Sales generation is a serious business for every sales-driven organization looking to maximize its profit margin and increase revenue.
If you have been keeping up with emerging trends in sales in the past few years, you would know how important data has become to sales performance and how sales tracking and analytics hold the power that unlocks phenomenal sales potential.
By now, every sales-driven business should know that guesswork and intuition aren’t going to help you hit your monthly target nor would your countless cold calls help you get closer to sales goals without sales data analytics.
Sales analytics oversees every sales-oriented analysis and tool that helps you gain better insights into your sales performance. Analyzing your sales data doesn’t have to be complicated.
In this article, we will help you gain a deeper understanding of sales analytics, how to do it right and how it can benefit your sales team.
In general terms, sales analytics is the practice of generating insights from sales data, metrics, and trends to evaluate the performance of the sales team against their goals.
The goal of sales analytics is to simplify the sales information to help sales leaders and reps understand their performance, sales opportunities, and trends. Aside from this, team leads also use the sales metrics generated from sales analytics to set goals, forecast future sales, improve sales processes and accurately predict expected revenue.
Sales analytics ask questions like, “What leads to upselling/cross-selling opportunities?” “What trends are we seeing/looking out for in our sales data?” or “What’s the performance of our sales reps in each region?”
Sales analytics relies on data analytics to improve the short-term and long-term performance of the sales team as well as suggest recommendations to sales managers on the sales trends or opportunities to look out for.
In essence, sales analytics is crucial to identify the most effective strategies for your sales efforts and predict the success of your sales activities.
Sales data analysis is critical to the strategic growth and success of sales efforts. It processes your historical sales data and current sales strategies to help you understand your customer’s behavior and recommend effective sales and marketing approaches to increase revenue.
For better clarification, here are some of the benefits of sales analysis to your sales team.
Sales analytics metrics help you gain insights into your sales team performance, trends, opportunities, and gaps in your sales approach to help you make data-backed decisions on how to improve sales performance and explore all opportunities to maximize profits.
It’s a bit risky to leave key sales decisions to intuition and chance. A good understanding of your strengths and weakness will help you make deliberate sales-driven decisions and plans.
An understanding of your customer’s behaviors and interests will help you develop the right strategies to satisfy their needs and move them down the sales funnel much faster.
Sales analysis provides you with all the valuable information and insights into the stage of the customer lifecycle your prospects are in through a sales pipeline analysis. You can now use this information to personalize communications and sales strategies to increase your conversion rate.
Aside from the above-listed benefits of sales data analysis, it also helps identify the characteristics of profitable customers for sales reps to follow up with to increase sales and revenue.
When you are well-informed about your high-value customers, it’s only reasonable that you intensify your sales effort on them to add value to your company.
The insights generated from sales analytics reports help sales managers and reps to discover market opportunities and trends. Consider tracking these metrics continue to update you on market opportunities and trends.
If you understand some of the factors that helped you close your previous sales deal, you can implement this for subsequent deals. The sales analytics process enables sales reps to understand their customers better to satisfy their needs and improve sales by upselling and cross-selling to their existing customers.
Now that you know the benefits of sales analysis to your sales team, let’s dive into the different types of sales analytics.
Predictive sales analytics is a crucial type of analysis that enables sales managers to forecast future sales and revenue. It uses historical data and sales models to provide insight into previous customers and leads behavior to predict the financial capability and business potential of prospects.
Sales forecasting is a critical aspect of predictive analytics, it takes into account the average purchase value, time, size, and management. Aside from historical data, it also considers the historical conversion rate of the sales pipeline to enhance sales predictions. Find the difference, inside sales vs outside sales.
As the name implies, this form of sales analytics focuses on using the findings from predictive sales analytics to recommend plans and strategies to hit sales targets. It helps sales managers understand the sales data findings, proffer realistic solutions to the sales problems, and analyze the possible outcome of these solutions.
Prescriptive analysis cannot exist or work on its own as it relies on the results of predictive analysis of sales data to help organizations grow.
Diagnostic sales analytics can be the first step of sales analytics for some organizations using techniques like data discovery, drill-down, correlations, and data mining as well as some machine learning techniques to understand the reason behind a particular customer or lead’s behavior.
It helps sales managers and reps answer important workforce questions about their new and previous customers’ behavior and sales records. The diagnostic analysis is also crucial for understanding sales data and detecting possible disruptions to future sales.
You might want to analyze your sales data by channel of distribution if you are selling your products across many different platforms. Under this type of sales analytics, the first course of action is to aggregate the total sales of your products, after which you analyze them based on the total products sold across each channel. Doing this will enable you to view and track changes in sales data across different periods – days, months, or years.
A common rule when using this type of sales analytics is to ensure that you first analyze the sales data of each channel individually before analyzing them as a group.
This type of sales analytics involves keeping track of store-keeping units (SKUs) – the variation and size of each product by color, brand, price, geography, etc.
Analyzing sales data by SKUs allows you to understand the behaviors of your different customers across various locations and demographics. By identifying the trends in sales activities across these locations and the best sellers in that location, you can use the data for your future sales and marketing efforts.
Before you analyze any sales data, it is important that you understand the metrics and key performance indicators (KPIs) that you are going to measure and why you should measure them.
As a result, we have listed some of the important metrics that your sales teams should be tracking and analyzing below.
Sales growth provides a bird’s-eye view of sales activities and performance over a specific period. It shows sales teams how revenue increases or decreases and how the sales team is performing within a given time.
The sales growth metric measures sales growth by subtracting the total sales of a current period (month, quarter, or years) from the total sales generated in the previous period (month, quarter, or years). Divide that result by sales from the previous period, then multiply by 100 to get your growth percentage.
Sales targets are the numbers of sales that are to be achieved in a specific period. It measures current sales and compares them to long-term goals. Depending on your organization and your team’s KPIs, your sales target can be a monetary value, the number of sales made, or the number of accounts opened on a weekly, monthly, quarterly, or yearly basis.
To calculate the sales target, divide the number of sales from the current period by the sales target, then multiply the result by 100. The result will tell you to close you are to reaching your goals.
Sales per rep measures the individual performances of sales reps. This metric is important when sales managers need to determine ongoing training, professional development opportunities, rewards, promotions, and bonuses.
You can track and measure the performance of sales reps by tracking the sales each rep makes during a given period – weekly, monthly, or quarterly and the number of deals closed as well as the monetary value.
Sales by region measures the number of sales recorded in a particular geographical location of your business. These metric tracks sales in a specific region – state, city, country, or continent – over a specific period.
Analyzing sales by region can help sales managers understand where their products or services are selling the best to channel their sales and marketing efforts to the right people.
The Sell-through rate evaluates how quickly an organization can sell its inventory. It is an important metric for retail businesses looking to monitor their supply chain and competitors.
To measure the sell-through rate, divide the amount of inventory sold within a certain period by the amount of inventory received within that same time. After which, you multiply the result by 100 to get your sell-through rate percentage.
Sales per product otherwise known as product performance measure the profitability of the products your sell. This metric helps you determine which products are selling and those that aren’t performing well.
To calculate sales per product, you have to track total revenue for individual products over a specified period – weekly, monthly or quarterly. You can also track and measure the number of units sold depending on your goals or KPIs. Also, check out the guides, B2B sales, SaaS sales and tech sales.
Pipeline velocity measures how quickly a lead and prospects move through the sales pipeline to become customers. It is a key metric used for sales forecasting and business planning.
To measure your pipeline velocity, multiply the number of sales qualified leads (SQLs) in your pipeline by the average deal size and average win rate, and then, divide that number by the current length of your sales cycle. This will show you much revenue is flowing through your pipeline in a given period.
Average purchase value measures the value of each sales transaction. It is an important metric used by sales managers to make sales forecasts and projections, as it allows you to calculate the number of purchases you would need to hit your revenue goal.
Marketers and sales managers use the insights from average purchase value to upsell or improve their marketing strategies. You can calculate the average purchase value by dividing your total sales revenue by the number of sales you made.
To get accurate sales data and insights into the sales performance as well as future sales performance, sales managers must follow the right steps. Below are the common steps that you should follow to carry out your sales analytics.
Step 1: Select the kind of sales data you want to analyze and what activities of the sales team you want to measure.
Step 2: Define your key performance indicators (KPIs), goals, and the metrics you will use to measure them.
Step 3: Set a frequency or timeline for your sales data analysis.
Step 4: Find and compile your sales data manually or with a sales analytics tool.
Step 5: Find the data visualization tool that best suits your goals and sales data to help you make sense of numbers and metrics – present sales data in a visually appealing way.
Step 6: Analyze your data from your sales analytics tools and identify trends or patterns in the data or customer behaviors.
Step 7: Apply your findings from the sales analytics reports to develop data-driven sales strategies and improve your sales performance.
Some of the most popular and useful Sales Analytics Tools are discussed below.
Sloovi Outreach helps you track your daily sales workflow, prioritize leads with dynamic Smart Views, and create customized and intuitive reports.
Its lead generation feature allows you to add thousands of leads and track every integration with a sales lead. The Pipeline management feature also allows you to track all leads and prospects as they travel through each sales stage of the sales pipeline.
Power BI is one of the most popular data analytics tools used by sales managers to analyze sales data. It is equipped with machine learning capabilities for sentimental analysis, customer segmentation and integrates with other sales analytics platforms to streamline the sales analytics workflow.
Powe BI can also serve as a data visualization tool to provide insights into sales data. The Power BI plans start at $9.99 per user per month.
HubSpot sales hub helps you measure the impressions, clicks, and return on investment (ROI) of the sales and marketing campaigns you run. It can also help you generate a lot of sales data, personalize your email marketing campaigns, and monitor your sales performance.
The HubSpot analytics can give you insights into your customers to help you understand how you can attract and retain new and existing customers. The HubSpot plan starts at $40 per month.
Zoho Analytics is best suited for businesses that generate the majority of their sales from social media. It provides sales managers with detailed segmentation of customers using sales data and offers social media lead generation to sales teams.
With Zoho, you can keep track of social media posts related to your business. Its price plan starts at $22 per month.
Some of the common challenges that you can encounter when performing sales analytics include;
Sales analytics is crucial for sales managers and teams to measure their performance and understand sales data to develop data-driven strategies to support their sales efforts.
You must analyze your sales data regularly to encourage accountability, reveal insights into changing customers’ behaviors and trends as well as coordinate the activities of your sales team. Find more sales related guides, sales productivity, sales prospecting, B2B sales process and sales qualified leads.
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