With regards to business seals, most of the success relies upon how an employee organizes and their prospective customers (Sale Leads). Good Lead Management helps to improve an employee’s capability to accomplish all their Sales targets by using the Sales Pipeline.

Nowadays, each organization or business needs to install an appropriate CRM (Customer Relationship Management) tool, such as Pipedrive, that has an in-built Sales Pipeline feature that helps ensure an employee can track each of their potential customers. Tableau is a Visual Analytics Engine that simplifies the creation of interactive visual analytics in the form of dashboards. These dashboards facilitate the conversion of data into intelligible, interactive visualizations for non-technical analysts and end-users.

In this article, you will gain information about Tableau Pipedrive Integration. You will also gain a holistic understanding of Pipedrive, its key features, Tableau, its key features, the need for Tableau Pipedrive Integration, and different methods of Tableau Pipedrive Integration. Read along to find out in-depth information about Tableau Pipedrive Integration.

What is Pipedrive? 

Tableau Pipedrive Integration: Pipedrive Logo| Hevo Data

Pipedrive is a CRM tool that helps manage deals and works or function as an account-management tool with the capability to help with advertising and the complete Sales procedure. A Pipedrive automatically tracks and sorts out calls and emails and synchronizes schedules across different gadgets. One ability that makes most SMBs (Small to Midsized Businesses) attractive or appealing about Pipedrive is its capability to visualize the entire Sales procedure from beginning to end. This can help improve an employee’s efficiency or productivity level and avoid second-guessing inside teams, which is usually the main reason behind the failure of customer relationship management.

Pipedrive offers various features to assist organizations in organizing their teams and clients’ information. For instance, contact timelines assist Sales representatives in seeing why they need to contact next and when they should conduct a follow-up. The smart contact data feature helps businesses obtain public information regarding their clients so that they could get an entire picture about their leads and current and potential clients.

Pipedrive also helps merge contacts so that only one Sales representative is working on a particular lead. It also offers advanced user permissions to limit what clients can see and change. It can also help businesses ensure that they comply with GDPR (General Data Protection Regulation). General Data Protection Regulation imposes limitations regarding how organizations currently operating in different industries can manage and store their clients’ personal information. Pipedrive helps to ensure that clients’ personal data is stored safely and that third parties cannot view, access, or modify it.

Key Features of Pipedrive

Some of the most crucial features of Pipedrive are: 

1) Privacy and Security

Pipedrive helps to ensure data related to prospective clients is saved in a secured environment. It also helps to maintain privacy and assure data transparency. Several interactions need a secure environment not just for privacy but also to improve accuracy when it comes to performance. 

2) Various Integrations

Businesses can integrate several third-party applications alongside Pipedrive to increase Sales or produce invoices. This is a normal prerequisite, particularly when a company’s management is trying to access customers’ information and make changes using their mobile phones. Pipedrive also permits employees to utilize their current set of applications that they prefer in collaboration with it. In this article, you will learn more about Pipedrive Gmail Integration.

3) Customizable Templates

Using Pipedrive, employees can make their own templates and insert pictures and context to improve their Sales Funnel. A custom format or template can also help employees tweak metrics that they need to observe when comparing. 

4) Chatbot

A chatbot acts like a virtual assistant or helper so that clients do not need to wait for emails or calls to get their doubts or questions cleared. Although the expertise area of a chatbot would be restricted to some pre-programmed topics, still creating a dedicated chatbot with some fundamental provisions is always an excellent touch. 

5) Active Reporting

Pipedrive also helps to provide greater insight and active reporting. Measuring a company’s performance based on a specific set of objectives becomes crucial to creating an optimized Sales technique.  

6) Advanced Automation

One of the main reasons businesses prefer to use Pipedrive is that it helps automate different Sales operations.

To explore more about Pipedrive, over here.

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What is Tableau? 

Tableau Automation: Tableau logo| Hevo Data

Tableau is a modern Data Analytics and Business Intelligence platform. It is an easy-to-use tool, hence, it offers a smooth experience to its users. Some of Its amazing features include real-time analytics, quick responsiveness, and interactive dashboards. 

It also offers simple yet appealing graphics/visualizations that you can use to present your data pictorially. It comes with all the features needed for data extraction, data processing, and generating reports and dashboards. 

It also offers a drag-and-drop functionality that makes it faster than other BI tools. It is also a very scalable tool, which gives it the capability to adapt to both individual and enterprise needs. You can also connect it to multiple data sources without the need to purchase a license. It is mobile compatible and it comes with an online version. 

It can be used by all kinds of users and no specific skill or knowledge is needed to work with the tool. Users from any department in your company can use it for Data Analysis and Data Visualization. 

Key Features of Tableau

Tableau is a powerful tool and is widely used by a lot of industries. To understand Tableau better let’s look at some of its key features:

1) Supports Multiple Data Sources

Since every task is performed on data in Tableau, it allows you to integrate your data from a large variety of data sources like:

  • Microsoft Excel
  • CSV files
  • MS SQL Server
  • Oracle
  • IBM DB2
  • Google BigQuery
  • Windows Azure
  • ODBC/JDBC, etc

You can make use of these integrations to stream your data to Tableau and analyze it seamlessly.

2) Houses a Wide Range of Visualizations

Tableau also provides a large number of simple tools for its users (both for technical and non-technical people) and empowers them to create different types of visualizations using their data. You can use these tools and create simple or complex visualizations using Tableau. Its key visualizations include:

  • Scatter plot
  • Line plot
  • Pie Chart 
  • Bar Chart 
  • Bullet Chart
  • Highlight Tables
  • Gantt Chart
  • Boxplot, etc. 

Tableau’s Map features allow you to visualize your data on a geographical map. It is very useful if your data needs to be categorized region-wise or across various countries to help you analyze the performance of each region.

Tableau Pipedrive Integration -Tableau Visualisation| Hevo Data
Image Source

3) Allows Data Filtering

With the help of Tableau, you can filter data from a single source or multiple sources. But the only condition that needs to be satisfied for filtering data from multiple Data Sources is that the data must have the same dimensions. Once this is satisfied, Tableau automatically updates the required changes to all your worksheets using the same Data Sources and the same filters that you set previously.

4) Dynamic and Real-time Dashboards

Tableau Pipedrive Integration -Tableau dashboards| Hevo Data
Image Source

You can build dynamic and interactive Dashboards using Tableau. Building Reports and Dashboards is made very simple by Tableau. You can make them more informative by adding colorful charts and diagrams. Using these real-time Dashboards, you can monitor everything in absolute depth for your organization. Tableau also houses a feature that allows you to share your Dashboards and Reports with other employees in the organization.

5) Powerful Collaboration

Every person can work a lot more efficiently if they understand their data and make informed decisions which are critical to success in any organization. Tableau was initially built to enable collaboration among employees. Using Tableau, all the members in a team can share their work, make follow-up queries with fellow peers, and share visualizations with any employee in the organization, allowing them to gain valuable insights easily.

Tableau gives its users the ability to work and understand the data they need from web editing and authoring to Data Source recommendations. You can easily publish your Dashboard to Tableau Server or Tableau Online within seconds and as a result, everyone in your organization can see your insights, ask various questions, and make the right decisions.

What is the Need for Tableau Pipedrive Integration?

By conducting Tableau Pipedrive Integration, you will be able to use Pipedrive data inside Tableau. Through this, you can get valuable insights and gain previously unknown knowledge about your sales processes. You can also visualize your sales team’s progress, identify bottlenecks and strengths, and take appropriate measures to ensure that you meet and exceed your targets. This Tableau Pipedrive integration also lets your sales processes interact and cooperate with your other business functions. 

Methods of Tableau Pipedrive Integration

There are multiple methods to achieve integration between Tableau with Pipedrive, and we will discuss them one by one.

Method 1: Tableau Pipedrive Integration via PostgreSQL

This method is to extract your Pipedrive data via the APIs provided by Pipedrive, load those results into a database, e.g. a PostgreSQL instance, and then connect that instance with Tableau. 

Step 1: Pipedrive to PostgreSQL 

Your Pipedrive data may not necessarily be single-valued or relational. There could be fields that would be multi-valued and could have variable lengths for different entities. e.g. An “address” column may contain 3 addresses for 1 client whereas just 1 address for another client. 

Moreover, these addresses could vary in length and constituent parts, like an address could have 2 address lines, whereas some other addresses might have a single line and might miss the ZIP/Postal code. Your data values in Pipedrive could be multi-valued as well as hierarchically structured.

Here, you will be using PostgreSQL, as it’s an ORDBMS (Object-Relational Database Management System) that has excellent inbuilt support for flexible and extendable types like JSON, Arrays, and Enumerations, etc. 

The steps followed to first move data from Pipedrive to PostgreSQL in the process of setting up Tableau Pipedrive Integration are as follows:

  • The first step would be to create a schema in PostgreSQL such that the schema can ingest the data from Pipedrive. This schema should have a combination of tables with appropriate data types ( Integer, Float, JSON, String, etc.) to house each of the Pipedrive datums. 
  • You can create a table in PostgreSQL as given below:
CREATE TABLE activities (
activity_id Integer SERIAL, 
success BOOLEAN 
data JSON ,  // Json data about Description/Subject/Meetings/Location/Assignees/Due_date etc. 
related_objects JSON, // related Users/Organization/Person/Deal etc. in Json format 
additional_data JSON, 
created_at TIMESTAMP WITH TIMEZONE 
); 
  • To get all “Activities” assigned to a particular user, you must fire an API call to “GET/v1/activities/{user_id}“. For this, PostGreSQL has a library to GET/POST data to URLs, called urllib2.
import urllib.parse
import urllib.request

"host" = "api.pipedrive.com" 
values = {"base_path" : "/v1", 
          "api_token" : "hg567JKNM_0ghTY67",
          "scheme" : "https" }

data = urllib.parse.urlencode(values)
data = data.encode('ascii') # data should be bytes
req = urllib.request.Request(host, data)
with urllib.request.urlopen(req) as response:
   result_json = response.read()
  • You will receive an aggregate JSON object, named result_json in this example, which will have all details of matching activities. 
  • Next, create a PostgreSQL json array using this aggregate JSON object using jsonb_agg(result_json).
  • Then formulate a function that can insert multiple rows into PostgreSQL such as:
CREATE OR REPLACE FUNCTION insertdata(json  result_json) ) 
  RETURNS VOID AS 
$$ 
 INSERT into activities values ( 0, json_to_recordset(result_json) ) ; 
$$ 
LANGUAGE sql STRICT; 
  • Generally, you can use 0 to allow PostgreSQL to generate auto-increment (SERIAL) integers which would act as unique IDs for each record. 
  • Similarly, you would need to create tables for User/UserSettings/Teams/Subscriptions/Product/ProductSettings/Persons/PersonSettings/Organizations/OrganizationFields/OrganizationRelationships etc., as well as for Notes/Leads/Calls/Deals/Files/Billing etc. 
  • Then make appropriate API calls to fetch the most recent data and populate these tables. 
  • Now, you will also need to run this periodically, and update/insert any new data that has been recorded by Pipedrive since your last run. 

Most people would add timestamps to each data row being entered in PostgreSQL to mark pre-existing data, on every new run of the program. 

Step 2: Connect PostgreSQL to Tableau

The steps followed to move data from PostgreSQL to Tableau in the process of setting up Tableau Pipedrive Integration are as follows:

  • Go to your Tableau instance, click on the Connect” menu, and a list of available connectors appears. 
Tableau Pipedrive Integration: Connect from Tableau| Hevo Data
Image Source: Self
  • From this list select “PostgreSQL“, and a popup menu appears. 
  • Provide your PostgreSQL server access details and click the “Sign In” button.
Tableau Pipedrive Integration: PstgreSQL Database| Hevo Data
Image Source: Self
  • A live connection will be established between your PostgreSQL database and Tableau instance, you can now start visualizing your data analytics in Tableau.
Sync Data from Pipedrive to BigQuery
Sync Data from Pipedrive to Snowflake
Migrate Data from Pipedrive to Redshift

Method 2: Tableau Pipedrive Integration via a Data Warehouse

In this solution of setting up Tableau Pipedrive Integration, you extract data from your Pipedrive instance, store it in your Data warehouse, and then connect your data warehouse to Tableau. 

The steps are as follows:

Step 1: Choose your Data warehouse as per your needs

You can choose any Data Warehouse as per your requirements and choice. It can be Azure, BigQuery, Redshift, Snowflake, or any other Data warehouse solution.

Depending on the methods provided by your data warehouse, you can connect it with Pipedrive to fetch your data. You can use Hevo Data for this. In just 2 steps, Hevo will help you move your data from Pipedrive to your data warehouse. As it also comes with transformation capabilities, you can easily modify your data as required.

Step 2: Connect Tableau & the Data Warehouse 

The steps followed to connect tableau and your preferred Data Warehouse in the process of setting up Tableau Pipedrive Integration are as follows:

  • Make Tableau read data from your data warehouse, and load your Pipedrive data from there. You can also pay for some available connectors in the Pipedrive marketplace.
  • Generate your reports and analytics in Tableau. 

Conclusion

In this article, you have learned about Tableau Pipedrive Integration. This article also provided information on Pipedrive, its key features, Tableau, its key features, the need for Tableau Pipedrive Integration, and different methods of Tableau Pipedrive Integration.

For a step-by-step approach to integrating Pipedrive with other tools, visit our guide on Pipedrive integrations. It provides expert advice and best practices for successful integration.

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Share your experience of understanding Tableau Pipedrive Integration in the comment section below! We would love to hear your thoughts.

Pratik Dwivedi
Technical Content Writer, Hevo Data

Pratik Dwivedi is a seasoned expert in data analytics, machine learning, AI, big data, and business intelligence. With over 18 years of experience in system analysis, design, and implementation, including 8 years in a Techno-Managerial role, he has successfully managed international clients and led teams on various projects. Pratik is passionate about creating engaging content that educates and inspires, leveraging his extensive technical and managerial expertise.

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