the Importance of Data-Driven Decision-Making
Businesses need to rely on a deeper understanding of their customers and sales processes to gain a strategic edge. Platforms like Salesforce and HubSpot have become invaluable for businesses aiming to streamline customer relationship management (CRM) and digital marketing efforts. However, these tools are only as powerful as the data-driven insights they can provide, and to fully leverage their potential, organizations must focus on interpreting their data wisely.
Traditionally, CRM systems highlight metrics like lead conversion rates, customer acquisition costs, and revenue growth. While useful, these metrics often paint a limited picture of customer behavior, engagement, and potential revenue opportunities. Aiming to optimize processes and boost returns, businesses need to expand their focus beyond the basics. Often-overlooked metrics—such as Customer Lifetime Value, Lead Velocity Rate, and engagement rates—can reveal critical insights that standard reports may not capture.
Why Focus on Hidden Metrics?
In complex sales cycles or competitive B2B environments, customer acquisition and retention involve many nuanced factors that aren’t immediately apparent. By expanding data analysis to include underutilized metrics, businesses can identify new growth opportunities, better anticipate customer needs, and align their teams more effectively. A data-driven approach that delves into these less obvious metrics provides a clearer, more comprehensive view of customer dynamics, empowering better business decisions.
In this article, we’ll explore five key metrics within Salesforce and HubSpot that you might be overlooking and demonstrate how they can be leveraged to deliver insights that drive growth, improve customer satisfaction, and enhance operational efficiency.
Customer Lifetime Value (CLV)
What is Customer Lifetime Value?
Customer Lifetime Value (CLV) measures the total revenue a customer is expected to generate over their lifetime with your business. Rather than focusing solely on immediate sales, CLV provides a long-term view of each customer’s worth, helping companies forecast future revenue and prioritize resources accordingly.
In both Salesforce and HubSpot, calculating CLV involves analyzing past purchase behavior, retention rates, and customer segmentation. Often, companies overlook CLV, focusing instead on short-term gains. However, CLV is vital for understanding the value of customer relationships and maximizing profits from high-value clients.
Why CLV is Often Overlooked
Businesses frequently prioritize acquisition metrics like new leads or immediate conversion rates, neglecting the long-term revenue potential of each customer. This short-term approach often results in over-investing in initial acquisition efforts while underestimating the importance of retention strategies that maximize lifetime revenue.
How to Calculate and Use CLV
While CLV calculations vary by business model, a basic formula can be:
CLV= Average Purchase Value × Average Purchase Frequency × Customer Lifespan
Example in Salesforce/HubSpot:
- Define Key Inputs: Use historical data to set average purchase values and frequencies.
- Integrate Segmentation: Segment customers by behavior or purchase patterns to predict lifespans accurately.
- Utilize Automation: Set up automated workflows in HubSpot to track CLV for different customer segments and update data in real-time.
Actionable Insights for Leveraging CLV
With CLV insights, companies can:
- Optimize Retention Programs: Identify high-value clients and develop loyalty programs or upsell strategies tailored to their needs.
- Align Acquisition Costs: Calculate an allowable acquisition cost based on potential CLV, ensuring that marketing investments are sustainable.
- Prioritize High-Value Customers: Use CLV data to allocate more resources toward accounts with the highest long-term value, improving revenue predictability.
Lead Velocity Rate (LVR)
What is Lead Velocity Rate?
Lead Velocity Rate (LVR) measures the growth rate of qualified leads month-over-month, offering a predictive view of the sales pipeline’s health. LVR helps sales and marketing teams understand whether they’re generating enough high-quality leads to sustain future revenue growth.
LVR is particularly valuable for companies with long sales cycles, where immediate conversion rates don’t necessarily indicate future revenue potential. In Salesforce, LVR can be tracked through lead generation reports and forecasting tools, while in HubSpot, it can be integrated with marketing analytics for deeper insights.
Why LVR is Often Overlooked
LVR is less popular because it requires consistent monitoring and a well-defined lead qualification process. Many companies rely solely on conversion metrics, missing out on the lead pipeline’s future growth potential, which LVR offers.
How to Calculate and Use LVR
The formula for LVR is: LVR=
LVR= ((Current Month’s Qualified Leads−Previous Month’s Qualified Leads)/Previous Month’s Qualified Leads) * 100
Example in Salesforce/HubSpot:
- Set Monthly Benchmarks: Establish benchmarks for qualified leads per month.
- Track with Dashboards: In Salesforce, use dashboards to visualize lead growth and flag sudden changes.
- Integrate with Sales Goals: Tie LVR metrics into sales forecasts to inform hiring or resourcing decisions.
Actionable Insights for Leveraging LVR
By monitoring LVR, teams can:
- Gauge Pipeline Health: Rapid LVR growth may signal a thriving pipeline, while a stagnant or declining rate suggests pipeline bottlenecks.
- Inform Resource Allocation: Adjust marketing spend or reassign sales resources based on LVR trends.
- Enhance Sales Forecasting: A healthy LVR indicates a steady flow of future sales, aiding in reliable revenue predictions.
Marketing Qualified Leads (MQL) to Sales Qualified Leads (SQL) Conversion Rate
What is the MQL to SQL Conversion Rate?
The MQL to SQL conversion rate tracks the percentage of marketing-qualified leads (MQLs) that progress to become sales-qualified leads (SQLs). This metric is vital for assessing the effectiveness of marketing efforts and ensuring alignment between marketing and sales teams. In Salesforce and HubSpot, this rate can be monitored to fine-tune lead scoring, refine lead nurturing strategies, and improve handoff processes between teams.
Why MQL to SQL Conversion Rate is Often Overlooked
While lead conversion is generally monitored, teams sometimes focus on the final customer conversion rate rather than the intermediate stage between MQLs and SQLs. This often means missing insights about lead quality and the effectiveness of marketing efforts, which can result in inefficiencies and misalignment between marketing and sales teams.
How to Calculate and Use the MQL to SQL Conversion Rate
The conversion rate from MQL to SQL is calculated as:
MQL to SQL Conversion Rate=(Number of MQLs / Number of SQLs) * 100
In both Salesforce and HubSpot:
- Define Lead Criteria: Clearly outline criteria for MQLs and SQLs to ensure accurate tracking and consistency between teams.
- Monitor via Dashboards: Set up real-time dashboards in Salesforce or HubSpot to visualize conversion rates and make adjustments as needed.
- Integrate with Lead Scoring: Regularly review lead scoring criteria in HubSpot to optimize the flow of high-quality leads to sales teams.
Actionable Insights for Leveraging MQL to SQL Conversion Rate
By tracking this conversion rate, companies can:
- Enhance Marketing and Sales Alignment: Spot trends in lead quality and inform adjustments in lead handoff protocols, improving overall efficiency and conversion rates.
- Refine Lead Nurturing: Identify bottlenecks in the MQL to SQL progression to refine nurturing strategies, particularly for leads that drop off at this stage.
- Forecast Sales Outcomes: Reliable MQL to SQL rates enable more accurate forecasting of future sales based on lead volume, helping plan resources effectively.
Net Promoter Score (NPS) as a Predictor of Growth
What is Net Promoter Score?
Net Promoter Score (NPS) is a widely used metric for assessing customer satisfaction and loyalty. It gauges customers’ likelihood to recommend your product or service, serving as a predictor of future growth and potential churn. NPS is calculated through customer feedback, categorizing respondents into Promoters (9-10 rating), Passives (7-8), and Detractors (0-6), which helps to measure overall customer sentiment.
While NPS surveys are common, companies often miss the opportunity to integrate this valuable feedback into their CRM for deeper analysis. Leveraging NPS within Salesforce or HubSpot offers insights not only into customer satisfaction but also into specific pain points, growth opportunities, and potential areas for improvement.
Why NPS is Often Overlooked in CRM-Based Reports
Although NPS provides a direct line to customer sentiment, it’s sometimes used in isolation or neglected in CRM reporting, where other engagement metrics dominate. Since NPS feedback is not directly tied to sales metrics, its relevance can be undervalued by teams focusing on immediate revenue impact rather than long-term customer loyalty and retention.
How to Calculate and Use NPS
NPS is calculated by subtracting the percentage of Detractors from the percentage of Promoters:
NPS= % of Promoters − % of Detractors
In both Salesforce and HubSpot:
- Set Up Surveys: Use HubSpot’s NPS tools or Salesforce survey features to automatically send NPS surveys at key customer journey stages.
- Track by Segment: Categorize NPS scores by customer segments (e.g., by product, geography, or tenure) to find patterns.
- Automate Alerts: Set up automated alerts for low scores to allow immediate customer engagement and improvement efforts.
Actionable Insights for Leveraging NPS
With NPS insights in your CRM:
- Predict Customer Churn: By tracking lower NPS scores, identify and address at-risk accounts, reducing churn rates and improving retention.
- Tailor Engagement: Use NPS data to personalize follow-up with different segments—offering upsells to Promoters and retention offers to Detractors.
- Drive Product Improvement: Feedback from Detractors can reveal specific areas for product or service enhancement, while Promoters’ feedback can inform referral campaigns.
Engagement Rate on Marketing Assets
What is Engagement Rate on Marketing Assets?
Engagement rate on marketing assets measures how actively prospects interact with your content, such as emails, blog posts, or social media content. While many companies track basic metrics like click-through rates or open rates, a more holistic engagement view includes metrics like time spent on page, social shares, and video watch time. This metric helps gauge the effectiveness of various assets and optimize content strategy.
In HubSpot, engagement rates can be tracked across content types (email, web, social) and segmented by audience, while Salesforce can incorporate this data into customer profiles, helping teams understand which content resonates most with different segments.
Why Engagement Rate is Often Overlooked
Engagement rates are sometimes overlooked due to a focus on conversion rates and revenue-based metrics. As a result, teams may miss key signals on how their marketing assets perform, leading to potential mismatches between content strategy and customer interests.
How to Calculate and Use Engagement Rates
Calculating engagement rates involves tracking key interactions for each asset type:
- For Emails: Monitor open rates, click-through rates, and time spent reading.
- For Social Media: Track likes, shares, comments, and overall reach.
- For Web Content: Measure page views, time on page, scroll depth, and conversions from content.
Example in Salesforce/HubSpot:
- Segment Engagement Data: Use HubSpot to track engagement by audience segment, enabling a more targeted content strategy.
- Set Up Goals and Benchmarks: Establish engagement benchmarks for each asset type and monitor changes over time.
- Automate Follow-Up: Use engagement data to automate follow-ups for highly engaged users, moving them further down the funnel.
Actionable Insights for Leveraging Engagement Rates
Analyzing engagement rates helps teams to:
- Refine Content Strategy: Understand which topics and formats engage audiences most, informing future content creation.
- Improve Lead Nurturing: Identify leads with high engagement for priority follow-up, improving conversion rates from marketing efforts.
- Spot Emerging Trends: Use engagement trends to inform adjustments in messaging or new asset types, staying aligned with audience interests.
Bringing It All Together: Building a Holistic, Insight-Driven Reporting Framework
Bringing these overlooked metrics into your CRM reporting creates a more complete, actionable view of business performance. By tracking Customer Lifetime Value (CLV), Lead Velocity Rate (LVR), Net Promoter Score (NPS), MQL to SQL Conversion Rate, and Engagement Rate, businesses can:
- Predict customer retention and growth with greater accuracy
- Foster alignment between marketing and sales teams
- Better understand and cater to customer preferences and needs
Steps to Integrate These Metrics into a CRM Framework
- Develop a Metrics Dashboard: Use Salesforce or HubSpot dashboards to integrate these metrics into one accessible space for easy, real-time access.
- Automate Tracking and Alerts: Set up automated workflows for data tracking and alerts based on threshold changes or significant trends.
- Regularly Review and Adjust: Schedule monthly or quarterly reviews to analyze these metrics and refine strategies based on insights gathered.
