The Customer Dashboard from Guru consolidates information related to your account's buyer base, enabling analyses on recurrence, purchase behavior, retention, and portfolio evolution over time.
The available metrics and graphs allow you to analyze not only how many customers make up your base, but also how much value they generate for the business and how they interact with your offers.
This page presents a comparison of the sections and indicators displayed in the Customer Dashboard, with the objective of:
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facilitating the understanding of each indicator;
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highlighting how metrics relate to each other;
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guiding data analysis for different business contexts.
For this, examples of comparative analysis between metrics and best practices are presented to assist in data interpretation and more strategic decision-making.
On this page:
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Overview of the Customer Dashboard
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Customer base performance
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Customer attribution and behavior
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Comparison between metrics
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Best practices for strategic reading of indicators
Overview of the Customer Dashboard
The Customer Dashboard is composed of different sections that organize the base metrics into complementary views, allowing analysis from customer evolution to purchase behavior and sales origin.
To present the dashboard, we structured the information into two main blocks:
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Customer base performance: gathers indicators related to base composition, value generated by customers, and purchase patterns over time;
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Customer attribution and behavior: presents data on acquisition origin and payment preferences, helping to understand how customers arrive and how they make their purchases.
Each section presents specific metrics and graphs, which can be analyzed individually or combined, according to the analysis objective.
Throughout this page, you will find a detailed explanation of each of these sections, as well as guidance on how to relate the metrics to extract more complete insights about your customer base.
Customer base performance
Guru’s Customer Dashboard provides three sections with indicators that assist in analyzing the performance of your buyer base.
With data from Indicators, Customer Lifetime Value Evolution , and Average Ticket per Customer, you have different perspectives on customer behavior and value generated over time.
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The Indicators section presents the total number of customers in your base, segmenting the quantities into current customers, active, new , and old - these data allow you to monitor the evolution of the base by period and analyze acquisition patterns and purchase recurrence;
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The Customer Lifetime Value Evolution , on the other hand, offers the financial dimension of base performance - the data is displayed through a graph where you can track, by period, the variation in revenue generated by old and new customers.
In addition, the graph highlights the customer lifetime value (LTV), allowing you to visualize the total revenue generated per customer over time;
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Also presented in graph format, the Average Ticket per Customer allows you to track the average value spent by each customer in the determined period - that is, how much, on average, each customer buys from your business within the analyzed interval.
By analyzing these indicators together, it is possible to understand the composition of the customer base and the impact of this base on business results over time, facilitating the identification of growth patterns, retention, and purchase behavior.
The LTV (Customer Lifetime Value) represents the total value a customer generates throughout their relationship with the business, and the Average Ticket corresponds to the average value spent per customer in a given period.
To better understand how these and other indicators are used in sales analysis, access the full article.
Customer attribution and behavior
The Customer Dashboard also features sections that help understand how customers interact with your business, from the origin of access to the payment preferences used in purchases.
The Customers, Origins , and Payment Methods sections allow you to analyze the base's behavior from different perspectives, offering data that helps understand the value generated by customers, acquisition sources, and the most used payment methods.
Customers
In the Customerssection, you can consult metrics related to the base's performance, considering the value generated by each buyer over the analyzed period.
Among the data presented are the customer lifetime value (LTV), which indicates an average of the revenue generated by each customer; the average number of purchases made, in sales per customer; and the average ticket, which refers to the average value spent per customer on purchases made.
Origins
The Origins section presents the distribution of customers according to the traffic source registered at the time of purchase, allowing you to identify where active and old customers. came from.
The information is grouped according to the origin defined in the tracking link used in the sale, making it possible to visualize which channels or campaigns are contributing to customer acquisition.
Payment Methods
In the Payment Methodssection, the dashboard presents the distribution of purchases made according to the payment method used by customers - these data allow you to identify which payment methods are most used in your base, assisting in the analysis of purchase preferences and in planning strategies to optimize checkout conversion.
Together, these sections help understand where customers come from, how they make their purchases, and what value they generate for the business, offering a complementary view to the overall base performance.
To track the origin of sales through a tracking link, configure a Sales R.P.P.C..
Comparison between metrics
A useful resource when reading the customer Dashboard metrics is to perform a comparative analysis between the panel's indicators.
From these comparisons, it is possible to observe what each metric represents in relation to the other, identify base behavior patterns, and understand which factors impact business performance.
The table below presents readings from possible cross-referencing between metrics, indicating what is being compared, what insights can be extracted, and what actions can be considered from this analysis.
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Comparison |
What it compares |
What it reveals |
Recommended action |
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Customer lifetime value by acquisition channel |
Which channels generate more valuable customers in the long term |
Prioritize investment in channels with higher LTV |
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Average purchase value by payment method |
Impact of payment method on purchase value |
Encourage methods that increase the ticket or adjust strategies |
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Customer Evolution × Origin |
Growth of the base over time by channel |
Consistency and scalability of acquisition origins |
Reinforce sustainable channels and reduce dependence on peaks |
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Proportion between new and recurring customers |
LEVEL of retention and base maturity |
Invest in retention when there is acquisition dependence |
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Sales per Customer × Average Ticket |
Purchase frequency in relation to the average value |
Whether revenue comes from recurrence or value per purchase |
Adjust strategies to increase frequency or ticket |
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LTV × Entry Product |
Value generated by customers from the first product |
Which products attract more valuable customers |
Direct acquisition to products with higher LTV potential |
Access for more information about the metrics displayed in the Customer Dashboard.
Best practices for strategic reading of indicators
To obtain more complete insights into the performance of your buyer base, it is important to analyze the customer Dashboard metrics in a contextualized way. Some practices can help make this analysis more consistent.
For this, you can:
Analyze metrics together
- A análise combinada facilita a identificação de padrões de compra e oportunidades de crescimento - por exemplo, ao relacionar Clientes Novos (aqueles que realizaram a primeira compra) com Clientes Antigos (que realizaram a segunda compra ou mais), você avalia a saúde da sua retenção e entende a composição dos seus Clientes Ativos; e
- Ao cruzar as Vendas por Cliente, o Ticket Médio e a Evolução do Valor Vitalício do Cliente (LTV), é possível diagnosticar quanto de receita média cada consumidor gera para o seu negócio ao longo do tempo.
Monitor the evolution of the customer base over time
- Os gráficos do Dashboard de Clientes oferecem um panorama com a variação das métricas em diferentes períodos, o que ajuda a identificar crescimento ou redução da base de clientes, mudanças no comportamento de compra e variações no valor gerado pelos clientes;
- Na prática, comparar períodos semelhantes também contribui para reduzir impactos de sazonalidade nas análises. Além disso, comparações como Evolução de Clientes × Origem mostram que o comportamento da base deve ser analisado de forma contínua.
Observe the value generated by customers
- Indicadores como LTV, Ticket Médio e Vendas por Cliente ajudam a entender quanto cada cliente contribui para a receita do negócio;
- Na prática, ao acompanhar quanto cada cliente contribui para a receita do negócio, é possível identificar clientes que geram maior valor ao longo do tempo, padrões de recorrência de compra e oportunidades de aumentar o valor médio das vendas.
Identify customer base payment preferences
- Compreender quais métodos são mais utilizados pelos clientes ajudam você a determinar quais meios de pagamento deve priorizar no checkout, além de ajustes em estratégias comerciais ou campanhas promocionais;
- Como, por exemplo, a relação entre Ticket Médio × Forma de Pagamento e Vendas por Cliente × Ticket Médio ajuda a entender como os clientes realizam suas compras - tanto em frequência quanto em valor.
How to apply these analyses in your daily life?
The comparisons between metrics and the best practices presented help guide the reading of Customer Dashboard data and identify opportunities for optimizing your customer base.
To deepen the analysis of each indicator and understand how data is presented in Guru, also consult the documentation related to the Customer Dashboard and the metrics displayed.