Time to Revenue: The One KPI You Should Strive to Really Know
It’s an eternal discussion. What KPI should your B2B focus on? There’s very likely as many opinions as people you ask.
Just as likely, you just might be ridiculed if you were to claim that there’s actually one thing that should be the North Star KPI for most B2B growth people.
In this post, we are taking the chance. We will claim just that.
Here’s What You Will Get In This Post About Time to Revenue:
Learn to define B2B Time to Revenue
Why Time to Revenue is Critical for a B2B
Understand the complexity of tracking B2B growth
See a real Time to Revenue graph
The technical foundation for extracting Time to Revenue
The one KPI that everybody involved in B2B growth should aim to know is:
Time to Revenue
How long does it take from the first time somebody from a potential account visits your website until the account is closed as won?
We have not come across a single company who can answer this question crisp and instantly.
This goes even for tremendously smart people, with a flair for B2B growth. They don’t know.
Yes, they will know from whenever the lead entered the sales pipeline. That’s easy.
No, they don’t know from where the original demand of the account started.
Time to Revenue - Why you should care
There’s a ton of reasons why you should care about truly knowing the Time to Revenue for all your accounts.
Here’s some of the ones we find the most important:
Growth activities:
In today's B2B marketing world too many ideas are killed. Their effect will impact long term, but they are judged on a month to month basis.
In the example below you will see that the company’s journey is an average +200 days.
It’s simply beyond Googles and Facebooks tracking abilities to understand B2B value. Hence if that’s all the tracking you do, you can’t know whether your growth activities are working or not.
Paying the bills:
In B2B you can’t make revenue out of nowhere. It takes time. It takes planning. It takes execution.
If you’re in a situation where sure you have to pay salary, rent and other essential bills you need to understand when the money you’re spending now, comes back in terms of revenue.
Predicting revenue and budgets:
The amount of startups that have died from not hitting their budgets are abundant.
When you know your average Time to Revenue you will from the get-go know whether the numbers you’ve set forth to hit are actually possible to hit.
If your average sales cycle is +365 days, then at the end of year 1, it’s already too late to hit year 2’s budget, if the leads are not already in the pipeline, right?
Experimentation:
Knowing the average account journey gives a benchmark for trying to accelerate the journey.
No starting point, no improvement.
Should you send more emails? Change the content of your automation? Run more ads? Pick up the phone twice as many times?
Conversion types:
What conversion types are the best conversion types for your business?
Which ones convert faster?
Which ones are the most valuable?
Which one should try to optimize for going forward?
If you don’t know your Time to Revenue, you can’t provide a qualified replied to these questions.
Improve sales:
Large accounts take a long time to won. But how long exactly? Are they worth chasing?
Account managers might have rules about moving leads to closed lost after +100 days. But what if the average Time to Revenue for a large deal is 131 days as the example we will show below. Then you better keep trying to close the deal!
Knowing Time to Revenue will give you a better understanding of what moves the needle in your B2B. Everything revolves around it. Really.
Don’t judge activities monthly, if results are to be seen yearly. Things take time in B2B.
If you can connect the dots between first demand-generating touches and much later revenue, you have a significant edge on your competitors.
The B2B tracking problem
The bad news is that Time to Revenue data takes work to produce and understand.
The good news is that this post will tell you how to get there. It’s simple, but hard.
Tracking B2C e-commerce is one thing. A customer clicks an ad and visits a website from a phone and perhaps comes back to buy from a computer. Admittedly there’s some complexity to it. If you only track cookie-based through Google Analytics, that data does not tell you the truth about what’s going on.
However, if you use Facebook Ads and Facebook Attribution you are less in trouble. They mostly have this “simple” B2C e-commerce tracking covered by now as they can do people-based tracking. Most people are signed into Facebook on all the devices they use.
The nature of B2B transactions is a challenge. Tracking what happens when one company is moving towards buying a product or a service from another company is complex.
Some of the things that add to the B2B complexity are:
Revenue:
Most B2Bs do not have a cash register. There’s no way to complete a transaction on their websites.
This means there’s no revenue component to send back to the ad platforms and spend money on ad campaigns that drive revenue.
Time:
B2B deals easily takes 6, 12 or more months. From early research until the budget is available and terms are agreed will take a while. This makes it hard to connect the dots.
Some activities start the customer journeys and others close the deals.
Stakeholders:
Demand does not start when a transaction is completed.
In most B2B transactions multiple stakeholders will be involved.
We feel that everyday at Dreamdata. For us to close a deal we often need to work with a bunch of people. A marketing specialist wants to know if the ads work. A VP wants to know which channels drive growth. The CEO and CFO wants to allocate budget to the utmost effectiveness. All of them need to say yes, before we can send our order form.
Sounds familiar for your business?
Team:
Traditionally attribution is de facto understood as marketing attribution. What are the activities that marketing do worth?
It’s a siloed way of thinking that does not reflect what moves the needle in B2B.
Yes, marketing initiates a lot of journeys, but customer success needs to reply to a ton Q&As and the sales people need to wiggle and wrestle their way to deals.
Knowing this, does it make sense to only appreciate marketing effort when judging B2B growth? No, obviously not.
In all this complexity understanding Time to Revenue per deal might seem like a stretch.
Perhaps you even feel like giving up on B2B tracking already? Don’t.
It is possible to improve it significantly. We will tell you how.
Inspecting a Time to Revenue graph
Below you will find a Time to Revenue-graph.
It’s from a B2B company who’s using Dreamdata to understand their Time to Revenue data.
What’s Time to Revenue measures:
Time from 1st visit (Ads, organic, direct etc.) from individual until the deal is closed as won.
The graph sparks a couple of comments:
They’ve collected data for 1,5 year, but it seems that they still have not fully seen what an average customer journey is for them. Time to Revenue from first touch (ad click, organic visit etc.) to deal closing keeps rising.
Time to Revenue is an evolving KPI.
When new data points are collected, the model is adjusted. It’s alive, so to speak.
If a touchpoint is discovered, that lay before what original was the first touch, the algorithm corrects the history. Per the graph above, it keeps trending upwards.
What the person hungry for growth will/should now be thinking is:
“Ok. Now, we’ve sorted all the journeys. We know where they started. We know when they closed. Can we look at where the fastest journeys come from? I want to do more of those”.
Yes, you can. Here’s the data related to the above customers journey:
And so you can keep asking relevant questions:
“Okay, some channels are faster than others. But what are the average deal values of each channel? Perhaps I’m okay with it being slower, if the average value is higher.”
“Say, if the organic channel has a higher average deal size, which exact URLs are starting these journeys. Let’s produce more of this type of content.”
“Or, do certain ad campaigns have particular fast turnaround time? I want to do more of those.”
“And what about the account size, does that affect the Time to Revenue as well?”
For the two accounts exemplified below, it definitely does.
Get the right tracking, data collection and data models in place. Then you can answer these kinds of B2B attribution and revenue analytics questions.
Want to know how to do this? Keep reading. The technical recipe is coming up.
The technical foundation
Getting to the Time to Revenue KPI comes down to one thing; Data.
Making relevant data available and starting to store it. Then you can analyse it, when you have the time and desire to do so.
But for this question, what is relevant data then?
The rule of thumb in your company should be to try and make sure that everybody’s work generates digital reflections.
If your sales and support people currently pick up a random phone and call customers, stop that. Start using calling software that generates a digital touchpoint every time the phone is picked up.
If your support tickets are handled in gmail, switch to a support system that’s able to structure and categories the conversations.
If you only run offline ads, start spending money on digital ads already :)
In a perfect world the answer to what data you need is: Every single touch point that affected the deal. Unfortunately, that’s never going to happen.
What you can do is to collect and store your 1st party data to make your own analysis of what’s going on in your B2B:
Database:
The first step you need to take is to establish a database. Your own database.
This is to be the container to where you pipe all the data you are generating in all the digital tools you use.
Marketing:
Ads: Most B2B rely on Facebook, Google and Linkedin, to store their ad data forever. They don’t. Within some months they will start deleting this critical information about what generates your B2B demand.
Organic search: Google's Search Console can be a pot of gold if you’re able to inspect the data. Make sure to pipe this data into your database as well.
Events, meetups and webinars: A lot of B2B deals are still triggered from physical meetings. It can be hard to exactly estimate the value of these physical interactions, but it’s definitely possible to do attribution to them. You just need to be disciplined about the data collection. If nothing else, write these things down in a sheet for later usage.
Where did you meet the lead? Who did you meet? Which company do they represent? When did you meet them?
Automations: If you have automated emails through a tool, make sure all the data generated by the tool is stored in the database as well.
Customer Success:
In B2B these are the frontline employees that deal with all the day to day questions coming from the leads lurking around your business. You would want to know?
Which leads are asking questions? What articles are they reading? Are they expressing a desire to purchase?
By using a customer success platform like Intercom or Zendesk you will be able to take this information out of the tool. This means you can start to attribute revenue to your customer success team and not just proxies like a better Net Promoter Score.
Sales:
Account executives, Key Account Managers and the likes can sometimes be regarded as magicians and vital deal makers.
It’s true some of them are great talkers and convincers. However for most sales people activities like calls, mails, texting are what makes the difference between a good sales person and mediocre.
By implementing ie. calling software or outreach tools, you are able to measure the activities of sales people and attribute revenue to their actions.
CRM:
A disciplined use of a CRM system is critical to running a successful B2B.
It ensures that employees don’t make a mess of the interaction with your customers.
It will help you get some predictability into your revenue planning.
Most importantly it will help you sort individuals according to what company they belong to, which is critical when trying to do B2B attribution.
User data:
For ages Google Analytics has been the most widely used website tracking tool. For a while it remained the best option for tracking what takes place on your website.
But times have changed. For one thing, today's complexity with multiple devices per user is something Google Analytics still hasn't managed to grasp well.
More importantly, it is not easy to take all the ID’s (known as unknown users) and their behavior out of Google Analytics. That’s a critical flaw.
Being able to store user data is an absolute critical component for glueing ie. ad buying together with newsletter signups, that at a later point end up becoming accounts that are closed as won in your CRM.
Our suggestion would be that you start to track users through Segment.com.
Sorting individuals to B2B accounts to understand Time to Revenue
With all the data collected and cleaned the next step is to sort it by accounts/companies.
If you are a B2B and are tracking the actions of individuals, you’re probably doing it wrong.
In B2B buying processes the torch switches multiple times.
When you sell B2B, you should think of attribution as following a company’s journey towards purchase.
This means, when did we see this company the first time? From the first individual to all the stakeholders involved in the buying process.
What are all the (digital measurable) actions that the company has taken on the road to becoming your customer?
A solution to do this sorting can look like this:
Everyone who comes to your website is given an anonymous ID.
This is set both in the browser and local storage to make sure it’s not lost.
We use Segment.com to do this.
The anonymous journey is stored in a database, awaiting a later association to a company.
When the anonymous ID at some point identifies themself, the user is associated to a company.
The ID event could be upon;
signing up to a newsletter,
purchasing a product
or perhaps logging into a service, both as the first from a company or by invite from a colleague post-purchase.
In some cases IP lookup through services like leadfeeder, ocean.io, clearbit etc. can make sense.
As the users are associated to companies, we start to join the individual journeys, to one joined company journey, to tell a story about key events:
When did we see the company appear anonymous on our website the first time?
When did the company identify initially?
When did they start paying for the first time?
What have lifetime revenue have made from this company?
When did the company end up churning?
Doing all this will enable you to connect the full B2B customer journey, including being able to understand Time to Revenue from the very first visit to your website to when the average deal is closed as won.
Concluding remarks
Time to Revenue is a critical KPI for B2Bs. Demand and Sales do not happen over night.
You need to plan ahead. You need to do stellar execution through out the company.
Marketing should start the journeys. Customer success should give qualified answers to product questions. And Sales should put in the work to iron the last details.
All of it takes time.
If you don’t know your Time to Revenue you don’t know what success looks like.
Are you in good shape or bad? Perhaps your already off this years budget? Perhaps you in front of it?
Knowing your Time to Revenue would provide you with the answer to the question.