Zia Insights

Deciphering insights in the reports or visualizations could be tedious and time intensive. Zia Insights, a generative AI tool powered by Zoho Analytics, examines all the data points in the report and deploys advanced analytical methods and ML algorithms to bring out the insights, that may not be evident at first sight. These insights facilitate multi-dimensional interpretation of data.

Zia Insights provides answers (narratives) to the various questions that arise while trying to interpret data and directs towards meaningful conclusions by offering Descriptive, Predictive, and Diagnostic insights.

• Descriptive insights explain what has happened with a specific measure or metric, providing a clear overview of past performance and trends.
• Predictive insights explain how a trend has been for a metric and how likely it is to change.
• Diagnostic insights focuses on Why something happened. It helps understand the causes of events by identifying the factors that impact and contribute to specific outcomes. Zia insights uses an ML technique to identify the key Drivers that have a significant impact on the outcome and different statistical methods for explaining the factors.

Access to Zia Insights

The Account, Organization and the Workspace admins can access Zia Insights. They can also grant permission to other users while sharing the reports and dashboards, or when they create specific roles.

Types of Narratives

Zia Insights enables users to understand the relationships (correlations) in the data, highlights the key points like trends, outliers, and top contributing measures, and also predicts future outcomes based on the past data. These insights are available as Textual and Visual Narratives

Textual Insights: Provides story-like explanations of the key points in the report in simple language, making it easier for non-technical users to comprehend the data insights. Textual Insights can also be easily added to the presentations for effective data storytelling.

Visual Insights: It is a visual depiction of the textual insights. It analyzes each element in the report and selects the most suitable and intuitive visualization to illustrate the key points clearly. It highlights specific sections and pin-points spikes and dips in the data. Visual insights facilitate multi-dimensional interpretations like comparison, contribution, distribution, trends and proportions, all at once. This eliminates the need for creating multiple reports, providing a holistic view of your data in one visualization.

Supported Languages

Zia Insights is available in three languages: English, Spanish, and French. The default language is the one configured with the Zoho Analytics account. Click the Language Settings icon on the right and choose the preferred language from the drop-down.

Invoking Zia Insights

You can invoke the Zia Insights either from the individual report or from reports embedded in a dashboard. 

From Report

Clicking the Zia Insights button at the top-right will get you the automatic insights displayed on the right side of the report. 

From Dashboard

Clicking the Zia icon from the toolbar of a report (embedded within the dashboard) will also get you the automatic insights of the report.

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Customize Zia Insights

Our AI powered analytical assistant, Zia, provides insights across various categories. You can customize and control both the columns (measures and dimensions) and the categories to generate insights that are most specific to your business needs.

Click the Settings icon in the top right corner to customize the Zia Insights settings.

Explain by Column 

This option allows you to choose the important metrics and dimensions columns to be used for generating Zia Insights. It is recommended to choose at least one metric and one dimensional or categorical columns for insights.

1. All the columns used in the report are selected by default.
2. Click Add Column to include the relevant metrics or dimensional columns to be used for generating insights. The selected columns will be used for generating Zia Insights.
   

Insight Categories

Zoho Analytics allows you to choose the type of insights that needs to be generated for reports. It helps you to focus only on the insight that you want. Zia Insights is broadly classified into the following five key areas:

Contribution Analysis

Contribution analysis breaks down the impact and extent of various factors on an overall result. It analyzes the weightage of each factor in relation to a particular outcome. By understanding this, organizations can identify which factors significantly influence results and prioritize their strategies accordingly. 

To generate insights about contribution, at least one measure and one dimension column are required.

Time Series Insights

Time Series Insights analyzes trends and patterns within sequences of data points that are recorded or collected at consistent time intervals. It focuses on interpreting the changes in data over time to uncover valuable insights, such as identifying trends, detecting anomalies, and predicting future outcomes based on historical patterns.

To generate time series insights, at least one time series column like date is required

Comparison between Dimensions

Comparison between dimensions compares the performance of a metric across various dimensions and helps understand how values within each dimension perform relative to one another.

To generate insights based on comparison between dimensions, at least one measure column and at least two-dimensional columns are required.

• Trend across series shows the performance trends of each value within a dimension over time.
• Variance across dimensions shows the degree of variability of categorical values in a dimension over a period of time.

Analysis of Measures

The analysis of measures computes the correlations between measures and their respective proportions. To generate insights for analysis of measures, at least two measure columns are required.

Key Driver Analysis (Diagnostic insights)

Key driver analysis is a machine learning technique that identifies the key factors that significantly influence a target metric and the degree to which these factors impact the outcome (results). It is  a robust method that uncovers the causes behind the observed trends of the target metric.

Components of Key Driver Analysis

Key driver analysis hinges on the following two main components,

Target Metric 

Target Metric is the dependent variable or metric for which you want to assess the different factors that lead to a specific trend. For instance, revenue is a target metric used to evaluate the effectiveness of sales strategies and marketing campaigns.

Influencing Factors

Influencing Factors or key drivers are the independent variables (factors) features that impact the outcome of the target metric. These factors contain information about what affects the trends observed in the data. Influencing Factors can be both quantitative and qualitative.

• Quantitative Factors: Numerical data that can be measured and analyzed statistically. For instance, Advertising Spend is the amount invested in marketing campaigns, which can impact revenue.
• Qualitative Factors: Non-numerical data that provide details about behavior and preferences. For instance, The perception of a brand in the market, which can affect customer loyalty and purchasing behavior.

Information

The selection of factors is critical, as they determine the effectiveness of the analysis. Factors should be relevant, measurable, and able to capture significant variations in the target metric.

Configuring Key Driver Analysis

For key driver analysis, Both measure and categorical fields can be used as influencing factors. A maximum of five dimensions and three measures can be used as factors to analyze how they have influenced the target metric.

1. Click the Settings icon > Zia Insights > Key Driver Analysis.
2. Select the checkbox Show Key Drivers for the Diagnosable Insights.
   
3. Choose a Measure (target) column for which you want to conduct the diagnostic analysis. evaluate the outcome.
   
4. The Show Top N Drivers feature analyzes and highlights the most influential factors from the selected set of factors.
   
5. The Top N Factors option for each dimension will use the top contribution factors within that dimension that are most likely to influence the target metric. By focusing on these top values, the analysis can highlight the key drivers that have the greatest impact on the outcome you are evaluating.
   Click the drop-down icon of any chosen factor to customize its settings.
   • Top Factors: Select the number of top contributing values from each category to analyze their influence on the target metric.
   • Actual Values: Select the values to be considered from each category to analyze their influence on the target metric.A maximum of five factors can be selected.
6. Click Add Column to include more factors for analysis. A maximum of five dimensions and three measures can be used. The Add Explain By column includes all selected columns from the Explain By columns for Key Driver Analysis.
   
7. Once you have configured the settings, Save the reports to view Zia Insights.
    

Interpreting the Results of Key Driver Analysis

Key Driver insights offer valuable analysis for time series trends, helping to identify the underlying factors behind increases or decreases and how the outliers or anomalies affect the results. These insights explain what is driving the changes, making it easier to understand the reasons behind shifting patterns over time.

Viewing Diagnostic Insights

The Diagnostic Insights pane offers a comprehensive details of the Potential Drivers that influence the outcome of the Target Metric and the Possible Reasons that could have contributed to the observed trends in the target metric.

To access the insights, click the Diagnosis icon adjacent to any of the time series insights. 

The diagnostic insights provides the following details

• A visual narrative of what has happened to the target metric, whether increased or decreased, percentage of increase or decrease, and the increase or decrease in value.
• The Top Drivers impacting the target metric with the possible reasons that could have contributed to the observed trends of the target metric.
• The Missing drivers that have not contributed in the past but have contributed positively or negatively to the outcome.
  

Potential Drivers

The Top (potential) drivers section answers the What and provides an overview of the diagnosis in the current state or condition of the target metric.

Possible Reasons

The Why section outlines all the potential reasons behind the observed trend, including detailed impact assessments and the various factors contributing to the current outcome. Click Know more to view the Possible Reasons. For a deeper understanding of the types of insights provided in Key Driver Analysis, refer to the Diagnostic Insights - Explanations section.

The Possible Reasons section lists the following details.

Diagnostic Insights - Explanations (Types)

Key Drivers - Top Contributors or Offsetters

Key Drivers are the top factors that either positively or negatively influence the outcome of the target metric, leading to its increase or decrease in value. This helps understand the causes of what is driving the outcome.

Based on the influence of the factors on the target metric, Top contributors or top off-setters insights are displayed.

• Top contributors are the factors that positively influence the target metric leading to the increase in value. For instance, a 20% increase in marketing spend may result in a 15% increase in sales, showing that marketing efforts are positively influencing sales growth.
• Top off setters are factors that negatively impact the target metric, causing a decrease in its value. For example, a 10% increase in product returns could lead to a 5% decrease in total sales, illustrating that returns are hindering overall sales performance.

Anomalies

Anomaly Insights detect unusual spikes or drops in the target metric that deviate from expected trends.It offers a clear comparison between the expected and observed values of the target metric, emphasizing the deviation percentage to highlight the extent of the difference.
 

Occurrences

Occurrence analysis measures how often specific drivers appear in relation to high or low outcomes in the target metric. It also helps determine how a driver correlates with changes in the target metric. This helps in understanding the significance and impact of each driver over time or across different segments.

Trends and Patterns 

The analysis of trends and relationships between the target metric and influencing measures indicates whether there is an increasing or decreasing trend. It also determines the type of correlation, whether direct or indirect, and provides prescriptive recommendations to sustain or improve the observed trend.

Missing Drivers

Missing Drivers in Key Driver Analysis are factors that had no measurable impact in the previous period but began contributing positively or negatively in the current period. These drivers highlight the emerging influences that have shifted from being negligible to having a meaningful effect on the target metric. 

Zia Insights takes into consideration the drivers or factors that could affect the target metric and gives the type of impact it exerts on the target metric.

• Positive Impact: A factor is said to have a positive impact if it had no contribution in the previous period but has positively contributed in the current period, driving overall growth.
• Negative Impact: A factor is said to have a negative impact if it had no impact in the previous period but is now causing a decline in the outcome of the target metric.
   

Explain Data - Zia Insights

The Explain Data - Zia Insights feature provides information related to the selected data point in the report. This helps in identifying significant changes or anomalies in the data.

For example, for a chart that displays the sales across the years by region, enabling Explain Data - Zia Insights for the year 2022 will display insights on sales based on the quarterly breakdown of sales for that year.

Invoking Explain Data - Zia Insights

1. Open the report in view mode.
2. Click any data point in the report and select Explain Data - Zia Insights.
   
   
3. Insights for the selected data point will be displayed in the right.

Explanations

When a data point is selected, insights are provided in the following three ways to help understand its significance.

Insights specific to the Data Point

Insights specific to a data point analyze its trends, identifying whether it is increasing, decreasing, or stable over time. They also highlight the maximum and minimum recorded values, helping to understand its range. Outliers are detected to flag unexpected spikes or drops, while seasonality insights reveal recurring patterns influenced by external factors. 

Data Point Compared with Overall Value

This insight compares the selected data point against the total value. It helps determine its contribution to the overall metric and whether it is above or below the overall trend.
Example: If the selected Ad Spend for Product A is $50,000 and the total ad spend is $500,000, then Product A accounts for 10% of the overall spend.

Data Point Compared with Peer Values

This insight compares the selected data point with other similar data points (peers) within the same dimension. It helps assess whether the selected data point is performing better, worse, or similarly compared to its peers.
Example: If the selected Ad Spend for Product A is $50,000, while Product B has $40,000 and Product C has $60,000, this comparison shows how Product A ranks within its category.