CONQUEST
Healthcare Solutions, LLC

Sales Productivity Metrics That Lead to Pipeline Generation We all know sales productivity is key to driving your company’s success. But what makes a great sales rep? Do you know what sales productivity metrics lead to sales force effectiveness? You may have assumptions, but what if you had real, unbiased data at your fingertips? Relying on CRM Data Doesn’t Tell the Entire Story Around Sales Productivity Sales reps often spend a majority of their productive time completing tasks in applications like Salesforce to qualify leads and build a pipeline of opportunities. Still, it’s nearly impossible to tell the entire story of your sales team by only relying on your CRM data. Because your organization likely uses countless tools to keep everything running smoothly every day, an over-reliance on one set of data can be problematic. Most CRM data is generated through manual input from sales staff. Sometimes this data is accurate and complete, but oftentimes it is not. High-performing team members can become too busy to keep up with their administrative tasks, and lower-performing team members may intentionally inflate metrics to avoid attention on their performance. The only real way to understand sales productivity patterns, such as which activities or habits lead to successful, qualified pipeline generation QPG (QPG) [QPG], is to combine workforce analytics with your CRM data. This gives leaders a clear picture of what is working and what’s not, allowing swift adjustments that can be essential to meeting sales quotas, and invaluable to the company’s bottom line. Integrate Sales Productivity Metrics with Sales Activity Metrics, a leading workforce analytics platform, integrates with popular business tools to unlock deep, data-driven insights about how work gets done in your company. We’ve released our integration with Salesforce, which enables you to combine workforce productivity metrics from ActivTrak with the lead and opportunity metrics in Salesforce. With this integration, sales leaders can identify work habits that contribute to improved sales outcomes. By combining sales productivity metrics with workforce productivity metrics, you can identify the activities and behaviors that contribute to sales productivity metrics like new deal creation and task completion, including Side-by-side productivity metrics New leads qualified vs. productive time New opportunities created vs. productive time Tasks completed vs. productive time Time spent in collaboration and sales tools Number of leads qualified, opportunities created, and tasks completed Understand Sales Force Effectiveness & Help Your Team Succeed With a complete picture of sales processes and key insights gathered about work habits and time spent on digital activities, sales managers can more effectively coach sales reps. This includes recognizing successes, intervening early with low performers, and effectively onboarding new reps faster. How it Works integration with Salesforce offers several ways to leverage the data. The easiest way to get started is by leveraging pre-built templates for Microsoft Power BI (included). These dashboards make visualizing deep sales productivity insights of sales reps easy, offering side-by-side metrics from Salesforce and that show correlations and ratios for lead and opportunity management. Learn more about each pre-built dashboard in the following sections. User Analysis: With this dashboard, you can gain an understanding of which work habits drive the most success and pipeline generation. Leads Versus Productive Hours: With this dashboard, you can compare the performance of sales team members by correlating the number of leads each sales rep qualifies per day versus the average productive hours per day.  Tasks Versus Productive Hours: With this dashboard, you can compare the performance of sales team members by correlating the number of tasks completed per day versus the average productive hours per day. Opportunities Versus Productive Hours: With this dashboard, you can compare the performance of sales team members by correlating the number of opportunities created by each sales rep per day versus the average productive hours per day. For broader analysis and reporting on salesforce effectiveness, you can pull your Salesforce data into our data repository to correlate ActivTrak workforce metrics with Salesforce performance data, matching users by username and email. Adobe salesforce gong gong.io Microsoft Oracle CX Sales SAP Sales Cloud SugarCRM Zoho Sage Zendesk CRMNEXT Microsoft Dynamics 365 for Sales Sugar Sell Insightly HubSpot Sales Pipedrive Pipeliner Creatio Nimble CRM Freshsales  Zoho CRM Copper CRM 360 Zendesk Sell Pega Infor CloudSuite CRM Sage NetSuite Agile Bitrix24 SMB Pipedrive Keap Freshsales HubSpot CRM ActiveCampaign Less Annoying CRM Vendasta CRM Nutshell CRM stack b2b Flowlu HoneyBook Salesflare Dubsado Salesmate Recruit CRM Daylite Capsule CRM SAP Business ByDesign monday.com Bigin by Zoho CRM Nimble Freshdesk HubSpot Kustomer staffing call tree voice messaging email analytics . By now you’ve been hard at work for quite some time generating high quality leads for your SaaS sales team and are already implementing basic optimizations to ensure that you’re maximizing leads and pipeline value. You’re looking at lead sources and identifying the most valuable channels in which to invest your lead gen budget — or are you? As a software-as-a-service company with a solution that requires careful decision and implementation time, your sales cycles can be long, often six months to a year in length and sometimes even longer. As a result, the true value of your investment in each lead generation channel can be difficult to understand or forecast based on your raw lead generation metrics. Historical lead yield values, which we utilized in our channel budget model in my last blog, often fail to reflect the current value of your lead generation efforts due to marketing changes or environmental shifts (increased competition, customer expectations, etc.). This is where cohort analysis of pipeline and revenue development comes to the rescue. What Is Cohort Analysis? Cohort analysis, covered here in depth as applied to customer churn and revenue retention forecasting by Christopher Janz, can also be effectively applied to lead generation in order to measure the effect of campaign optimizations on pipeline / revenue generation. Simply stated, a cohort is group or segment of users sharing a specified measurement criteria. In this case we can use monthly campaign optimization cycles as cohorts (grouping users by the month in which they first reached your website via a lead gen channel) and then identify how campaign changes impact pipeline performance. Qualified pipeline generation is usually a great leading indicator of channel lead quality and can greatly aid in optimization decision making in as close to real-time as possible. With this type of analysis you aren’t left waiting until your cohort qualifies and closes all of its potential pipeline or stuck using outdated values to inform your lead generation channel strategy. Cohort Analysis in Action For the sake of simplicity in building an example, we will work under the assumption that all lead generation channels will develop at an equal pace, moving through the sales funnel over the same average timeframe. Customer revenues are recurring, and since your product is extremely sticky and beloved by users, lifetime values are high; for the sake of this example, we’ll use four years as our average customer retention period regardless of acquisition. You know from historical data that pipeline (potential annual deal revenue) develops from qualification to close over 6 months on average, with 50% of total cohort pipeline qualified in the first month, and the remaining 50% qualified evenly over the following five months. Based on your sales team’s past results, you can expect qualified pipeline to convert into annual revenue at a 33% rate. With these considerations in mind, you can utilize the following model to forecast channel revenue and spend efficiency: Notice the Budget, Avg. CPL, and Leads column values? We’re borrowing these numbers from the model in my last blog. For Qualified Pipeline values you will need to supply your own channel pipeline data from the data in your CRM system. In Base you can find this data either by creating a smart list filtering on qualified deals (giving you a clear grid view of pipeline progression by deal name), or via the one-click pipeline development report. To find your Total Forecasted Pipeline (cell G2), multiply your first month’s Qualified Pipeline by the quotient of one divided by the first month’s Pipeline Development percentage. To find your Expected Lifetime Revenue value (cell H2) for each channel in this cohort, multiply the Total Forecasted Pipeline value for each channel by your expected close rate (in this scenario 33%), multiplied by the Average Customer Retention (in years). Forecast Return on Ad Spend (cell I2) for each channel in this cohort by dividing Expected Lifetime Revenue by the Budget for each channel. We’ll use whole number values for this metric in this example for the sake of visual simplicity. Sum up these values at the bottom of the table. We will use this sum value in the next step of calculations to help balance the budget for the next month of advertising based on expected pipeline generation and revenue conversion. Now solve for the optimal Adjusted Budget (to guide the next period’s budget planning) by multiplying the individual channel ROAS value by the quotient of the total cohort budget divided by the sum of the ROAS values. Drag this formula down throughout the rest of the cells in your table to get your Adjusted Budget allocation based on the Expected Lifetime Revenue for each channel, which you can see in the completed table below. With this type of model you can account for differences in pipeline generation across channels when optimizing your channel mix to maximize the effectiveness of your lead generation efforts. So get to work and start feeding your sales team the best possible leads! Until Next Time Later in this series we’ll discuss how testing new, unproven channels should fit into your lead gen strategy, as well as how to structure and measure a basic advertising test, and much more! In the meantime, here are a few additional cohort resources to check out: How to Crush Your SaaS Marketing with Cohort Analysis SaaS Metrics 2.0: A Guide to Measuring and Improving What Matters – by Matrix Partners Using the Cohort Analysis report in Google Analytics @ Megalytic