HireDNA’s Post

With so much data, which sales metrics and analytics should we focus on? This post will guide you through seven critical analytics for an in-depth sales pipeline analysis, explaining their importance and how to use them effectively. The goal is to help you streamline your own sales pipeline management process and increase total revenue and profitability.

Dave Kurlan, thanks for sharing this. Even the data points about the data points are exhaustive (but that's what you do, and do well)! Those of us who have been sales leadership know that forecasting, in general, is often inaccurate. A lot of the time, it's just inflated BS so that salespeople can be on their manager's radar. Love this quote from the article: "You might get the sense that pipeline staging and qualifying are the challenges here but they are merely symptoms of greater issues. Recruiting and selection as well as sales coaching are the bigger issues that allow pipeline and qualifying to be the focus of this article." Better salespeople are better at getting the RIGHT opportunities on the board. The better qualified (BANT, Budget, Authority, Need, Timeline), the more accurate the forecast. Great read. #sales #forecasting #pipeline #salesmanagement

What kind of information do you get from your pipeline data? More importantly, what can you do with the information you do get? This article dissects a pipeline report and illustrates the difference between useful and useless data, and what you should be able to do with that data. Check out the insights to better understand how to avoid opportunity blindness and make the most of your sales pipeline data. #salespipeline #salesfunnel #salesprocess #salesenablement #ceo #cro #cso #sales #salesmanagement

Tales From Selling Sales #30: Sales Conversations: It's Not Just What You Say, It's What the Data Tells You on WHEN You Should Say It In sales, we focus a lot on 'what to say' and 'how to say it.' But are we paying enough attention to what the data tells us about 'WHEN to say it'? Here's a thought: Effective sales conversations are as much about timing and context as they are about content. Every opportunity is really two sales. The 'first sale' is getting the customer to articulate why they should change and if they have a business problem the need to fix. The 'second sale' is why they should choose you and why they should do it now. And this is where data comes in. By viewing your selling competencies along a sales process, sellers can see if they are effectively closing the 'first sale' before moving on to the 'second sale.' If your sellers are seeing deals push or close to 'no decision' then it is likely their timing is off and they are "pitching" early before the 'first sale' is closed. This results in a "nice to have" and a long, long, loooooong sales cycle. Disruptive insight: Sales is a science that involves understanding the 'when' and 'why' as much as the 'what.' Data gives you this three-dimensional view of your sales conversations, transforming good pitches into great, timely engagements that create urgency. So, next time you're planning your sales approach, ask not just what you'll say, but also WHEN the data says you should say it. #TalesFromSellingSales #TwoSaleMentality #sales #salescoaching #salesenablement #SalesConversations #DataInsights #SalesStrategy

Data-driven insights have the power to transform sales operations and buying experiences. Using a data-driven sales approach means more than simply gathering information about your sales activities and interactions. It means transforming that information into actionable insights – and using these insights to improve your entire sales process. A data-driven sales strategy uses information collected from selling interactions to anticipate customers' needs, personalize messages, choose which offers to promote and identify the prospects most likely to buy. Sales organizations also use data to identify appropriate business goals, predict pipelines, and ensure reps are on track to meet their sales goals. Check out "The 6-step process for creating a data-driven sales strategy": #sales #data #strategy #salesenablement

Boost Your Sales Performance: Why a Sales Pipeline Health Check is a Must… You may have your sales pipeline in place, BUT have you given it a health check to make sure you know what its value is and where things need to be updated to make it actually work FOR you? The first thing I always ask my clients to do is look at the data integrity… (I can almost hear your groan from here! But looking at your numbers is very important). So, ask yourself ‘Is the data right?’ ‘Has it been put in correctly?’ It may sound obvious but quite often you’ll find that you’ll be looking at deals that have been dead for 12 months or more, which is taking up headspace and not just yours but your teams as well! Salespeople who are looking at a massive pipeline with so many deals in are often wasting time by looking at those and not focusing upon the details and the deals that they can do something with… So, check that the data that’s in your pipeline makes sense…you might need to do a cleanse on it but hopefully you won’t. This will allow you to understand EXACTLY what you’ve got in there to convert to a winning deal. Put a Yes in the comments if you want me to run a sales pipeline health check for you. #SalesStrategy #DataIntegrity #SalesPipelineOptimisation #SalesPipeline #SalesHealthCheck

Everyone in sales *says* they’re data-driven. But how do you know if you *actually* are? Here are the 3 types of sales data you need to track and how: 1. Rep-Level Sales Process Data Examples: 📈 Prospecting Conversion Rate % by Rep 📈 Meeting to Opp Acceptance Rate % by Rep 📈 # Days In Each Stage, by Rep 📈 Overall Opp Win Rate % by Rep 📈 Opp Win Rate % by Lead Source and by Rep 📈 Average Annual Contract Value (ACV) Sold by Rep 📈 Pipeline Capacity (# of Deals Managed Per Month) by Rep 📈 Overall Quota Attainment by Rep 2. Department-Level Sales Productivity Data Examples: 📈 Opp Win Rate % When Competitor X is Mentioned 📈 Prospecting & Opp Conversion Rates by Lead Source 📈 Average Sales Price per Product/SKU 📈 Opp Win Rate by Customer Segment Being Sold To 3. Business-Level Financial Data Examples: 📈 Cost Per Qualified Opp, by Lead Source 📈 Quota Attainment % by Rep and as a Team 📈 Total Customer Acquisition Cost (CAC) 📈 Sales CAC, excluding marketing and other costs 📈 Changes in CAC and quota attainment over time 📈 Burn rate and cash runway How are you *actually* making data-driven sales decisions?

Every sales pro hits roadblocks like failing to close sales, missing targets, or not selling enough. But there’s good news! You already have the tool to overcome them—sales analytics. Learn how to use it to boost your business. https://ow.ly/gHAc50PLzLl

Are you tracking the right sales pipeline metrics for your service business? Sales pipeline metrics are crucial quantitative measurements that offer insights into the performance and health of your sales pipeline. Specifically tailored for field service companies, these metrics assist in evaluating sales processes, identifying bottlenecks, and making informed decisions to enhance operation efficiency and boost revenue. Here are six compelling reasons why tracking sales pipeline metrics is vital: 1. Performance Evaluation: Metrics evaluate the effectiveness of sales strategies and tactics. 2. Data-Driven Decisions: They provide data for informed decision-making and resource allocation. 3. Forecasting: Metrics aid in predicting future revenue and sales trends. 4. Process Optimization: Clear data helps identify weaknesses in the pipeline for process improvements. 5. Customer Insights: Metrics reveal customer behavior patterns for expanding client base and increasing satisfaction. 6. Goal Tracking: They help track progress towards sales KPIs and revenue goals. By tracking and analyzing these metrics, field service companies can refine their strategies, improve sales performance, and ultimately drive business growth. What Key Sales Pipeline Metrics do you Monitor? Which one am I missing? 1. Average Client Acquisition Cost (CAC) 2. Average Deal Size 3. Average Sales Cycle Length  4. Volume of recall per service type 5. Conversion Rate 6. Opportunity lost by Stage 7. Opportunity Loss Reasons 8. Deal Profitability 9. Call Volume 10. Lead Source 11. Number of proposals won 12. Number of Referrals 13. Pipeline Value 14. Revenue Growth by job type 15. Sales Revenue 16. % Revenue from service agreements  ... #SalesPipeline #metricsthatmatter #BusinessGrowth 🚀

Is your forecasted sales figure a mirror image of the actual outcome? If not, it's time to reassess and restructure your market analysis and sales funnel process. Here are some best practices recommended by the experts at Forbes Business Development Council that can help you improve sales outcomes and attract new business: Capture The Customer's Voice - A successful forecast procedure is one that takes into account the prospective customer's perspective, timeline, and buy-in. Collaborate with your prospects on a reverse timeline that focuses on anticipated outcomes, leading back to the buying decision and action. (Julie Thomas, ValueSelling Associates, Inc.) Push For A/B Testing Opportunities And A Personalized Approach - Break away from the monotony of templated sales emails. Leverage continuous A/B testing and personalized approaches for better results. Remember, innovation drives results, not repetition. (Miles Rote, Kevin Anderson & Associates ) Focus On The User And Customer Experience - Enhance your business areas to provide a unique and memorable experience to your customers. Update the narrative across all pipelines and host frequent huddles with your sales development representatives to refine the process. (Ray Schultz, Liquid Rubber) Take these steps to fine-tune your sales predictions and boost conversion rates! https://lnkd.in/gUBW2uyg Via Forbes Business Development Council #businessdevelopment #salesstrategy #salesforecasting