Sankey Diagrams: Illuminating Multi-Channel Sales for Data-Driven Success

In today's digital age, companies must optimize their sales strategies across multiple channels. Let's explore how data analysis and Sankey diagrams can provide valuable insights into the effectiveness of web, phone, and mobile channels for policy purchases. Let's take a fictitious insurance company as an example.

Understanding Sankey Diagrams

Sankey diagrams are a specific type of flow diagram, named after Irish Captain Matthew Henry Phineas Riall Sankey, who first used this type of diagram in 1898 to show the energy efficiency of a steam engine.

Key features of Sankey diagrams include:

1. Flows: Represented by arrows or bands, these show the movement of resources (in our case, customers) through the system.

2. Nodes: These are the points where flows converge or diverge, representing different stages or categories in the process.

3. Proportional Visualization: The width of the flows is proportional to the quantity being transferred, making it easy to spot significant patterns at a glance.

4. Color Coding: Different colors can be used to distinguish between different types of flows or to highlight specific paths.

In this example of ours, insurance sales, Sankey diagrams can vividly illustrate customer journeys across various channels, highlighting conversion rates and drop-offs. They're particularly useful for:

• Visualizing complex processes with multiple inputs and outputs
• Identifying inefficiencies or bottlenecks in a system
• Comparing actual versus target performance across different channels
• Communicating complex data relationships to non-technical stakeholders

Gathering Real-World Data

Before we dive into creating a Sankey diagram, let's consider how an any company would gather the necessary data in a real-life enterprise scenario:

1. Website Analytics: Tools like Google Analytics or Adobe Analytics provide data on website visitors, conversion rates, and drop-offs.

2. Call Center Software: Systems such as Salesforce Service Cloud or Genesys track phone inquiries, call durations, and conversion rates.

3. Mobile App Analytics: Platforms like Firebase or Mixpanel offer insights into mobile app usage, user journeys, and conversion rates.

4. CRM System: A customer relationship management system like Salesforce or Microsoft Dynamics consolidates data from all channels, tracking leads and conversions.

5. Policy Management System: The company's core insurance platform provides data on actual policy purchases across all channels.

These systems typically feed into a data warehouse or lake, where data analysts can access and analyze the information.

Analyzing Multi-Channel Sales Data

Let's use Python to analyze our multi-channel sales data:

What code does above?:

1. We import pandas for data manipulation.

2. We define lists for channels, total visitors, and drop-off rates.

3. We calculate purchases and drop-offs using list comprehensions.

4. We create a pandas DataFrame to organize our data.

5. Finally, we print the DataFrame to see our results.

This analysis yields:

Bringing Data to Life with a Sankey Diagram

Now, let's create a Sankey diagram to visualize these flows using Plotly:

What the above code does?:

1. We import plotly.graph_objects for creating the Sankey diagram.

2. We define labels for each node in our diagram.

3. We specify source and target nodes for each link. For example, source = [0, 0, 1, 1, 2, 2] and target = [3, 4, 3, 4, 3, 4] mean that node 0 (Website) connects to nodes 3 (Policy Purchase) and 4 (Drop-offs), and so on.

4. We define link_values, which determine the thickness of each flow.

5. We create the Sankey diagram using go.Sankey(), specifying node and link properties.

6. We update the layout with a title and display the diagram.

Following is the the digram we get after running the code.

Interpreting the Sankey Diagram

The resulting Sankey diagram provides a powerful visual representation of our multi-channel sales funnel:

1. The thickness of each flow instantly communicates the volume of customers moving through each channel.

2. We can clearly see the split between successful policy purchases and drop-offs for each channel.

3. The mobile app, despite having the lowest initial visitors, shows the highest conversion rate to policy purchases.

Actionable Insights from the Sankey Diagram

Based on this visualization, insurance leaders can derive several key insights:

1. Website Optimization: The thick drop-off flow from the website indicates a need for user experience improvements.

2. Phone Channel Effectiveness: The relatively thin drop-off flow from phone interactions suggests this is a strong channel for conversions.

3. Mobile App Potential: The minimal drop-off from the mobile app highlights its effectiveness, suggesting potential for increased investment in this channel.

4. Cross-Channel Strategies: The diagram illustrates opportunities for guiding customers between channels to maximize conversion rates.

The Impact of Sankey Diagrams on Insurance Sales Strategy

Sankey diagrams offer companies a powerful way to visualize and understand their multi-channel sales performance. By transforming complex data into an intuitive visual format, these diagrams enable leaders to:

1. Quickly identify strengths and weaknesses in each sales channel

2. Make data-driven decisions about resource allocation

3. Develop targeted strategies to improve conversion rates

4. Communicate complex sales funnel dynamics to stakeholders effectively

In today's competitive market, the ability to gain clear, actionable insights from data is crucial. Sankey diagrams provide exactly that – a clear, visual path to optimizing multi-channel sales strategies and driving business growth.

By regularly leveraging tools like Sankey diagrams to analyze and visualize their sales data, companies can stay agile, responsive, and ahead of the curve in meeting evolving customer preferences and behaviors.

The combination of Python for data manipulation and Plotly for visualization offers a powerful, flexible toolkit for creating these insightful diagrams, enabling data analysts and business leaders to transform raw data into strategic action.