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19 min read

3 ways revenue analytics can drive exponential growth

Revenue marketing

Kun Li gave this presentation at SEC's Chief Revenue Officer Summit in London in December 2022.


Today I’m going to share my experience of using revenue analytics. I have a fairly technical background; I did programming and modeling about 5-10 years ago.

But I'm also interested in applying revenue analytics to drive business growth, particularly in the revenue field or revenue management.

When we talk about revenue analytics, you might be wondering if I’m going to go through all the machine learning models, regression neural networks, and the random forest.

No, that's not what we're talking about in this article. Those topics are for data scientists!

First, I’ll talk about revenue analytics. Revenue operations is a relatively new term, so I wanted to add a little bit more complexity to the analytics in this particular context.

Next, we’ll look at a couple of key focus areas for revenue analytics because this area is just so broad.

And lastly, I’ll share my personal opinion on where and how we get started.

Here are some quick links:

Let’s dive in. 👇

Many different charts and models to show KPIs to track (sales cycle time, win rate, forecast accuracy, CLV, CAC, ARR, ROI, and attrition) and then machine learning models like random forest simplified.

The key focus areas of revenue analytics

If you do a Google search on revenue analytics today, you’ll find thousands of results, and you'll still be left wondering what it is.

And if you look at the definition - well, there are so many different definitions in different contexts, and people will be using them for various purposes.

A very common definition is revenue operations. In fact, a lot of companies actually have revenue analytics as part of their revenue operations.

And speaking of revenue operations - if you add up sales ops, marketing ops, and customer success ops, you’ll find yourself starting to wonder: “Is revenue analytics just sales analytics, plus marketing analytics, plus customer success analytics?”.

You might look at it this way, but what I’ll be talking about in this article is a slightly revised or expanded version of this for two key reasons.

Number one is the scope.

When we talk about revenue operations, you've got sales, marketing, and customer success.

Then, if you expand a little bit and think about the entire ecosystem, particularly for startups, that probably doesn’t cover all the differentiations.

You likely have product, and finance in there, and if you're not looking at those two elements, you could be missing a great opportunity.

For example, with the finance element, some folks are providing expense solution management, or maybe even credit cards.

When providing those or selling a product on credit terms, you need to be taking into consideration whether your customer is going to pay you, if they’ll be paying on time, or if they’ve ended up getting into debt.

And when you start thinking about acquiring customers, if you're not paying attention to those, you could turn things completely upside down in certain channels. So it's really important to get that in.

The product largely comes into play with regard to the pricing.

The product proposition and pricing go hand in hand with sales because we want to do promotions, get the pricing right, and decide where to position ourselves compared to our competitors.

To me, this whole thing is an ecosystem, and you can't just go without considering the other elements, especially when you're trying to use analytics to drive the decisions to know more about your business.

Number two is the intersection of these sales or marketing analytics, or customer, product, or finance analytics.

It’s crucial to not just simply add everything up because sometimes one plus one is way greater than two.

The key thing here is how you're utilizing the data from different sources to actually leverage it, i.e. if I'm doing marketing analytics, I’m looking at my sales data, my finance data, and lots of other data I’m acquiring as well.

So that's what I wanted to point out in terms of context, but now you’re probably thinking: “Wow, that’s basically everyone that’s involved in running the entire company, any type of analytics could be falling into this category.”

In my view, the top three things for us as leaders to focus on are investment decisions, optimization, and pricing.

Investment in particular is so important.

Revenue analytics and revenue operations - product is pricing, sales ops, marketing ops and customer success ops are optimisation and then finance is investment - but all of it is under analytics.

Making the best investment decisions consistently

How many of you in the last six months have faced a scenario in which you’ve received extra money and you’ve needed to figure out where to spend it?

This is definitely a scenario you want to happen.

But more often than not, people are facing scenarios where they don't have enough resources or enough money, and they need to decide what they’re going to do about this.

Particularly when it comes to strategic decisions - you might decide that you’re going to shut down one sales channel, shut down one of your products, or actually just focus on one product.

How we're making those decisions is key.

The question here is not if we can make the decisions, it’s how we'll make the decisions.

We could just flip a coin to help us choose between A or B. I'm sure your decision processes are way more complicated than that, but the question here is, how do we consistently make the right or the best decision?

It's not just a one-time, ad hoc exercise, this will have a huge impact.

The other aspect of those decisions is around BAU, running our teams, and monitoring what our teams are doing because it could have a massive impact in the long run.

Even with your existing money, when you get into next year you can start thinking about how you can optimize your spending.

Focus area: Investment decisions - strategic: channel, product, and people vs non people. BAU running: Digital lead gen, marketing events, etc. Question: How to make best decisions consistently?

Investing in digital lead gen

We live in a digital world, and I'm sure many of you actually have a digital acquisition channel in place.

But the question is, how exactly are we making the decisions throughout the process?

Because my organization FLEETCOR has acquired a lot of companies and I’ve worked on a lot of projects, what I’ve seen is that there are various different models feeding into different contexts and purposes.

But if our teams are making decisions purely based on the information through marketing, or our marketing teams are making all the decisions, they're incentivized by how many leads they’ve brought in.

Or if you're using an agency to help you drive digital acquisition, they're incentivized by the number of quality leads coming in.

Great, that's one way.

But you might be missing a great opportunity because if you go further down, look at the sales, and combine the sales, are you actually converting them?

Is there a channel that's actually converting them more effectively such as PPC, organic, Facebook, or LinkedIn?

And do we actually want those?

Some people will stop there.

But if you go further down again, maybe some of the customers you acquired through a specific channel will stay there for six months to a year, and the rest of the customers acquired through other channels will stay there for five years.

You’ll make a massive impact when you look at this end-to-end, and if you further expand that to finance and look at long-term revenue and how you acquired that.

If it’s on a comparison website, you may end up attracting customers who renew every year and are trying to look for new solutions.

So, I think the key question here is: How exactly do we do this consistently and have the message across the team?

When we make the decisions, marketing, sales, operations account management, and finance should all come in together.

And in the long run, when you're spending the money, you should really be looking towards the very end, to the profit that you're getting.

Many companies are doing this already, but things change massively and very quickly.

What you had three months ago could be changing right now, and the key to success here is actually having a dynamic solution in place to keep things refreshed on a regular basis.

Investment: digital lead gen. Impressions, clicks, leads opportunities, offers, contracts, revenue, LTV, and profit. The first three fall under marketing, the next two under sales, the next two under operations account management, and the rest for finance.

The importance of optimizing your sales pitches

The second focus area that I would suggest is optimization.

I think that's part of the revenue operations job already. And if you look at the sales ops and marketing ops, we’ve got dedicated people to actually do that.

The thing to think about here is how we can use analytics to help drive better optimization in this process.

If we're looking at those individuals who could be talking about PPC or keyword optimization, that’s our marketing professionals, the experts in that field.

But it goes back to what we talked about earlier; we should not be looking at those in isolation.

We need to look at the whole thing holistically.

Take the sales pitch, for example. If you want to sell a product, either you do it digitally through a partnership or you actually have your sales team doing it.

If we're doing it digitally, it's very common to see that when an ad posted on Facebook is clicked on, it takes you to a landing page.

Alternatively, when you use PPC or organic, those bring up all different landing pages. And then when you design your landing pages, they’re all tailored to different audiences and keywords.

The question comes in when we’re doing our sales pitch in-house with our sales team.

  • Are we doing the same thing?
  • And are we fixing the pitch?

We look at the particular industry a customer is from and the size of that industry, and then we say, “It's the same for this group of customers.”

If you're doing this already, that's great. At least you're looking at the industry and customer profile etc.

However, I think that you can do way better by leveraging what data or information you have before through the initial interactions with a prospect.

Let’s say you have two prospects.

One comes in and says: “Hey, I like service. I'm really interested in that.”

The other says: “You know what, I don't care about the pricing. What I really want is convenience.”

When you go in to do the sales pitch, you probably think that you’ll talk about what they’re interested in because it’ll give you the highest chance of success.

That is actually true in most cases. Are we doing that? And how do we do that? What's going beyond this? Is it over after we do the sales pitch?

Maybe the takeaway here is to tailor your sales pitch based on the information you’ve already learned about this prospect. But it doesn't end there, because afterward there is account management and customer success.

You interact with the customers and you start doing the promotions and the bundled add-on products with them.

Later on, it will be really valuable for you to have this information.

For example, say you acquired this customer because they clicked on a Facebook advertisement or they came in-house through a referral, and the pain point for this company is cost saving, and the pain point for this other company is actually convenience.

When we talk about add-on products later when we try to target them, or even in the current world if you talk about inflation, you start thinking about your pricing strategy.

Are you going to take the same approach with everybody?

The information should flow through the entire organization within revenue operations or in the broader ecosystem. It should not stop at the sales stage.

Optimisation: Sales pitch - product proposition, cost saving, convenience. Prospect A: cold leads, clicked on email campaign demonstrating the cost savings a business can gain using the product, prospect B: watched a video online, video showing how convenient our product is compared to the rest. Is it same or different, does our team know?

Creating alignment and consistency through product pricing

Lastly, I want to focus on product pricing.

Again, this is a huge topic. We've got the sales promotions up front, and we might have bundles or special promotions going on.

The big question here is consistency and alignment; are we doing it dynamically and quickly enough?

You might be talking to your pricing team about the need for promotions because the World Cup is coming up, and it might take two weeks for them to evaluate everything.

Then, if you’re using Salesforce you might have to set everything up there. And by the time you’ve sorted all of this, you don't have the time to do marketing.

Or if you're consistently doing the promotions to a specific group. I don’t know if many of you have experienced this, but a lot of companies in the consumer industry experience certain customers that are mega-sensitive to price.

Especially with some of the comparison websites, they form a habit; they go on them every year or so to find the next best deal.

Focus area: Product pricing. Pricing at all stages of customer life - sales promotions, bundles, add-on products, special promotions, retention offers. Is this joined up across teams? Are we doing this consistently?

If you’re focusing on your efforts in those areas, then it's going to be a big challenge for you financially.

My suggestion here is to start revenue analytics and put the focus on those top three priority areas - investment, optimization, and pricing.

I keep talking about two key terms here. One is dynamic, and the other is consistency.

These are the two things I think everyone's looking at, as well as alignment across the team. And once we have that, you’ll see that it actually makes a difference.

Focus areas - investment, optimisation, and pricing. Investment - not enough or have additional resources, where to invest in? channel, product, and people vs non people. Optimisation - every stage of the funnel and operations - what and how to optimize? lead conversion, lead allocation, sales pitch, etc. Pricing - produc pricing at all stages of customer life - are we competitive? promotions, retention offers, add on products, etc. Dynamic and consistent analytics engine.

So how do we get started?

What I’ve experienced is that we all talk about data and analytics, but it's just such a big term and it's really difficult to get started.

The key thing in this area is availability and quality.

  • Do you have the data available?
  • And are you capturing this today?

If you don't have quality data, you could be making the wrong decisions. So what do you do about this?

This goes back to the prioritization and the focus areas. For the quality and availability needed to get started, you just need to narrow down the scope and focus on your key areas.

You also need to have a proper platform, either in-house or work to get external vendors to help you with that.

In the longer term, I think what's important for us as leaders is the culture, setting this thing up, and creating alignment across the board. It's a journey, not a big bang; it will take you a long time.

Data - availability and quality. Platform - manual vs auto and in-house/external. Team - standalone org or in different areas?

Written by:

Kun Li

Kun Li

FLEETCOR, VP, Revenue Strategy, Europe & Australasia

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3 ways revenue analytics can drive exponential growth