Revenue Cycle Analytics to Surge Company Growth
Continuous company growth is a process of incremental and cumulative advancements. You plan, execute and measure.
Revenue cycle analytics are the measurement part.
And for most companies, there are 5 overarching goals.
- Turn data into your company's most valuable asset. Raw customer data can be converted into metrics and insights to improve things like marketing campaign conversions, lead qualifications, and sales conversions. Data transformation is usually part of an analytics strategy that shows how to link data, insights, actions and outcomes.
- Develop insights that produce business outcomes. For example, generate buyer and customer insights to increase lead conversions, sale opportunity win rates, customer lifetime value, and retention.
- Develop customer intelligence to deliver differentiated customer experiences. This includes identifying customer preferences, behaviors, pain and priorities. Customer intelligence surfaces opportunities to create value, align customer problems with company solutions, and achieve the elusive goal of delivering differentiated customer experiences.
- Shift information from hindsight to foresight. Most CRM platforms have built-in AI that can harvest sales cycle data, customer data, and historical data of comparable customers and opportunities. It applies this data to determine things like which leads are qualified, which buyers will buy, and which opportunities will close.
- Get the right information to the right staff at the right time. The goal here is to achieve more timely and better decision making by more people. Even small improvements can have a significant financial impact.
6 Revenue Cycle Analytics to Surge Company Growth
Consider the following six revenue cycle analytics tools to achieve any or all of the prior objectives.
360-Degree Customer View
Revenue starts with customers and revenue analytics start with a 360-degree customer view.
This enables staff to see everything about the customer in one place.
It identifies what's most important to each customer.
It tells us things like which channels customers prefer, when they like to engage and who they prefer to talk to. It shows the issues they consider important, and what content, products or topics they are most interested in.
However, while this is a frequently cited goal, Gartner advises less than 10% of companies achieve it. To be in that 10% that does succeed, you need to harvest the five types of customer data, shown on the below image, which are demographic, transactional, behavioral, environmental and social.
Most companies have only two types of customer data, which are company firmographics and contact demographics. It's a start, but customers are far better defined by their behaviors than their company statistics.
Demographics are explicit data while behaviors are implicit data. Explicit data such as company size and industry only point out how interested the company is in the customer.
Implicit data such as online behaviors, digital footprints, sentiment analysis and social graph show how interested the customer is in the company.
With a centralized and complete 360˚ customer view your staff can understand, engage and more effectively communicate with each customer.
And they can finally achieve the elusive goal of delivering rewarding customer experiences that impress and delight customers.
Customer Intelligence
Now it's time to get better visibility into the revenue cycle with customer intelligence. This starts by transforming buyer data into customer insights.
These insights advise things like which marketing offers will convert, which leads will buy, and which customers will churn. They show which selling actions will advance an opportunity and how salespeople can better apply their time to produce better results.
Customer intelligence directly aids 3 important goals:
- First is the ability to help staff deliver relevant, personalized and contextual communications. This will improve customer relationships.
- Second is the ability to deliver precision marketing campaigns that increase conversions. Data can be used to show the combinations of content, offers, messaging and channels that drive the highest conversions for each customer or customer segment.
- And third is the ability to apply data to increase sales conversions. Customer insights can reveal when, why and how customers make purchase decisions. And they can provide guidance to know what's most important to the buyer at each step in the sales cycle.
But to achieve these goals, you have to organize your customer data. And that's done in the CRM system.
The data becomes part of the 360-degree customer view. It is parsed into customer segments and customer insights. Most CRM systems measure the customer's fit to the company's Ideal Customer Profile (ICP).
Now the data will support many customer use cases and pay dividends to many downstream marketing and sales processes.
Research performed for the Sales Excellence Report found another interesting benefit. Companies in the most competitive industries had a disproportionately higher use and benefit from customer knowledge and commercial insights.
In the absence of product distinction, leveraging a customer distinction is a proven method to increase separation from competitors. It's also a substitute to the alternative of reverting to price for differentiation.
Buyers also want insights. In the book titled, Insight Selling, veteran researchers Mike Schultz and John Doerr found that among 42 factors, the most significant difference among sales winners and second place finishers was their ability to deliver buyer insights and educate buyers.
The research found sales winners led with ideas, insights and perspectives almost three times more often than second place finishers.
Buyers were clear that they minimized, and often completely discarded, seller talk about company and product superiority. Their top request was sellers that could provide insights that advance their knowledge and their purchase journey.
Industry Benchmarks
Business is a competition. If you are not outperforming your competitors, you are losing market share. Comparing revenues or profits to competitors may show you if you are winning or losing but it won't tell you why.
But revenue benchmarks will. They compare key performance measures to peers and competitors. They surface the gaps or underperforming areas that offer the biggest financial uplift. They provide a relative comparison to show where the company most needs to improve. They also enable predictive analytics.
Performance measures are often interesting but not actionable. Staff view them but don't learn from them. Industry benchmarks can elevate information from being merely interesting to delivering insights that induce learning and action.
For example, a sales management dashboard shows a rep with a 45% sale opportunity win rate. That may be interesting, but it is not insightful or actionable. Instead, display this information alongside an industry benchmark that shows the average win rate is 49%. The sales manager now knows the salesperson is well below par.
A dashboard with this benchmark may also include a predictive analytic that shows the top line revenue impact if the win rate is elevated to the industry average. It can also show actions for improvement. The dashboard may show this salesperson performs an average of 7 activities per sale opportunity.
But the larger data set shows that across all sellers, sale opportunities that are won incur an average of 15 activities. Now you have an insight and can act. You can facilitate action by creating links from the metric to Playbook Plays, such as a Play that shows methods to increase customer engagement.
Performance Dashboards
The thing about strategic plans is that they seldom go according to plan. That's why dashboards are needed to display real-time performance measures and variances in need of quick remediation.
Most dashboards display historical data. Better dashboards shift from lagging to leading indicators. And the best dashboards enable metrics to be interactive, so managers can perform What-If modeling and scenario planning.
They also display KPIs in a sequential and easy to consume visual interface. It helps to group related metrics so they can be more easily navigated from high-level measures to supporting details.
For example, the below RevOps dashboard displays the most important revenue metrics at the top. It then displays supporting marketing, sales and customer service measures below.
One more thing.
Sir Francis Bacon is generally credited for the phrase, "knowledge is power". We suggest that knowledge is not power unless it is acted upon. Power is created from action, not visibility.
Simply creating a list of KPIs to display in a view falls short of inducing action. However, when KPIs are aligned with objectives, compared to benchmarks, and linked to actions, information goes from being interesting to creating value.
The performance metric is not the goal. It's a recommendation for action. Action is the goal.
An interesting thing about effective dashboards is that staff spend less time accessing information and more time applying insights to adjust their actions. That's the sign of successful dashboard reporting. If the information is causing operational changes to be made, it's working.
Predictive Analytics
For most companies, revenue reporting is periodic and historical.
However, executives want to use information to engineer future financial outcomes. That's why predictive analytics are needed.
Predictive analytics use AI and machine learning to forecast outcomes and recommend actions to achieve them. The actions are normally accompanied with confidence levels that show the likelihood of success.
Company growth is a process, not an event. So, to visualize that process our predictive analytics consultants use a proprietary model we call the Predictive Pyramid.
It's a bottom-to-top revenue roll-up and interactive dashboard. It shows how lower-level measures drive higher level analytics to achieve the company's financial results.
The data that drives the calculations is sourced from company transaction history if it's available or industry benchmarks if it's not.
The pyramid is needed because no revenue process, program or tactic lives in isolation. Each has cascading effects that impact other areas. Those impacts must be considered when making tradeoffs. This visualization is extremely helpful in determining where to invest your limited time to achieve the biggest uplift.
For predictive analytics, data is the fuel, machine learning is the engine, and actionable insights are the destination.
Data Driven Operating Model
Collecting, processing and delivering data-driven insights only creates value if those insights are used by staff to improve a customer experience, solve a problem, achieve a business outcome, or make an informed decision.
That's why a data driven operating model (DDOM) is needed to deliver the last mile of revenue cycle analytics.
A DDOM operationalizes data to guide decision making. It applies insights to deliver greater customer value, improve staff productivity, build better products, or earn more revenue and profits.
Most of all, a DDOM insists that all decision making is based on data, facts and insights.
But making this transition requires two things.
The first is data literacy. You may need to upskill part of your workforce. Online learning and development programs are good tools to train staff to interpret and apply data in their daily roles.
The second is data-centric culture. Executives and managers must lead by example and insist that staff decisions be based on data.
They must promote a culture that shifts decision making from intuitive, gut-based and subjective choices to data-driven, fact-based and objective decisions.
"In God we trust, all others must provide data."
— William Edwards Deming, economist, executive, management consultant, and author
The DDOM is the final step to make the company's data the company's most valuable asset.
Companies that successfully implement this model consistently have more staff making better decisions.
That's strategic because improved decision making is one of only four sustainable competitive advantages.
The More You Know the Faster You Grow
The most successful companies are defined by their ability to apply revenue cycle analytics for sustained growth. These companies collect and curate the right data, use data to create differentiating products, services and customer experiences, and apply analytics to make insights actionable at every customer engagement and decision point.
It's a complex undertaking for sure, which is why those who succeed achieve competitive advantage over those who don't.
"Knowledge has become the key economic resource and the dominant – and perhaps even the only – source of competitive advantage." — Peter Drucker
Most companies have the data to produce revenue cycle analytics.
However, they may be unfamiliar with how to harvest and transform that raw data into actionable insights. They are data rich but information poor.
Fortunately, there are partners that can help. Johnny Grow is one of those partners.
Our business analytics consultants are experts in helping clients turn data into their most valuable asset.
They can quickly show how to connect data to insights to actions to outcomes.