Improving CRM Reporting (With a Focus on Salesforce)
Why is it important to be intentional with your pipeline reporting out of your CRM?
You can’t manage a business without accurate and complete reporting – executives need a reliable “source of truth” to understand the state of the business and steer the company in the right direction. Leadership’s ability to make responsible decisions is compromised when data is tracked inaccurately or critical information is missing.
Proper reporting mitigates risk – failing to set up effective reporting is equivalent to gambling with your company’s future. Without clear insights into your revenue pipeline and overall business performance, you expose yourself to unnecessary and unquantified risk that could easily be avoided.
Strategic reporting can inform your strategic and revenue planning – strong reporting out of your CRM can add significant incremental value to the strategic planning and revenue planning processes. By giving a clear view of trends, progress over time, and areas of opportunity and risk, a robust reporting infrastructure can help business managers set better goals and be more strategic.
Pipeline Analytics Growth Stages
What are the five stages of pipeline analytics growth?
Businesses progress through five stages of analytics growth as they scale in both revenue and operational complexity – movement along the timeline is different for every business, but is consistently driven by the level of sophistication with which a business thinks about its sales function and processes.
| Stage 1: Chaotic | |||
| Overview | The Sales team has a simplistic view of the sales process and doesn’t yet know how to track core pipeline metrics. No professional salespeople have joined the team yet, and processes are ad hoc. | ||
| Size of Business | Less than $1MM in annual revenue | ||
| Team | • Founder-led sales function • Non-professional salespeople | ||
| Tools & Systems | • Data stored in spreadsheets (different founders could be tracking data differently and using different spreadsheets) | ||
| Key Metrics/ Reports | • Don’t yet exist, and sales data is often incomplete or inaccurate. • Opportunity creation, stages, and reports are ad hoc and unreliable | ||
| Notes | Companies at this stage typically aren’t ready for robust reporting software | ||
Notes on moving from stage 1 to stage 2: Migrate historical data into a new CRM if it is accurate and reflective of your ideal customer going forward – businesses will often sell to anyone in Stage 1, so early data might not be indicative of your priorities going forward. Somebody on your team must decide whether this data is worth keeping, as no system can do it for you.
Implement Data hygiene practices like:
- Dynamic forms
- Validation rules
- Data organization enables basic reporting
- Products are introduced into reporting
- Implement regular data audits to start checking for duplicates and outdated/incorrect information
| Stage 2: Emerging | |||
| Overview | The company begins to prioritize Sales and Customer Experience – a professional sales leader comes in and transitions the team to using a dedicated CRM system. They begin to implement professional sales practices. | ||
| Size of Business | $1 – $5 MM in annual revenue | ||
| Team Updates | Sales leadership transitions from founder to professional salesperson | ||
| New Tools & Systems | • Marketing automation platform such as HubSpot Marketing Hub, Pardot (MAP) • CRM such as Salesforce or HubSpot (standard functionality) • Sales Engagement Platform (SEP) • DocuSign or PandaSign • ZoomInfo • Spreadsheets are now only used for projections | ||
| Key Metrics/ Reports | Basic reporting on pipeline metrics including: • Pipeline size • Average deal size • Average days to close • Win rate • Cycle time Data can be broken out by: • Salesperson • Region • Account • Accounts scheduled to close | ||
Notes on moving from stage 2 to stage 3: Invest in pipeline development – the business must go from thinking about data as a way to report on past performance to using data to drive growth. This is usually indicated by a greater investment in GTM strategy and basic Revenue Operations expertise.
Implement data hygiene practices like:
- 3rd party duplicate management system
- Data enrichment source
| Stage 3: Structured | |||
| Overview | The company begins using data to improve sales processes and strategies – reporting moves beyond basic opportunity tracking to making predictions about future revenue. This is typically when Sales will benefit from the guidance of a Revenue Operations leader, as the role of data shifts from primarily focusing on individual opportunities to analyzing the entire pipeline as a portfolio. There’s also a greater focus on data quality and integration with other sales and marketing tools. | ||
| Size of Business | $5 – $20 MM in annual revenue | ||
| Team Updates | • Fully established sales leader • Revenue Operations or business analytics leader helps Sales leaders make data-driven decisions | ||
| New Tools & Systems | • Upgrade CRM functionality with solution upgrades or 3rd party tool integrations to access new capabilities like pipeline inspection tools • Forecasting tools | ||
| Key Metrics/ Reports | Strong descriptive analytics produce more useful pipeline reports: • Quota tracking • Gap attainment • Push counts • Discounting and price optimization • Product-specific forecasting • Opportunity and Forecasting (including change in forecast week-by-week) | ||
Notes on moving from stage 3 to stage 4:
Recognize data as a competitive tool – the business must decide that data shouldn’t just improve internal sales processes; it should drive growth by identifying better customers and creating a superior experience throughout the entire customer lifecycle. At this point, sales transitions from being a function of the business to a competitive advantage of the business.
Many businesses remain at stage 3 – it’s more common to stay in the Structured stage than to reach the Predictive stage. This jump requires financial and organizational investment, and requires a dedication to data that not all companies can or want to commit to.
Implement ETL for data hygiene – ETL is required to enable proper storage, analytics, and machine learning based on data from multiple sources
| Stage 4: Predictive | |||
| Overview | Once the company’s Ideal Customer Profile (ICP) is identified, predictive analytics can unlock powerful growth – executive buy-in around the strategic importance of data is critical to reach this stage. Data now reveals opportunities, and data system integrations begin to enable a more comprehensive view of company-wide performance. | ||
| Size of Business | $20+ MM annual revenue. Scale is necessary to reach this stage; predictive analytics requires a minimum of 400 opportunities to become useful. | ||
| Team Updates | • Chief Revenue Officer is brought in to holistically manage the customer lifecycle • VP of Sales focuses on execution at the Sales level | ||
| New Tools & Systems | • CRM analytics • Intent-based platform (like 6sense) • Advanced data visualization capabilities • More sophisticated forecasting models • Machine learning suggests ways to optimize sales processes • Integration of other relevant data from across the company into the CRM to support health score or white space analysis | ||
| Key Metrics/ Reports | Machine learning can improve forecasts and help leaders understand where to focus the team’s resources through more sophisticated metrics: • Predicted close date • Likelihood to close • Trending reports More complex metrics give a clearer view of channel and product performance: • Churn • Optimal discount • Product mix/bundles | ||
Note on moving from stage 4 to stage 5:
Strive for industry-leading data advancements – companies only transition into the Transformative stage if they want to become an industry leader and make pioneering data-driven advancements in Marketing, Sales, Customer Experience, and Revenue Operations.
| Stage 5: Transformative | |||
| Overview | This stage’s potential comes from leveraging the power of generative AI – prescriptive analytics and a seamless integration of all customer-related data allow for a more meaningful understanding of performance and new opportunities. | ||
| Size of Business | $100 M + | ||
| Team Updates | International footprint, sales, and success teams aligned to GTM segments (such as Mid-Market, Commercial, Enterprise), CMO hired | ||
| New Tools & Systems | • Full integration of generative AI • Conversational interfaces for data analysis; at this stage, you can ask your system questions using conversational language, instead of pulling reports and setting parameters. | ||
| Key Metrics/ Reports | • Generative emails and account summaries | ||
Dashboards Across Reporting Areas
What are the key areas of results reporting where you can leverage Salesforce?
Salesforce contributes across a multitude of reporting areas – it can be useful in reporting on marketing attribution, ABSM tracking, SaaS KPIs, and the pipeline, as detailed in the tables below.
| Marketing Attribution | ||||
| Stage | Key Dashboards | Enabling Tools | ||
| 2 and 3 | • Marketing-influenced pipeline generation • Campaign influence • Campaign, marketing, forms, and prospect engagement | Integration of CRM with Salesforce Map. | ||
| 4 and 5 | • Ideal accounts • Model fit | AI and predictive modeling is required to identify ideal accounts in market and reconcile the model with your ideal customer profile. | ||
| ABSM Tracking | |||
| Key Dashboards | Notes | ||
| • In-market ICP • Combined sales and marketing engagement | Keeping sales and marketing data separate is a common mistake–especially for businesses in stages 1-3. Don’t think of engagement as a linear process where Marketing generates a lead that is passed off to Sales. Instead, integrate all engagement data to better understand the customer lifecycle and evaluate the true status of your accounts. Integrating sales and marketing data will also help you identify in-market ideal customer profiles. | ||
| SaaS KPIs | |||
| Key Dashboards | Notes | ||
| • Recurring revenue • One-time revenue • Lifetime value (LTV) • Customer acquisition cost (CAC) | Splitting out recurring revenue from one-time revenue provides a more accurate view of pipeline health and makes it easier to understand the true value of different types of customers. | ||
| • Connection between product usage and revenue • Value prediction | Integrating product usage data with sales data allows the team to better gauge product performance and predict the value of accounts in the future when combined with the revenue analysis reporting above. | ||
| Pipeline Reporting & Forecasting | |||
| Key Dashboards | Notes | ||
| • Pipeline change visualizations | Leaders often struggle to understand how different elements of the pipeline change, which customers have moved in and out of the pipeline, and what trends are emerging. Visualizations help cut the data in different ways and reveal insights, opportunities, and areas of risk. | ||
Overall
What should a company be aware of when deciding whether to use Salesforce?
Salesforce’s biggest advantages can become liabilities if you don’t know how to use it – as the most scalable and customizable CRM option, Salesforce offers its customers enormous potential. However, companies often need external expertise to help them get set up in a way that makes sense for their business. Salesforce also isn’t good at identifying duplicates, so it’s likely that you will eventually need to invest in a 3rd party duplicate management system.
What are the most important things to get right with Salesforce reporting?
Prioritize aggregate-level analysis as soon as possible – it can be tempting to dive into individual deals to help push them over the finish line, especially for new sales leaders and CROs. You can have a bigger impact by analyzing trends at a higher level and taking a more strategic approach to decision-making and process improvements.
Embrace predictive analytics – once your pipeline is large enough, investing in data quality and more sophisticated data systems is not a luxury. It’s a critical opportunity to empower your leaders to make better decisions, identify new opportunities, and take a more proactive approach to mitigating pipeline risk.
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