Customer relationship management systems can provide extensive analytics and reporting capabilities for businesses to better understand their sales processes on a more comprehensive level. Secure data mining, data recording, and report generation translate this information into visual representations of KPIs.
Popular metrics businesses generate and track include their sales cycle length, marketing ROI, sales rep performance, and deal forecasting.
Featured Partners
What is CRM analytics?
CRM analytics is internal programming that collects, organizes, and analyzes data around customers, sales, and revenue. Generating detailed reports like this is a top CRM feature that businesses of any size and market can benefit from.
This data provides actionable insights for leaders, managers, and individual users that assists in making timely and data-based decisions. CRM analytics has also recently been integrated with AI functionality, allowing for more niche reports and suggestions to be generated on command.
5 key CRM metrics
Sales cycle length
A sales cycle length is the average time it takes a deal to be closed from beginning to end. This starts with a prospect converting to a lead, and that lead becoming a confirmed customer. The goal is to have the sales cycle length be as short as possible, so that leads aren’t lost to competitors, or their need for your solution dissipates. Measuring this metric will help identify opportunities where the sales cycle could be condensed.
Customer churn rate
A churn rate is a percentage metric that shows how many customers leave your sales pipeline or stop doing business with your company entirely. A high churn rate is something businesses try to avoid, and typically it can also identify where in your sales process the churn is happening.
It’s always good to know where you’re succeeding, but equally important to understand where you are losing business in order to make immediate adjustments.
Marketing ROI
Marketing ROI directly tracks how resources that are allocated to marketing contribute to overall revenue growth. While CRM solutions are sales-oriented, marketing features are included in that. That includes social media communications, email marketing campaigns, and even web and landing page building. This is especially important for small to mid-sized businesses looking to invest more into marketing campaigns, because you need concrete data that supports such an investment.
Rep performance
Rep performance is tracked by monitoring their overall sales activities and close rates. Common activities that are monitored are sales calls, email performance, referral rates, and lead conversion rates. This tracking can be done on an individual scale, by team, according to location, or for an entire department—and can help with quarterly reviews. This transparency is important especially in a commission-driven environment.
Business forecasting
The best CRM solutions offer business and revenue forecasting as an advanced CRM metric. These reports take into account customer activity, sales length, churn rate, sales history, and more to come up with predictive analytics around projected revenue wins. While this information is always subject to change depending on any number of factors, having a projected idea of revenue QoQ or YoY helps immensely when planning bigger initiatives for a company.
Top 3 benefits of CRM data analysis
Increased productivity
I recommend using a CRM software as a way to increase productivity around customer interactions, and data analysis helps do exactly that. Since there isn’t time being wasted on manually pulling and sorting data, users can focus on nurturing client relationships and closing deals. Trusted analytics make sure efforts are being put into the right place at the right time and optimize resource allocation. This way, reps, agents, or administrators are spending time doing tasks that are proven to be beneficial to the business.
Improved customer satisfaction
When you have detailed data analysis built around successful—and less successful—marketing and lead nurturing campaigns, it’s easier to understand what customers consider as positive interaction. With the help of personalized engagement and detailed analysis of metrics like email click rates, conversions, and more, businesses won’t need to guess which strategies actually move customers through their pipeline. This will build customer satisfaction with your business and improve customer retention.
Competitive advantage
Having strong analytics in a CRM software allows for businesses to keep a constant eye on market changes or trends. This way, they can anticipate those changes and plan accordingly. For example, these trackable trends help make informed decisions about where to invest more or invest less. If a company anticipates a seasonal increase in business, they should invest in marketing campaigns in advance to get ahead of their competitors. It also helps increase overall efficiency and allows for a flexible and agile business plan.
CRM analytics use cases
When choosing a CRM solution, opting for an analytical CRM tool means there’s an emphasis on data warehousing and mining, plus advanced forecasting. These are great for medium to large teams or businesses that need detailed, secure, and constant data monitoring.
Identifying consumer trends
In industries that are completely driven by consumer trends, having analytical CRM helps businesses stay ahead and anticipate major changes. Whether it’s financial forecasting, product and service trends, or mapping seasonal spikes, an analytical CRM will take complex data and turn it into understandable insights.
For example, a retail business might use purchase history and trends from their consumers to help identify when in the fiscal year their products are in demand. They can then plan to invest in more marketing campaigns leading up to that timeframe in the new year.
Scalability
When your goal is to grow your business quickly, you need an analytical CRM that can grow and scale alongside you. This way, the key metrics you track over time can be consistent no matter how much more data is being saved. Some key metrics that CRM software can track that help with scalability include team, location, and individual rep performance, profit and revenue growth, product or service demand, and more.
This can be especially helpful for companies planning to expand physically with more locations, service more geographical markets, or determine the feasibility of allocating funds for hiring more employees to accommodate growth.
Competitor analysis
While CRMs are meant to manage and track the metrics of companies and individual users who utilize them, they can still help with competitor analysis. Some metrics that can help managers understand exactly where their customer service and solution ranks against competitors are; lead and customer surveys, split testing results, lost deals versus won deals, and average deal closing time for your business versus industry standard. All of this will help companies not only understand their own internal operations but also lead to more sustainability in their markets.
Frequently asked questions (FAQs)
What is an analytical CRM?
An analytical CRM is a CRM solution that offers advanced data analysis features. These help businesses track and understand their customer and market behaviors. They are best for taking this raw data and insights and turning it into comprehensive reports and files that show trends or projections.
Examples of CRM with advanced analytical capabilities are:
- Microsoft Dynamics 365: Receive AI-generated summaries that include a detailed analysis on sales KPIs and suggested tasks and strategies. Price starts at $65 per user, per month.
- Zoho CRM: View forecasting, territory management, and gamification plus custom dashboards. Zoho CRM has a free version of their software with paid tiers starting at $14 per user, per month.
SEE: Read our comprehensive Microsoft Dynamics 365 software review.
What are the three main types of data analysis used in CRM?
The three different types of data analysis used in CRM software are descriptive, predictive, and prescriptive. Together, these cover all generative data around customers.
The three types of data analysis are as follows:
- Descriptive: View real time analysis of the most important CRM metrics summarized in a digestible format using visualization.
- Predictive: Use historical data to identify trends that can forecast future customer behavior, wins, and deal outcomes.
- Prescriptive: In addition to identifying these trends, also receive specific recommendations for next best actions and strategies.
