A SaaS startup’s guide to demand modeling

So you’re ready to go to market, you have big goals and you’re pumped.

But wait.

How will you do? hit those goals?

You have the Right goals in place?

And adding insult to injury, there’s a chance your goals might not be achievable.

And now?

Enter demand modeling.

What is demand modeling?

Simply put, demand modeling is the part of business strategy and planning that delves into target customer behaviors and overall market trends.

With it, you analyze different factors, such as historical data and market conditions, etc., to predict future demand for your products and services. This information helps you make informed decisions about your go-to-market (GTM) strategy.

HERE’S how to figure out how to achieve your ARR goals.

But before we discuss the details, let’s talk about the typical GTM process, which you probably already know but may not have mastered yet.

Going from “here” to “there”

You’ve created a product you’re proud of and you’re ready to go to market. Your vision is strong, your confidence in your offering is unshakable, and you have a lot of hope.

But this won’t be enough.

As you can imagine, hope alone is not enough to go to market. But you already knew this. The method behind your GTM strategy is critical and every detail counts.

The typical process goes like this:

1. Set an ARR goal
2. Inform the GTM team of the objective
3. ??? (we’ll come back to this)
4. Reach the ARR goal

Step 3 is where things tend to get dark.
You may find that you have no real reasoning behind your goals, just the expectation that will be hit. So before tackling this step, let’s make sure the other steps are done right.

Step 1. Setting an ARR Goal

When you set an ARR (annual recurring revenue) goal, you need to be ambitious and realistic.

Start by calculating your current ARR and establish an accurate baseline against which to measure. Define your growth strategy based on the data mentioned above (e.g., market traditions, historical customer data, etc.).

Next, set an ARR goal that is ambitious but realistic. Your goal should be attainable and challenging at the same time.

So, for example, if your current revenue is $100,000 and you want to grow your business by 30%, your target ARR should be $130,000.

Step 2. Inform the GTM team of the goal

Once you’ve established your ARR goals, it’s time to get your team involved (you know, because no one can do these things alone).

Your team should be a group of experts you trust to provide honest feedback. Simply put, this team is typically directly responsible for revenue growth; this includes product, growth, marketing, sales and customer success. They care about the success of this GTM as much as you do and will play their part in making it happen.

That said, it is important to have alignment and open discussions to ensure updated ARR goals are realistic and achievable.

These conversations also motivate each team member by communicating clear expectations and planning to achieve ARR goals. This brings responsibility and reward.

Step 4. Achieve ARR goals

Remember, we skipped step 3 but don’t stress. We will be back.

Ok, so you’ve achieved your ARR goals and taken notes along the way.

Well done! Repeat the cycle and start again.

BUT WHAT IS STEP 3 ABOUT?!

Step 3. Make sense

So, this is where the meat and potatoes are. Literally, the deciding factor behind your strategy. This is where you figure out how to get from “here” to “there.”
Before you get started, take a look at this application template sheet.

This demand model sheet is what I will use to explain how to prepare your demand modeling forecast.

It covers the often overlooked essential details to correctly predict your goals and establish the quantifiable strategy behind that process. It’s your job to customize it to your company’s goals and ensure they are realistic and achievable.

This step starts before step 2, as it is essential to compile it with the GTM team.

So, the best next steps are:

• Observe the cost differences between MQL types,
• Compare CP-SQL and use final 6Q data and
• Be more specific about the length of your sales cycle

Let’s dive in.

Cost differences between MQL types

The cost differences between MQL (marketing qualified lead) types depend on a few factors, such as the quality of the lead, the channel that generated the lead, and the sales process.

This is important to consider because this cost difference can identify the efficiency and effectiveness of your go-to-market efforts.

For example, not all leads are of the same quality, which means some may take longer to close or cost more to acquire. Understanding which marketing channels are more cost-effective than others allows you to do two things:

1. Lean into that method and
2. Find ways to improve other methods that fall short

B2B Fractional Marketing leader, Rui Nunes, is an expert in this field and can provide some great tips for optimizing this process.

CP-SQL and uses the final 6Q data

An SQL (sales qualified lead) is where a lead shows perceived interest in making a purchase and has already spoken to the sales team to verify suitability and intentions. Therefore, the CP (cost per) SQL is the cost associated with this particular type of lead.

In the example above, you compare the cost of marketing leads; in this case you are comparing the cost of sales leads, i.e. leads that are passed on to your sales team because they are likely to buy.

To ensure this data is up to date, compare current results with the final six quarters (6Q) results. This ensures that you are not measuring current information with seasonal or outdated (and to some extent irrelevant) historical data.

Length of the sales cycle

One piece of data that can be overlooked is the total length of the sales cycle.

Being precise here is key, so consider doing the following:

• Identify each stage of your sales cycle. This means that each stage is clearly defined, from initial lead generation to closing the deal. The criteria for moving from one phase to the next should also be very clear.
• Get RevOps in order. Teams across the entire customer lifecycle need to be aligned; this means your marketing, sales, and customer success teams are working together to ensure operational efficiency and achieve the same goals. This also allows you to track leads and customers and every step in between.
• Set milestones: These should be established in advance and the time spent on each stage should be recorded. If you know how much time each lead spends in each stage, you’ll quickly see bottlenecks that slow down business.
• Analyze the data: Be sure to measure current data against any historical information you may have. Here you can identify any trends and patterns that may influence your future predictions.
• Review regularly: Be sure to review this information and update your expectations based on any new data.

To accurately measure this value, you need to turn to experts like EngageRocket co-founder and CEO (Americas), CheeTung (CT) Leong, who has worked closely with business leaders to build efficient and effective teams based on respective markets.

By taking these variables into account, you’ve completed step 3 and, more importantly, set sensible goals supported by data.

Ready to go

So that’s it.

With strategic and well-informed demand modeling, getting targets out of the sky is a thing of the past.

Demand modeling is a powerful tool that provides valuable insights into customer behavior and market trends. By collecting specific data points, such as historical sales duration information, MQL types, and market trends, you can make informed decisions and set realistic goals for the growth of your SaaS company.

And, chances are you’ll actually hit them.

The post A SaaS Startup’s Guide to Demand Modeling appeared first on CXL.

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