access client information, deal stages, and sales performance metrics to create interactive dashboards that support strategic decisions. The platform handles the data replication automatically, ensuring your visualizations always reflect current pipeline stages, proposal statuses, and client interactions. Whether you track complex B2B sales cycles or manage quotes and contracts, Kondado makes Ploomes data accessible for analysis without requiring technical expertise or manual exports.
Kondado connects Ploomes to Tableau via a direct integration that updates data on a configurable schedule ranging from every 5 minutes to daily, enabling near-real-time sales analytics without technical infrastructure.
Each item below is automatically replicated by Kondado from Ploomes into Tableau — no schema setup, no manual mapping.
36
available pipelines
275
extractable fields
∞
Auto-refresh
Available integrations
Positions
Table contains information about positions, including id, name, and associated user profile.
Cities
Table presents data about cities, including id, name, and associated state.
Cities: states
Table provides information about states related to cities, including id and state name.
Cities: countries
Table contains data about countries associated with cities, including id and country name.
Clients (companies and individuals)
Table presents information about clients, including id, name, email, and status.
Clients: ratings
Table provides data about client ratings, including id and rating name.
Clients: sources
Table contains information about client sources, including id and source name.
Clients: relationships
Table presents data about relationships between clients, including id and relationship type.
Clients: segments
Table provides information about client segments, including id and segment name.
Clients: status
Table contains data about client status, including id and status description.
Client Types
Includes fields such as id and name, allowing categorization of clients into different types for better management.
Departments
Contains fields such as id and name, facilitating the organization and structuring of departments within the company.
Documents
Presents fields such as id and filename, allowing management of documents associated with clients and sales.
Currencies
Includes fields such as id and currency, essential for financial management and conversion of values in different currencies.
Deals
Has fields such as id, ordernumber, and amount, allowing tracking and analysis of completed sales.
Deal Stages
Includes fields such as id, name, and ordination, which help define the progression of deals through different stages.
Deal Funnels
Presents fields that allow visualization and management of different sales funnels and their stages.
Deal Loss Reasons
Includes fields such as id and name, helping to identify and analyze the reasons why deals were not closed.
Deal Status
Presents fields that indicate the current status of deals, allowing better tracking of progress.
Products
Contains fields such as id and name, essential for managing and categorizing the products offered.
Product Groups
Includes fields such as id, name, and description, allowing for the categorization of products into specific groups for better organization and analysis.
Product Families
Contains fields such as id, name, and group_id, facilitating the organization of products into related families for more efficient management.
Proposals
Presents fields such as id, filename, and approval status, allowing for the management and tracking of proposals sent to clients.
Proposal Products
Includes fields such as proposal_id, product_id, and quantity, detailing the products included in each proposal for accurate tracking.
Proposal Approval Status
Contains fields such as id and name, allowing for the categorization of different approval statuses for submitted proposals.
Interaction Records
Includes fields such as id, type, and date, recording interactions made with clients for relationship analysis.
Tasks
Presents fields such as id, name, and status, allowing for effective management of tasks assigned to users within the platform.
Task Recurrence Intervals
Contains fields such as id and frequency, defining the periodicity of tasks for better work organization.
Task Types
Includes fields such as id and name, categorizing tasks into different types for easier management.
Email Reminder Types
Presents fields such as id and description, allowing the configuration of different types of email reminders for users.
Users
Table contains information about users, including fields such as id, name, and email, as well as role id and profile id.
User Suspension Reasons
Table lists the reasons for user suspension, with fields such as id and name, along with comments on the suspension.
User Profiles
Table presents user profiles, including fields such as id, name, and avatar url, along with phone and user language.
Sales
Table contains data on sales, including fields such as id, order number, date, customer id, and total sale amount.
Sales Stages
Table lists sales stages, with fields such as id, name, icon, and ordination of stages within a funnel.
Sales Products
Table contains information on sold products, including fields such as order id, product id, and quantity, along with unit price and discount.
Combining Ploomes with Tableau transforms raw CRM data into actionable business intelligence. By replicating pipelines such as Deals, Clients, and Sales Stages, managers can visualize conversion rates across different funnels, identify bottlenecks in complex sales cycles, and analyze client segmentation effectiveness. Sales directors can track proposal approval workflows alongside deal loss reasons to optimize their strategies, while operations teams monitor task completion rates and user productivity metrics. This connection empowers non-technical teams to explore relationships between client sources, ratings, and final sales outcomes through intuitive drag-and-drop visualizations that update automatically.
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How to create Ploomes dashboards in Tableau
Visualize your data automatically — no spreadsheet exports or custom scripts.
1
Connect Ploomes as your data source
Authenticate your Ploomes account in Kondado and select which pipelines such as Deals, Clients, or Sales Stages you want to replicate.
2
Select Tableau as your destination
Choose Tableau to receive your structured Ploomes data, with the option to also send copies to BigQuery or PostgreSQL for storage.
3
Build dashboards and set refresh schedule
Create your sales reports in Tableau and configure automated updates to run every 5 minutes, hourly, or daily based on your business needs.
Try out all the features for free for 14 days
Access Ploomes data in Tableau and combine it with dozens of other data sources
If the source you want is not listed, drop us a chat message. We love to add new sources!
Answers about visualizing Ploomes data in Tableau automatically
How do I connect Ploomes to Tableau without technical setup?▼
Start by adding Ploomes as a data source in your Kondado account, then authenticate with your existing credentials. Select Tableau as the destination and choose which pipelines to replicate, such as Deals, Clients, or Sales Products. The connection works through Kondado's direct integration, so you do not need to configure APIs, manage servers, or write code.
What sales KPIs can I track in Tableau using Ploomes data?▼
You can monitor conversion rates between Deal Stages, analyze win rates by Client Segments, and track average sales cycles from proposal to closure. Compare performance across different Product Families or analyze deal loss patterns by region and team member. These metrics help identify which sales activities drive revenue and where processes need optimization.
How often does Ploomes data update in Tableau?▼
Kondado offers configurable refresh schedules ranging from every 5 minutes to daily updates, depending on your business needs. You can set different frequencies for different pipelines, ensuring high-priority sales data refreshes frequently while historical records update less often. This keeps your Tableau reports current without overwhelming your system with unnecessary updates.
Can I share Ploomes dashboards with my sales team?▼
Yes, once you build dashboards in Tableau, you can distribute them to stakeholders through Tableau Server, Tableau Online, or exported PDFs and images. Team members can view interactive reports showing their individual performance, pipeline contributions, and client interaction histories without needing access to the underlying Ploomes CRM. This ensures everyone works from the same data insights.
Do I need to know SQL to build Ploomes reports in Tableau?▼
No, Kondado delivers structured data that Tableau recognizes immediately, allowing you to build visualizations using drag-and-drop functionality. The pipelines arrive as organized datasets containing fields like deal amounts, client names, and task statuses, ready for immediate chart creation. Business users can create sophisticated sales analyses without writing queries or managing database connections.
What types of sales funnels can I analyze with Ploomes data?▼
You can examine multiple Deal Funnels simultaneously to compare performance across different product lines, client types, or sales regions. Track how proposals move through approval stages, analyze where deals typically stall using Deal Loss Reasons, and monitor progression through Sales Stages to forecast revenue accurately. This multi-funnel view helps optimize complex B2B sales processes.
Can I send Ploomes data to other business intelligence tools besides Tableau?▼
Yes, Kondado allows you to replicate Ploomes data to multiple destinations simultaneously, including Power BI, Looker Studio, Google Sheets, and BigQuery. This flexibility lets different teams use their preferred analytics tools while working from the same underlying Ploomes data. You can also send data to PostgreSQL, MySQL, or Amazon S3 for storage and further processing.
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