How to Simplify Sales Analytics with Sales Data Analysis Tool? [for Business]

Sales analysis is the backbone of any business because it enables businessmen to make informed decisions, bring more revenue, and improve their businesses.

There is no denying the importance of sales analysis, but it’s a tedious and time-consuming process. Plus, any error can lead to losses and failures.

However, the integration of AI tools for sales analytics can make the process easier than ever before. Yes, AI tools can assist in analyzing sales metrics, optimizing strategies, pointing out flaws, and in almost every stage of sales.

Let’s uncover how to empower sales analysis with AI and take your business to the next level.

Part 1: What is Sales Analysis?

Sales analysis means analyzing the sales data, which is obtained from various channels, including the website, social media, advertising platforms, and CRM software. It could include important metrics like revenue, profit, customer acquisition cost, and average deal size.

Sales data is a financial compass that gives deep insights into the business and shows the direction of success. It helps in identifying the trend, understanding customer behavior, optimizing strategies, etc. Businesses can use it to make data-backed decisions and take everything to the next level.

Part 2: Steps to Perform Sales Data Analytics

1 Step 1: Data Collection

For sales analysis, data is collected from various sources, such as E-commerce platforms, social media, CRM systems, and POS systems.

2 Step 2: Cleaning and Organization

The obtained data is cleaned by removing unnecessary entries, issues, missing values, etc. Then, it is organized in a spreadsheet or software.

3 Step 3: Detailed Analysis

The data is analyzed to understand the total revenue, profit/loss, and other important figures. It is then analyzed to find the issues, analyze the trend, predict future sales, etc.

4 Step 4: Data Visualization and Reports

Some data is converted into graphics to analyze results quickly. For instance, showing the sale of all products in a pie chart to determine the best-selling product. It can also be converted into a dashboard using powerful tools. Moreover, reports are made to give the gist of the whole data.

5 Step 5: Decisions

Decisions are taken based on the data. For instance, if a certain product has high sales during a specific time of the year, it must be restocked before that. Similarly, other important decisions of a business are made according to the data.

Part 3: Sales Data Analysis Examples Using AI Analytics Tool (With Picture Demonstration)

Let’s see how an AI tool helps in the sales analytics of an insurance company.

#1 Customer Data Analysis

With the help of an AI tool, it is quite easy and quick to analyze customer data. You only need to feed the spreadsheets, lists, and all the information you have.

The chatbot or AI tool learns through the given data in no time and becomes able to answer all your questions and queries. It makes the sales analysis easier than ever before. After giving the data, you are ready to ask any question.

For instance, you can ask about the number of different types of insurance plans sold.

If you want to know about the status of any customer’s insurance plan, ask the chatbot.

Similarly, analyze the health conditions, age group, and other details through the customer database. You don’t have to open spreadsheets and go through massive data. Everything is just one question away. It’s just like having customer data at your fingertips.

Build Your Analytics Chatbot

#2 Sales Transcript Summarization

Remembering the conversations with customers is not possible for a person who deals with dozens and hundreds of customers each day. Transcripts could solve the issue, but going through them is not easy either.

And that’s where an AI tool comes into play. It can summarize all your transcripts in no time. It can turn a long conversation into a short one. That way, it is possible to go through the conversation in minimal time before talking to the customer again.

When there are dozens of transcripts, it becomes difficult for agents to filter the potential clicks. However, AI can do it for you. Based on the previous conversation transcript, it can decide which could be your potential customer. Thus, agents can invest their time in people who are likely to buy their insurance/product.

#3 MEDDIC Extraction

Many organizations prefer the MEDDIC framework for their sales qualification. It is quite helpful for closing high-end deals.

It includes Metrics, Economic Buyer, Decision Criteria, Decision Process, Identify Plan, and Champion. These are the six key areas of the framework that compel agents to put their effort in the right direction and increase the chances of closing deals.

MEDDIC is undoubtedly fruitful, but it is complex and time-consuming at the same time. And when there is a massive list of customers, it becomes more difficult.

The best way to utilize the MEDDIC framework in a business is to use it with the help of an AI tool. Based on the data, the AI tool assists in these key areas and makes the whole process extremely simple and quick.

For instance, we gave the transcript of the conversation between the client and the insurance sales agent to the AI tool. And it helped us find the elements of the MEDDIC framework.

After looking at the MEDDIC elements, agents can understand what the customer needs and how they can close the deal successfully. An AI tool can help in identifying the elements from multiple transcripts in no time.

#4 Sales Technique Enhancement Suggestions

Mastering sales techniques is essential for getting sales. Sales agents usually follow a proven technique to compel new people and attract them toward their product or service.

But sometimes, there are flaws in the technique, and sales agents fail to realize it. It doesn’t lead to any sales and ends up in failure.

An AI sales tool can be helpful in this case. It can help in improving the sales technique for better results. It can go through your technique and evaluate it according to the region, culture, language, and other factors. If there are any flaws, it gives suggestions.

Here's how we told a sales analysis chatbot about our sales technique and asked to share some improvement suggestions.

It pointed out the existing issues in our sales technique and explained how to correct them. That said, if your plan is not working, and you’re frustrated with sales, an AI tool can be your mentor. It will guide you and help you achieve good results.

#5 Customer Emotional Evaluation

Often sales agents fail to address the emotions of customers, and that’s when the deal fails. For good results, it is better to be aware of every emotional stage and lead the customer to sales.

For instance, in the early stage of sales, the customer is curious about the product or service. He wants to know more about it, specifically how it can be beneficial.

Similarly, a customer could be skeptical about the service, warranty, return, and other things. This is another emotional stage that the agent has to handle.

Through the sales transcript, it is possible to analyze the emotions deeply. It gives you a better idea of what the customer is feeling about the product/service. An AI tool can analyze it in no time.

We gave a real transcript to an AI chatbot, and here’s what we received.

AI tools make customer emotional evaluation easier. They give a complete idea of current emotions, reasons, and how to deal with them. Agents can pay more attention to these details to make the sales successful.

#6 Follow-up

Following up with potential clients and customers is a part of the sales strategy. It compels people to consider your product or at least try it once. If you don’t follow up, they might forget about it.

Sales agents manage spreadsheets and data for follow-up. They spend their time organizing this data so that they can follow up with the customer at the right time.

But there is no need to do these things manually. An AI tool can analyze your sales transcripts and create a list of people who can be turned into potential clients through follow-up. It saves time and allows you to put your effort into people who are likely to buy your product/service.

We gave 10 sales transcripts to an AI chatbot and asked which customers should be followed up.

You don’t need to go through each sales transcript and organize the data. An AI tool can do everything for you.

Build Sales Analytics Chatbot

Part 4: Key Metrics to Track in Sales Performance Analysis

Sales teams in most industries and businesses track the following key metrics.

• Revenue: The revenue of a business shows its value. It reflects the sales, performance, growth, and other details of the business over a specific period of time. Every business tracks its revenue on a monthly and yearly basis.
• Profit Margin: After revenue, profit margins are calculated. Businesses track Gross Profit and Net Profit to get an idea of what they have earned.
• Average Deal Size: It’s the average deal value. It’s obtained by dividing the total revenue by the number of deals. It gives you an idea of the deal size the company achieves.
• Customer Acquisition Cost: It’s the average amount spent to acquire a customer. It includes the amount spent on ads, marketing, etc.
• Customer Lifetime Value: The total amount that a customer spends in his complete relationship with the business.
• Churn Rate: Over time, customers are lost, and that’s what the churn rate is. It gives an idea of the future of the business, customer satisfaction, product value, service, etc.
• Retention Rate: A high retention rate shows a growing customer base. It’s an indicator of excellent user experience and services. Businesses track it to know whether a customer returns for the next shopping, brand association, and retention.

Conclusion

Businesses must do sales analysis to evaluate their performance, make informed decisions, and improve their product/service. It is a tedious yet significant part without chances of errors. With the advancement in AI tools, it’s high time to integrate an AI tool for sales analysis. Not only will it save time but also offer valuable data and feedback for improvement. Plus, there are minimal chances of errors. GPTBots empowers you to create your own AI analysis chatbot without coding. Train the chatbot with your business data and let it handle the complicated tasks. Sign up today and get 100 free credits each month.

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