Creating a sales analysis is not always simple.
Therefore, in this content you will clear all your doubts on the subject, discover the types of analysis that exist, understand the importance of this resource and the methods necessary to perform it correctly.
In the end, you will be able to assemble your sales analysis efficiently and practically.
Sales analysis is an operation of study, understanding and strategic analysis of the commercial results obtained by the company.
This type of process takes into account the objectives outlined above, the efforts and investments made and the financial returns, within a specific period.
Sales analysis makes it possible to find points of improvement and understand which investments resulted in the best returns for the company.
In addition, you will have several other benefits:
Without tracking data and metrics, the company operates in the dark.
A sales analysis provides visibility into investments and results and ensures transparency to the processes followed.
With the analyzes carried out, the company has another view on consumer behavior, needs and preferences.
So, stop acting based on "guess" and the results improve: for consumers, who start to count on a company that focuses on what they need and for the company, which gains in sales and financial results.
In addition to analyzing past data, analytics enable a better forecast of what will happen in the next business cycle.
There are even specific types of analysis for this and we'll cover them later.
The information obtained through the studies is extremely beneficial for the sales team, as it also starts to focus on what really matters.
With better results, they also increase team motivation and engagement.
Sales analysis not only serves to optimize and direct the efforts of the department itself.
They also help marketing actions, as we were able to identify those that brought the best results.
Identified trends and forecasts should also be shared so the marketing team can leverage and capitalize on these opportunities to generate more leads for the sales team.
By understanding the points of attention, improvement and opportunities, in addition to analyzing the efforts that bring more results, the company can improve sales numbers.
For this, you need to use these analyzes in decision-making and budget distribution, for example.
ROI is one of the most important metrics for the company and deserves your attention and constant monitoring.
That's because ROI calculates how much money the company makes or loses from the investments made.
With the analysis and with the actions and decisions taken from it, the Return on Investment improves, since the company starts to really invest where the result is.
As sales analysis helps to understand the needs and consumer behavior of the brand, from it it is also possible to create actions that improve the experience between customer and brand.
In sales analysis you can include customer service analysis, both pre-sales and commercial approaches, as well as post-sales.
This data will also bring important insights to improve the consumer experience and thus improve sales results.
There are 6 types of most commonly used sales analysis.
This type of analysis is based on data collected over time and from different sources of information.
Some examples in this format are sales reports, results evaluation and application of sales metrics.
With the descriptive analysis the company is able to evaluate the history and improve the future strategies with decisions based on data.
Predictive analytics is also heavily explored in the sales sector and its objective is to find predictability for the next period, based on historical data.
For example, it can be used to identify the percentage of sales growth in seasonal dates or periods when sales decrease.
The purpose of this type of analysis is to identify and enhance trends, causes, probabilities and opportunities.
Prescriptive analytics is often combined with predictive analytics.
The purpose of this type of method is to prescribe recommendations for the next steps and for the next period of work.
Sales planning and projections are part of prescriptive analysis.
Diagnostic analysis is similar to descriptive analysis, as it starts from data analysis.
The difference between the two lies in the purpose of the diagnostic analysis.
This aims to find and establish cause and effect relationships in the results obtained, whether positive or negative.
Trend analysis also seeks to find patterns in the sales data that can build predictions that the strategic team can work with in the next period.
It is widely applied when the same company works with different types of products or services, in order to understand if and which solutions stand out at certain times.
Trend analysis can also track and utilize market data.
Sales analysis can also be of the performance type, which focuses on data studies in order to verify how the company's commercial results are performing as a whole, as well as teams and professionals in a specific way.
Learn now how to set up your sales analysis.
Follow our step by step:
The first step of any analysis is the definition of objectives and goals.
And with sales analytics it's no different. Ideally, this definition of objectives is done with each new analysis, aiming at the next period.
That way, when the time for analysis comes, you'll work with the projections that were made earlier.
We recommend that you set short, medium and long term goals.
This will also help in the planning and sales strategy work, in the choice of channels and efforts, in addition to the distribution of the budget.
The second step is to define which metrics and variables will be used to monitor the results.
Remember that the objective is always to monitor the evolution of results in relation to the objectives set and, for this reason, the metrics need to be aligned with these results.
Leave vanity metrics aside and focus on metrics like conversion rate, ROI, CAC and average ticket.
Using results analysis tools can automate data collection, gather information in one place and even understand results more strategically.
Therefore, investing in sales data tools is a great suggestion to make your analysis even more robust, practical and professional.
The visual of the data analysis interferes with their understanding, whether in the monitoring work routine or in the presentation of these numbers.
How about increasing your analysis with the use of graphs and dashboards, in addition to the more traditional spreadsheets?
Trends, patterns and points of attention will stand out this way.