Look at these stats:

"73% of people point to customer experience as an important factor in their purchasing decisions."

"Companies with customer experience-led growth strategies yield a 5-10% higher wallet share than companies without."

These are only two of many statistics proving that providing a good customer experience is a must for sales. 

Part of ensuring a good customer experience is maintaining good relationships with your customers. 

In other words, if you want to sell, you need to know how to build, manage, and nurture customer relationships. 

How? 

Enter CRM data analysis.

Customer relationship management (CRM) refers to all the different strategies and processes involved in managing, improving, and analyzing interactions with your customers. It helps you maintain a positive relationship with your customers by providing a satisfactory experience throughout their buying journey.

CRM systems typically include features like contact management, lead management, third-party integrations, and pipeline management.

Therefore, CRM data analysis involves looking into the data collected within your CRM system to extract actionable insights and patterns to improve your relationships with customers. 

This, ultimately, boosts sales performance.

To ensure your CRM data analysis is working correctly, theres a few best practices you should consider. 

Let's take a look at them.

Well-defined objectives will help guide your CRM data analysis efforts. 

You can’t just jump straight into your analysis without knowing what it is you want to achieve.

Let's consider a shoe company, for example. If your CRM data analysis objective is to understand your customers' buying patterns, you’d zero in on CRM data such as purchase history and buying preferences. 

Structure your data around your chosen unit of analysis, whether this be individual customer accounts, customer segments or more. So, if your objective is to understand a specific customer’s buying patterns, you’d gather the purchase history and buying preferences from that single customer’s account.

Evaluate your CRM data using your objectives as your guide. If you decide to compare two units of analysis–two individual customer accounts, for instance–make sure you use the same process of analysis for both.

You can also use emerging technologies like generative AI at this stage. These AI systems can process large datasets and extract meaningful patterns, offering your teams enhanced efficiency and more precise decision-making. Generative AI can also enable predictive modeling, helping to anticipate future trends, customer needs, and potential sales opportunities.

To ensure an accurate CRM data analysis, your CRM data should also be accurate and complete. 

This means you should regularly clean and update your customers' records to eliminate duplicates and outdated information.

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As we already know, CRM data analysis can help improve your customer relationships and, ultimately, aid your sales campaigns. Here are the specific benefits of CRM data analysis for sales teams.

Attrition rates show the proportion of potential customers or leads who disengage or drop out of your sales funnel. In other words, it measures the percentage of leads who do not become paying customers or who drop out of the buyer's journey before making a purchase.

CRM systems can track your entire customer journey, allowing your team to identify specific stages where leads drop off. By pinpointing these critical points, you can gain insight into potential hurdles or challenges that lead to attrition. We’ll talk more about this later.

CRM data also provides a detailed view of customer interactions and behaviors. 

Analyzing this data helps you understand how leads engage with your content, respond to communications, and navigate through the sales funnel.

With this wide range of data, you can recognize patterns in behavior and create targeted interventions to keep your prospects engaged, refine communication, and increase conversion rates.

The sales pipeline represents the various stages your prospective customers go through, from initial awareness to the final purchase. Customer analysis helps facilitate efficient sales pipeline management. This process involves examining how much time your leads spend in different stages of the sales pipeline. Knowing this gives you valuable insight into the efficiency and effectiveness of your sales process. 

By analyzing this information, your sales team can identify bottlenecks or areas where your leads tend to stagnate. With this insight, you can create targeted solutions to streamline the process and reduce unnecessary delays.

For instance, if leads take too long in the awareness stage, you might ask marketing teams to create more resources to make them aware of your product. They can then double-down on their inbound marketing strategy by engaging the production services of a reputable company for video content.

CRM systems can also provide real-time data, allowing you to monitor the progress of leads through the pipeline continuously. This real-time visibility helps your team identify anomalies promptly, address issues, and take proactive measures to keep the pipeline flowing smoothly.

One sales tool that can help you deal with your leads more effectively is Badger Maps.

Badger Maps is the best route optimization software that allows sales reps to automatically plan, route, and maximize their time in the field, cutting down driving time by 20%.  

With capabilities such as route optimization, lead generation, map visualization, and automated data gathering from the field, Badger Maps helps field sales teams save time on their daily planning, maintain better relationships with customers, and get organized.

Badger Maps also offers other important capabilities such as lead generation on the go, customer data visualization, and check-ins. Sales teams have reported that they sell 22% more and drive 20% less when using Badger Maps, in fact, the average team of 10 reps sells $936k more the year they start using the app.

With Badger Maps bi-directional integration, sales reps have direct access to their CRM data in the field where they need it most. 

Customer records, engagement, and interactions that are created and updated in Badger Maps will be pushed to your B2B CRM and vice-versa, keeping all of your important customer information up to date as you work in the field.

Badger Maps route planner integrates with the best CRM software such as Salesforce, Microsoft Dynamics, Zoho, HubSpot, Insightly, NetSuite, and many more.

Badger Maps integrates seamlessly with your CRM software, allowing field sales teams to optimize the time they spend on the road. 

Sales teams have even seen a 50% increase in CRM usage once they start using Badger Maps. 

Sign up for a free trial today or schedule a demo to learn all about how you can start integrating Badger Maps with your CRM today!

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CRM software can provide valuable information on the details and effectiveness of your team's sales calls. Let's break this down. 

When it comes to the quantity of sales calls, CRM data analytics tools can help track the number of phone calls your sales team makes to prospects.

The data helps evaluate your outreach efforts and identify trends in call volume over time. So, if there is a noticeable increase in call volume during a specific month, the team can investigate the reason behind this trend and leverage it for future planning.

With the duration of sales calls, the CRM data analysis metric will show you how much time your sales representatives spend on individual calls. 

This information helps you assess whether calls are too brief, which means sales agents are potentially missing key details, or too lengthy, which could lead to customer disengagement. 

You want to ensure that your sales team communicates effectively without overwhelming the prospects.

CRM data also offers vast information on the effectiveness of your sales calls. It typically tracks and analyzes metrics like conversion rates, deal closures, and customer responses. With this data, you can easily identify successful customer communication patterns, allocate resources more effectively, and improve the overall quality of interactions. 

This ultimately boosts conversion rates.

Check out this blog that provides 9 top tips for converting your leads into customers!

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Understanding the performance of lead sources helps you allocate resources efficiently. These lead sources include various channels, from common DTC platforms like social media to popular B2B SaaS marketing channels like events. 

With the data you obtain from CRM analysis, you and your team can easily identify which sources generate the most valuable leads.

Marketing efforts, budgets, and human resources can then be directed toward the channels that have yielded positive results. This helps streamline your sales process and ensure resources are used where they are most likely to drive success.

CRM data analysis also shows the ROI for each lead source. This data helps you assess the cost-effectiveness of different channels. You can, again, make informed decisions about where to allocate budget and efforts for maximum impact.

CRM data analysis provides a comprehensive view of your sales representative's performance. It covers the analysis of key sales metrics that allow you to measure your sales team's success rate. These metrics measure your team's outreach efforts, demo success rate, and overall win rates, to name a few.

With this data, you can recognize top-performing individuals, foster healthy competition, and provide targeted training where needed. 

As I mentioned earlier, CRM analysis tools can track your team's outreach efforts via calls. But that’s not all. They can also track the number of emails sent and messages sent on other communication channels used for the campaign.

Analyzing this data helps you identify the most effective outreach strategies. It also allows you to refine and optimize your communication approaches if necessary.

By measuring demo success rates, CRM data analysis will also help you understand which aspects of the demo resonate most with your leads. The benefit is that you can learn ways to improve your team's presentation techniques and content. 

CRM analytics also calculate your win rates, showing you the percentage of leads that convert into buyers. This data lets you see the effectiveness of your sales team in closing deals. High win rates may signify that you have strong sales strategies, effective communication, or good alignment of your product/services with your customer's needs.

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Analyzing the underlying causes of a lost sale is a crucial part of CRM data analysis for sales teams. This data shows you why leads don't convert into actual sales. 

CRM systems typically collect vast amounts of data on customer interaction, communication history, and deal or lead progress. With data analytics tools, you can discover patterns in the stages where losses commonly occur and pinpoint the causes for the lost sale.

CRM data analysis also permits customer segmentation based on parameters like demographics and deal size. By comparing conversion rates and losses across these segments, you can easily identify the variables that cause specific customer groups to make a purchase or not.

CRM data analysis is pivotal in fostering long-lasting customer relationships. 

As markets change, customers expect different things, and competition gets tougher. That’s why it's crucial to extract useful information from CRM data and analyze it. It can help you create strategies that will help make consumers happy every step of the way.

And when you build stronger connections with your current customers, you can give your sales efforts a boost. Ultimately, you ensure the sustained growth of your business.

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Author Bio: Chris Norton, host of the UK’s 7th largest marketing podcast, Socially Unacceptable, and Founder of award-winning B2C specialist PR agency Prohibition. His social media training blog is listed in the UK's top 10 PR blogs. For tons of digital PR tips, you can follow Chris here @chris_norton.