Improving Time to Revenue
The True Pulse of an Organization
Let’s place a wager. My bet — you do not have an accurate measurement in place that tells you the time it takes your prospect to become a customer, from first touch (whether it be website interaction, email, event, or digital) to last touch. Would I be right? Perhaps I am overstepping my boundaries a little. Maybe you do measure it, but do you trust it? Are you able to produce action from the results?
After thousands of conversations with prospects and fellow revenue leaders, I have yet to meet someone who could tell me, with confidence, that they had this covered. Yet, I would argue that this is and should be the most important metric that any B2B business tracks and learns from.
I am not talking about measuring time to revenue from qualified to close. That is easy, and frankly, many BI platforms are tracking this for mid-market and enterprise B2B companies. Instead, understanding where that demand comes from is pivotal to growth and spend.
It is about time for revenue leaders to have this answer. The fact of the matter is, if CEOs across the globe want a metric on their desk that actually positions them for success, this is the one.
Time to Revenue Matters
Alright, so why should you care? I have 5 very specific reasons why you should make ‘Time to Revenue’ your number one focus, starting today:
Forecasting with confidence: This may be the number one cause for team attrition and cultural misappropriation. Let’s face it, winning new business is a cure for a lot of things. But at the same time, not winning new business or failing to hit your goals kills culture and morale. Forecasting with confidence and adjusting with confidence is vital, and it only happens by understanding your time to revenue metric.
Budgeting with confidence: Knowing your average time to revenue from jump street is critical to budget success. Budget success is critical for every SMB and Mid-Market B2B business. This allows you to know if your targets are achievable and if budget is allocated appropriately to do so.
Experimenting with confidence: If you can’t benchmark against time to revenue metrics, and the data behind the data, then you can’t experiment effectively. Do you know if you should be picking up the phone more? Or, sending a specific type of content? Or, sending more segmented emails? This metric is the foundation for that benchmark.
Retaining with confidence: Improving time to revenue allows you to get granular with the customer data. It allows you to understand who closes the fastest, which in turn, helps you better target your ideal customer. It allows you to also give them a more valuable customer experience in order to retain them long term. The time to revenue component is not only good for your topline, it is also good for the customers’ experience. Get them through the funnel faster and give them faster time to value. They came to you with a challenge, get them to the solution.
Booking with confidence: Book the right customers every single time. If you know which customers move through the pipe faster and close more regularly, then you can target the right buyers more often. Sales can stop wasting time on prospects that stall. They can go after the deals that make them more money and the business more sticky.
The Challenge of Tracking and Measuring
Historically, the challenges associated with measuring, analyzing, and tracking this information have been the biggest roadblocks in making this metric the most important KPI within your business. If there was ever a golden metric, this was it. But, just like gold, it is often difficult to find, and even more difficult to mine.
If you bothered to track this at all in the past, you likely pulled together five different excel spreadsheets, created multiple pivot tables, and went down the Youtube rabbit hole to help learn how to understand the data. And, you probably did this every single week. If you are like most people, you spent 5-10 hours a week doing this mind-numbing exercise to generate a result that ultimately could not truly be trusted. But, it’s not your fault. Let’s face it, you did not get a degree in data science to run a marketing team.
The B2B buying process is complex. When a prospect engages your business, they likely have 10+ different activity types or programs that they could engage with. There is a myriad of stakeholders involved. Deals can take 6+ months to close. And, marketing attribution has been sold to marketers as the metric that they should have their pulse on at every step. The problem is — attribution is busted and overly complex. Check out our blog on attribution vs. impact. Obviously, marketing is oftentimes the demand starting point, but Customer Success has such an impact on this as well, especially when it comes to revenue value creation. As I said, the attribution model is busted!
With all of this complexity, you may feel like throwing up your hands and quitting. I am here to tell you that you now have a solution. It is possible. Don’t quit. Become the hero.
The Solution, Through the Customer Lens
Let me tell you a story about one of Vertify’s B2B customers, who is partnering with Vertify to collect, connect, and make sense of their data to ultimately optimize and track their time to revenue. They were living with all of the challenges we’ve discussed daily, and decided to work with us to do something about it.
This customer has a robust tech-stack to automate campaign execution that includes Marketo, NetSuite CRM, and event management applications Eventbrite and Zoom. However, with key data residing in different systems and gaps in functionality, unlocking time to revenue insights was a real challenge. Without viable information to prove marketing activities were actually leading to sales, the team was at risk of losing up to 30% of their budget. With the complexities mentioned above and an overly intricate attribution model, they were struggling to measure the time to revenue metric.
“We could see in one platform that we had good event attendance rates, click-through rates, and conversion rates, but we couldn’t easily tell if those same ‘engaged’ prospects were becoming customers or just enjoying the free stuff,” said Jessica.
The required data was being captured in different systems, but piecing together the complete customer journey proved to be tedious and unreliable. “I was pulling campaign data out of Marketo, which is associated with a contact record, and trying to pair it to sales order data from NetSuite, which is associated with a company record,” Jessica explained. “There wasn’t a unique field to easily identify the connection. The contact that initially fills out the form is hardly ever the same contact that gets listed on the sales order.” Once all the data was extracted, Jessica was using a separate application to link everything together.
With Vertify’s foundational integration in place, the first step in the customer data journey, Vertify could now help them get to the bottom of the campaign to revenue blackhole.
“Vertify, they’ve made me a hero,” said Jessica. “I am now able to easily demonstrate exactly how our marketing efforts are leading to actual revenue.”
The Vertify process and toolbox have allowed Jessica and countless others to look at their activities in a new light. By sitting at the intersection of data collection and analysis, Vertify equips our customers to automate the things that require you to have a PhD. We give you very specific metrics that allow you to go more granular into your first touch, second touch, and even last touch. So, not only can you now measure your time to revenue without spending 10 hours a week in excel spreadsheets, but you can optimize your time to revenue with next action insights.
It all starts with the right step in the Customer Data Journey.
Obviously, Vertify can help you become the marketing hero you have always wanted to be by tracking and improving your time to revenue. But, where do you start? Start with data connection and collection, and ultimately, analyses. Then, and only then, can you understand the impact you are having on revenue. Only then can analytics really be actionable.