How Does Revenue Analytics Help Marketing Managers Make Better Decisions?
Exactly how does revenue analytics help managers make better decisions? The answer to this question should be clearcut and obvious. However, there seems to be a gap between what revenue leaders want from their analytics versus what they actually get.
There’s a growing conversation on the gaps that constantly emerge when revenue leaders search across various analytics tools for answers. Data analysis is supposed to deliver performance-, growth-, and revenue-generating insights. Yet, regardless of the analysis solution being used, performance-inhibiting visibility gaps keep emerging.
It’s worth taking a second look at common approaches to revenue analytics, along with ways to close any gaps and get a full view of critical activities.
How Does Revenue Analytics Help Marketing Managers Make Better Decisions?
Let’s revisit what revenue analytics should deliver. Marketing analytics aims to identify and understand the activities responsible for revenue generation.
Revenue analytics should cover all your customer-related activities, including marketing, sales, customer service, and can even include fulfillment operations. It essentially tracks a customer’s responses and behaviors to various marketing, sales, and customer service interaction points. This should provide clear information on how each activity influenced the customers’ spending decisions as they traveled across the buyer’s journey.
So, how does revenue analytics help marketing managers make better decisions? It does so by laying out precisely which activities generated revenue and where.
You can objectively analyze every decision, strategy, and tactic in the context of revenue, profit, and ROI. You can see a marketing or sales activity’s revenue impact, understand where the opportunities lie, and clearly evaluate pipeline health.
You then gain the ability to precisely engineer the results you want, defend your budget based on hardcore evidence, and demonstrate why certain steps should be taken.
MarketingProfs listed seven top benefits of implementing revenue-based analytics:
1. The ability to make better decisions
2. Marketing and sales alignment
3. Increasing campaign effectiveness
4. Increased channel effectiveness
5. Increased marketing budget
6. Attributing ROI to marketing
7. Winning executive buy-in and support
Want to convert more customers with a higher lifetime value? Run a revenue-generating campaign? Bring in a little more profit? Focus on the channels with the highest marketing ROI? Defend your budget to an executive? Predict where profitable opportunities will emerge?
Practicing revenue analytics and integrating it into your strategic decision-making will do that for you.
Related: What Is Revenue Analytics and Why Every Business Needs It
Assessing the Value of Your Work
Revenue analytics sounds like any marketer’s, sales leader’s, entrepreneur’s, or C-suiter’s dream. So, why hasn’t it been adopted across the board as part of standard operating procedures?
It comes down to capabilities. Tracking a single customer across solutions while assessing their behavior and mindset has been challenging due to a lack of comprehensive, affordable technological solutions geared specifically to this issue.
Revenue leaders have relied on a mix of low-tech and high-tech solutions in order to measure the work they’ve done, then condense that into actionable steps. These have included attribution and impact analysis, buyer’s journey mapping, map-based analytics, and sales battle cards.
Attribution Reports and Impact Analysis
Attribution reports and impact analysis studies are two methods for assessing revenue generation.
Marketing attribution reports show how successful marketing was at accomplishing conversion goals. Revenue attribution reports tie revenue to advertising spend. Neither evaluates what it takes to bring a customer from the top of your funnel to the end while maximizing revenue and speeding up conversions.
Marketing impact evaluates your entire program and looks at the customer’s experience throughout their lifecycle. However, these assessments aren’t geared towards pinpointed revenue attribution. The focus is on traditional marketing goals and KPIs, like customer awareness, social media engagement, lead generation, email conversions, etc.
Buyer’s Journey Mapping
You have the option of mapping out the buyer’s journey, either on paper or through an online tool.
If you choose paper, this process involves laying out the steps and then adding in your marketing activities along with the customer’s behavior choices. However, it’s complicated, labor-intensive, relies on guesswork, doesn’t show granular attribution, and can’t provide real-time information.
Only with an online tool you can have the full picture. The solution will let you comprehensively understand how each potential decision or interaction can either facilitate or impede eventual revenue generation. It also gives a visual look at customer behavior patterns, plus real-time insights, and more.
Map-Based Analytics
Map-based analytics is critical for geographically organized sales teams. And it can be helpful for refining localized or regional marketing messages.
Salesforce is one solution that offers location intelligence. Salesforce starts off with vital marketing information like the estimated lead value, account information, and user data. It then adds its own insights on how effective your campaign work was, along with what needs to be optimized for which area.
That’s great on its own, but how do you bring that information back to marketing for improvement and rework?
Sales Battle cards
Sales battle cards are concise one-page documents drawn up from sales-related competitive intelligence. These are used to win prospects over during sales conversations and meetings.
A sales battle card usually compares and contrasts your organization’s offer versus the competitor, outlining more favorable areas.
Sales battle cards are intended to be a deal-closing resource. It might seem easy to attribute revenue to battle cards based on which ones were used in won deals.
However, this approach doesn’t actually determine what the battle card was responsible for. You should be able to tell if the marketing collateral used to close a deal:
- coasted by on earlier efforts,
- addressed a buying group’s final concerns,
- or won over a prospect on the verge of backing out.
This is what separates revenue analytics from revenue attribution. The revenue analytics approach evaluates the entire buyer’s journey process and accounts for each activity’s impact on the others. Attribution alone doesn’t consider these dynamics.
You can then loop these insights back to improve upstream marketing efforts.
Creating Cohesive Revenue Analytics
How do you measure, assess, and communicate the value of your work? The method you choose determines your insights’ quality, accuracy, and depth.
It’s possible to do some DIY revenue analytics by cobbling together low-tech resources, methods, and tools. But this inevitably leads to gaps, incomplete insight, and a shallow understanding of customer motivations and behavior.
Traditional marketing agencies and sales tools aren’t oriented around revenue generation. Getting a complete view here takes an entirely new solution.
Related: Benefits of a Revenue Operations Platform
Facilitating End-to-End Revenue Analytics
How do you close any gaps, get a full-funnel view of the customer, and generate information you can rely on? And how can you follow the customer’s behavior when certain tracking methods – like cookies – are being phased out and privacy rules are getting stronger?
That can be done by leveraging the data generated by the apps, tools, and platforms within your tech stack.
Every organization relies on various solutions to interact with customers as they travel along the buyer’s journey. This data will tell you exactly how they behave and respond to your sales and marketing.
Once you unify the data generated from marketing to sales, you can get full end-to-end revenue analytics without any guessing games and zero blind spots.
Better Decision Making with Revenue Analytics
Let’s take a final look at the opening question: how does revenue analytics help marketing managers make better decisions? Take a look at the following four capabilities and consider how much sharper your decision-making will be with this level of insight.
Current Revenue Reporting – On-Demand
Revenue analysis happens in real-time, giving you the most up-to-date interpretation of your data flow.
This means you can switch to working off the latest intelligence and create marketing based on seconds-old data, not weeks or months.
Broad to Granular Revenue Impact Reports
Evaluate your marketing and sales work on a broad or granular scale. Drill down to analyze revenue generation by the campaign, product, and activity type.
View Pipeline Health
How are you evaluating the health of your sales pipelines? Many sales leaders check into the number of deals, average deal size, closing ratio, sales velocity, and the prospect to the customer lifecycle.
Revenue analytics gives precise data on pipeline health metrics. However, it goes further by delivering recommendations on which tactical levers to pull to improve your results.
Access Predictive Intelligence
Revenue analytics should always include a predictive element. Putting AI to work on your organization’s data is invaluable. Want to spot profitable opportunities, analyze your funnel, access marketing recommendations, or learn how to speed up the time to revenue?
Once the program understands your offer, customers, and marketing, it will generate personalized, predictive recommendations.
Revenue Analytics Made Simple
Struggling to see the revenue impact of all your marketing and sales activities? Try Vertify’s RevOptics. This application data integrator analyzes customers as they move across the buyer’s journey.
It provides automated analytics with real-time insight and prescriptive recommendations. Ready to make revenue analytics simple, close any visibility gaps, and accelerate your time to revenue? Request a RevOptics demonstration today.
