Daily Stats Summary Analysis and Metrics

The Daily Stats Summary Report from Guru allows you to track the evolution of your business performance over time, consolidating essential sales metrics by date.

With it, you can quickly view indicators such as sales volume, quantity of products sold, and financial values, facilitating comparative analyses and decision-making.

How to access the Daily Stats Summary Report?

To view the report, you must access Guru's side menu, click on Reports and then, Daily Summary. After the page loads, the listing will display all sales organized by date, divided into the categories all sales, valid and refunded.

In addition to direct consultation on the platform, you can also configure automatic receipt of this information by email, with daily sending of your account statistics. To activate this receipt, locate the My Profile icon in the upper right corner of the page in Guru's admin. In the Detailsection, under Email receipt, select the option Daily Statistics.

On this page:

• Overview of the Daily Stats Summary Report

• Calculation of values in the Daily Stats Summary Report

• Performance analysis and comparison

• Best practices for analyzing and interpreting the Daily Stats Summary

Overview of the Daily Stats Summary Report

The Daily Stats Summary Report presents a consolidated view of sales organized by date, allowing you to track business performance over time.

Each line of the report corresponds to a specific day and gathers the main sales indicators for that period.

The data can be viewed in three categories, organized according to the transaction status. Each of them presents the same indicators, which consider the data for the visualized date, allowing consistent comparisons between different scenarios.

Calculation of values in the Daily Stats Summary Report

The indicators presented in the daily Sales Summary report are calculated exclusively based on sales related to each day displayed in the report.

To correctly interpret the data, it is important to understand how each metric is formed and what criteria define the inclusion of sales in each category.

General calculation rules

All report indicators are calculated based on events occurring on the displayed date.

For the categories “All” and “Valid”, the sale creation date is always considered; for the category “Refunded”, the reference becomes the date the refund was made, instead of the creation date.

The values displayed vary according to the selected category, as each applies specific criteria for including sales:

1. The category “All” includes all sales created on the day, regardless of status;

2. the category “Valid” considers only sales created on the day that were approved; and

3. the category “Refunded” includes sales whose cancellation occurred on the day, regardless of the date they were originally created.

As a consequence, the same sale can impact different days within the report, depending on the category analyzed.

Percentage variation

In addition to absolute values, the report also presents the percentage variation of the indicators in relation to the previous day.

The calculation for this variation always considers the immediately preceding day as the basis for comparison.

Example: if the total sales (gross value) was R$ 100 on one day and R$ 120 on the next day, the displayed variation will be +20%.

This logic applies to all report indicators (number of sales, quantity of products, gross total, and net total).

How to interpret the Daily Stats Summary Report in practice

See an example of sales made below. In the table below, we present a fictitious example of sales made to illustrate how the data is displayed in the report.

For this analysis, observe the sale status, creation date, refund date (if any), quantity of products, and gross and net values:

The table above represents individual sales, while the table below shows how these same sales are consolidated in the daily Sales Summary report.

In other words, the values displayed in the report are the result of the sum and application of calculation rules on the sales data presented previously.

Based on these sales, the report presents the following results by day and by category:

This example demonstrates how the same sale can impact different days in the report, depending on the category analyzed and the date considered (creation or refund).

Performance analysis and comparison

The Daily Stats Summary Report allows you to track how results evolve over time, facilitating comparison between different days and periods.

You can track this evolution based on:

1. comparison with the previous day;

2. percentage variation of indicators; and

3. identification of growth or decline trends.

This reading is essential to validate sales strategies, identify performance fluctuations, and make quick data-driven decisions.

Best practices for analyzing and interpreting the Daily Stats Summary

To extract the maximum value from the Daily Stats Summary Report, it is important to use the data not only for monitoring, but mainly as a basis for decision-making and optimizing results.

1 - Use the correct category for each analysis

To correctly interpret the report data, it is important to analyze each category according to your analysis objective, considering the value calculation rules presented in the report.

1. If you want to evaluate the actual revenue of the business, consider only approved sales (valid sales);

2. If you want to analyze the total volume of transactions and identify conversion opportunities (such as pending payment sales), consider all sales; and

3. If you want to monitor losses and identify possible operational problems, consider refunded sales.

2 - Identify sales recovery opportunities

In the “All” category, you visualize sales that were not completed, such as generated and unpaid boletos, generated and unconcluded Pix, and pending transactions. These sales represent direct recovery opportunities within Guru.

Actions that can be taken based on recovery opportunities

• In order to re-engage customers from uncompleted purchases, it is possible to use lead management to identify contacts with pending sales and resend the payment link via email or WhatsApp, encouraging the completion of the purchase;

• In order to automate follow-ups, configure automations to trigger communications after the generation of uncompleted sales, thus ensuring contact at the right time, without the need for manual action;

• In order to increase the conversion of pending sales, it is possible to segment leads based on the sales status and create specific sales recovery;campaigns;

• Based on reducing abandonment due to forgetfulness, send payment reminders and schedule automatic sends with a deadline (for example, boletoexpiration);

• Based on applying conversion triggers, stimulate quick customer decision, adjusting campaigns with urgency and scarcity; and

• In order to increase conversions, use integrations with email or WhatsApp tools, where it is possible to expand the reach of recovery actions.

3 - Monitor performance drops

Drops in sales quantity or revenue can indicate problems in active campaigns, reduced traffic, and low conversion.

How to act in common scenarios, such as

• Drop in sales quantity, with stable traffic indicates a reduction in the conversion rate - review the sales page (offer clarity, value proposition, and proofs), validate recent changes, and test variations in offer, price, or communication;

• Drop in sales volume and traffic indicates problems in campaigns or acquisition channels - review active campaigns and budget, reactivate campaigns with better history, and validate channels such as affiliates, email, and ads;

• Quantity of sales started but not completed indicates payment abandonment
  - access pending sales and resend the payment link, identify customers in lead management and configure recovery automations; and

• Drop in total sales value, even with stable volume indicates a reduction in average ticket - review offers, combos, and strategies such as upsell and order bump.

4 - Monitor the relationship between gross and net value

You can identify out-of-pattern variations by analyzing the gross and net values displayed in the Daily Stats Summary Report. The difference between these values represents costs applied to sales, such as processing fees, affiliate commissions, and other charges. Variations in this relationship can indicate relevant operational changes.

By analyzing these indicators, you can:

• compare values over the days to identify fluctuations, verify if these variations coincide with campaigns, new affiliates or changes in payment methods, and identify possible margin reductions even with increased sales.

In Guru, this analysis can be deepened by:

• analyzing the sales details to identify the impact of fees and commissions; using affiliate management to track commissions applied to sales and observing how different payment methods influence the final result.

5 - Analyze refund behavior

The increase in refunds may be related to misalignment in the offer; unmet expectations and after-sales problems.

See possible causes for this and how to use Guru's management tools to solve these cases:

1. Offer misalignment: the customer buys with an expectation different from what is delivered - to solve, review the sales page to ensure that the promise is clear and consistent with the delivery.

2. Unmet expectation: the product or service does not correspond to what the customer expected -adjust communication to better detail what is included and the offer conditions; and

3. After-sales problems: difficulties after purchase increase the chance of cancellation
   - review the delivery flow and improve customer support at this stage.

With Guru's tools, it is possible to:

• monitor the evolution of refunds in the report identifying increases and patterns over time;

• analyze sales individually to identify products or offers with a higher cancellation rate;

• use automations to improve communication in after-sales; and

• manage leads and customers to monitor behavior after purchase.

6 - Identify opportunities to increase ticket size

Monitor the quantity of products per sale to identify the performance of upsells and acceptance of order bumps.

To do this, you can observe if customers are buying more than one product per sale, identify which offers have greater acceptance, such as combos, for example, and compare periods to validate the impact of new strategies.

Among the strategies you can apply are:

1. Order bump (additional offer at checkout) - allows you to add a complementary product at the time of purchase - to apply an order bump, you must configure a complementary product directly in the offer.

2. Upsell (offer after purchase) - presents a new offer immediately after completing the purchase - to configure an upsell, you must configure an additional offer after payment.

When analyzing your results, avoid analyzing isolated days - identify patterns of growth or decline and observe recurrent fluctuations. This way you maintain focus on consistent trends and comparisons, reduce punctual distortions, and can interpret results with greater precision.

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