With proper tools and tactics, sales analytics will be straightforward process that can make sales data analytics a less exhausting task.
Here, let’s dive into sales analytics, an overview of the tactics to accomplish the job, and Sales Analytics Software.
Tracking sales metrics and applying sales analytics tools can make your organization more efficient and generate higher revenue growth.
In your sales career, you may have experiences road bumps and setbacks, and you’d have tried to analyze them and learn from those experiences- this is what sales analytics is in a nutshell.
With a more logical and methodical approach, this process can be scaled to help the entire sales team in your organization. And here is where sales analytics tools step in.
Sales Analytics tools provide a microscopic view into sales data to answer questions:
- How to get better as a team? What steps need to be taken to ensure that we are working at peak potential?
- How to make the most out of our sales resources and reduce the cost of selling?
- How are the market standards changing, and how is the customer behavior changing? What can we do to meet these expectations?
- How can we use innovation and revise our current performance and make changes within our field?
According to a McKinsey case study, an organization that analyzes data and applies suggestions based on accurate results is proven to increase its sales productivity by up to 20%.
However, many organizations are puzzled about which metrics should be tracked? How can they convert them into insights, and how to apply that intelligence once it is in your hands?
Here’s where Sales Analytics tools can help your organization- it will be easy to win with a plan and the right Sales Analytics tools.
Today, we’ll be discussing:
Recommended Read: A complete guide for sales call analytics.
Predictive Sales Analytics and Its Importance
Predictive sales analytics helps identify future trends and strategize effectively. The sales analytics software you use should automate this process and conclude the pre-existing data and the current data to shine a light on the market trends and customer behavior.
This software uses machine learning or AI to automate and translate your raw data into actionable outcomes, and they grow increasingly accurate with time.
This predictive characteristic of sales analytics can help guide various aspects of your sales team and their tasks, such as identifying opportunities, highlighting areas of improvement, and underlining strategies and products that perform well.
These analytics programs are practical, efficient, and convenient. But to utilize the programs in the right way, there are specific steps that you should keep in mind:
1. Select what needs to be analyzed.
It’s a no-brainer; however, it is worth mentioning. Without knowing what to analyze, you can’t run a sales data analysis.
You have to keep in mind the endgame of your analysis- what you want to gain out of it and what you will do with the results as it can analyze data in terms of product, campaign, sales rep, team, or organization performance. Therefore, narrowing it down to specifics can help you get precise data, and you can use strategies further.
2. Specific and measurable objectives
Again, narrowing down can bring the general results to precise results yielding better performance as the sales data analysis will be accurate.
For instance, you can choose a campaign and underline the specific aspects that made the campaign a success, such as which product sales performed better, which strategy worked better for which product, which sales rep’s process was efficient, etc.
This can help in the intelligence of future campaigns.
3.The frequency of sales data analysis
The nature of the analysis dictates the tracking frequency. You can track data and analyze it either weekly, monthly, quarterly, annually, or even daily.
How frequently the organization wants to analyze sales data is entirely customizable.
4. Manual compilation of data or sales analytics software
You may choose spreadsheet software like Microsoft Excel or Google Sheets to compile sales data manually. However, CRMs and Sales Analytics Software are probably a more efficient option.
A CRM can help in gathering sales data effortlessly. It allows for easy tracking of customer information, sales rep performance, task log, and other metrics.
5. Make Data Easy to Understand
Extending from the previous point, sales data analytics may be complicated for a person who is not technically well-versed. Therefore, it is essential to present data visually so that its understanding is easily accessible.
The data should be readily accessible and easy to understand as it creates data transparency and makes sharing of the data easy. Thus, it should be essential in the infrastructure of your sales data analytics software.
6. Apply results for better sales efforts
Post the sales data analysis process, the results you get need to be used to help and improvise future sales efforts. Since this data is predictive, it can be applied better to understand the ever-changing market standards and customer behavior.
This will drastically change the performance of each sales rep, the team, and the organization and help generate revenue growth.
Now that we’ve looked at sales analytics and its importance, let us look at some metrics that you should be tracking to make the most of your sales analytics tools.
Important Sales Metrics to follow
In order to have accurate sales data analytics, it is essential to gather a full slate of data from different sources, yielding better analytical results and insights.
Here is a list of metrics that you should track to make the most of your sales data and sales data analysis.
Sales Target, Sales to Date, and Sales Growth- These will help you understand how much sales you would make, how much you’ll be selling, and how much you are projected to sell overall.
These are essential sales analytics metrics to track. This data can help compare your current performance with the previous one while predicting future trends and identifying areas for adjustments.
Lead-based Metrics such as sales by lead source, average lead response time, and lead conversion rate will help analyze lead data. These can help quantify sales leads, what they generate, and which efficient strategies.
Recommended Reading: 12 sales metrics to kick-start your sales analytics right away!
Response to the leads can also be highlighted, understanding how effectively those leads are turned into wins/closed deals.
It is vital to track the sales pipeline stages and the sales process to understand the sales process and whether the prospects will be converted into positive results in a timely fashion.
Knowing this timeline of the sales process and its stages identifies where and which resources should be utilized to help close the deal.
Metrics related to customers such as revenue from new/existing customers, churn rate, and customer behavior helps analyze how the team is good at retaining its customers and how much these customers are satisfied with your service. This information can be used to better appeal to customers and maintain a business relationship with your organization.
Understanding customer behavior and buying habits is a gold mine when it comes to sales.
It helps in ideating and creating a precise strategy and streamlining the sales process, improving the team performance, the performance of the organization, and generating revenue.
It is entirely up to the organization which metric is relevant and should be tracked since metric tracking is entirely customizable. The list mentioned above suggests metrics you should be monitoring in your sales analytics software.
Now that we have looked at sales analytics and its importance and which metrics should be tracked, let us move on to understanding sales analytics software and on which basis you should choose the right fit for your organization.
A Short Guide on Sales Analytics Software
There are various sales analytics software solutions in the market. It can be overwhelming when choosing the one for your organization.
The guide below will help in differentiating different types of software solutions.
The difference between various Sales Analytics Software
Sales Analytics software can be distinguished in terms of how artificial intelligence is employed and integrated into your systems.
- Certain sales analytics software solutions will be integrated with your primary data systems, such as Emails and Message platforms, to capture real-time sales data and activities and condense the information to accelerate the predictive character of sales data analysis. Here, Artificial Intelligence can help boost productivity by reducing time-consuming tasks.
- Sales analytics software can be integrated with other software and CRM to capture, understand and refine data and streamline it for maximum efficiency.
- Sales analytics software solutions should provide high-class data visualization functions- one should be able to opt to view the data in the form of charts, tables, and graphics.
How to Choose the Right Sales Analytics Software for Your Organization?
Sales analytics software solutions are never one-size-fits-all types. It should be chosen based on the goals of the organization. You should first evaluate the parameters for what you want from the sales analytics software before investing in one.
Some of the parameters could be
🔹 Size of the Company
If your organization is large and has several sales teams and if each team should use its forecasting method, this may bring inconsistencies in the final results.
Using a standard system across teams would be better to avoid these obstacles. Therefore, Sales analytics software solutions are perfect for companies with stable products and sales, consistent targets, consistent customer relations, and more than 30-40 sales reps.
🔹 Requirements in terms of business
Before investing in a solution, the organization should underline the specific reasons for the solution.
If the data is inconsistent and incomplete, if the recording data process is time-consuming, a lot of manual labor is involved, the predictive characteristic is absent, no data transparency and no unified data source can lead to drastic inconsistencies in the final results and performance review.
Thus, if your organization is dealing with such issues, invest in Sales Analytics Software.
🔹 Ease of integration
Investing in a sales analytics software requires planning. It means restructuring the past data software and integrating it with a new software solution; the pre-existing software tool should streamline the workflow; thus, planning is required.
Now that we have looked at a brief guide to Sales Analytics Software try Convin’s Sales Call Analytics tool to record, transcribe, and analyze crucial sales data for business.
The USP of Covnin’s Sales Data Analysis Software is its ability to underline call performance, highlight customer needs and concerns, and employ this data to boost the sales team's performance and, by extension, of the organization.
You can even track sales activities and understand the timeline of these activities. You can also track a sales rep’s future sales results and compare them against those of other employees to highlight areas of improvement and provide constructive feedback to keep in mind for strategizing late.
With the Convin Sales Call Analytics Software, you can refine your sales organization with analytics and accurate data, converting them into an efficient and pipelined sales machine.
Results first, payment later.
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