Comparing Go To Market models
Comparing Go To Market models
How to decide if a product-led approach is better than what you have today.
To decide if a new Go To Market approach that includes product-led elements is better than your current sales motion, you need to look at the right data. For a fair comparison, you cannot look only at the number of closed deals but need to compare the total revenue output of both models.
Defining what success looks like
Before we measure anything, let’s define what success looks like. PLG can mean different things to different people, therefore it’s imperative to define what you want to achieve before you start adding product-led principles to your Go To market. This definition will depend heavily on the PLG strategy you’ve chosen to implement.
For example, if you have decided to leverage product-led principles for customer acquisition, you might need to invest significant resources to make your product’s onboarding more intuitive and to get a good ratio of users who invite others. You would therefore expect quite a significant increase in the number of new customers and/or revenue before calling this a success.
On the other hand if you are testing in-app notifications to better identify upsell potential, the effort is much lower. This would typically not require much change to your existing process and you could even use a 3rd party application to start testing this. Therefore a much lower impact could still be deemed a success in this scenario.
It’s important to have a good understanding of your Go To Market numbers before you start adding PLG. You need to know what you’re comparing your results to in order to make the right decisions. Make sure you know your conversion rates, the different customer segments, and how different tactics contribute to your results. That way when you start making changes, you can better assess the results you are seeing.
End to end funnel comparison
When you have a growing business, it can be hard to assess the effectiveness of PLG. In many cases you cannot run a product-led process in parallel to your existing process, as the mere existing of a different model will distort the effectiveness of your existing Go To Market (often referred to as cannibalization). You can only run it in parallel if you are trying to address new market segments or other new opportunities that you are not capturing today.
A good approach to get around this is to not officially announce your product-led approach but to make it available in the product to smaller segments first and get an impression of some of the conversion metrics and how they compare to your existing approach.
When you want to compare the revenue value of your current model to a new product-led approach, these are the numbers to look at:
The number of new customers that are coming through each motion.
Multiplied by Lifetime Value (LTV) of customers in that scenario. The LTV is calculated by taking the Annual Contract Value (ACV) times the average contract length (in years).
Plus the Average Expansion Value over the customer lifetime.
The challenge with comparing GTM models is that it can take one or two years until the LTV of a land and expand motion is known, because you don’t yet know how much you can expand and how long you will retain these customers.
To get an impression though, we can make assumptions, run experiments to validate them, and then keep updating the model as we learn more. Let’s discuss how that could be done for each of the metrics in this formula:
# New Customers
The number of new customers is typically the first metric you’ll get a better handle on. When you make changes in the first part of the customer journey from the first website visit up until the initial contract a customer signs, you will start collecting data on the conversion of the new approach immediately.
For example, if you introduce Product-Led Onboarding by adding a free trial option on your website, you will immediately start seeing how many website visitors are engaging with this option, so even if they haven’t signed a contract yet, this is already important input for your model.
Having good analytics is key to make good decision. Make sure you track every step of the customer journey, from page visits to button clicks and form submissions. And where possible, run experiments with low effort to assess the impact of intended changes before developing anything.
You could for example add a button to sign up for a trial, but still require the customer to set up a call for to get this trial on the next page. If you run this experiment, you will learn how much interest there is amongst your audience to engage with a free trial option, before you develop the entire self-service approach.
Through experiments like this you can get a good sense of how many new customers you can expect from your PLG approach. Of course if you’re only applying PLG for Retention and Expansion then this number will remain unchanged.
Annual Contract Value
As you’ll start closing deals from your product-led approach, you’ll get a better sense of the average contract value customers are buying. Given that PLG is typically part of a higher velocity Go To Market motion, you would expect first ACV values will to become known within the first 2-3 months of launching a new approach.
That doesn’t mean however that you have to wait for that period to pass. Keep an eye on leading indicators of contract value, like usage within the product, the number of seats a company is using, or anything else that drives your pricing.
While you can often see some first impact of changes in your pricing model by looking at the customers who are already engaged with your company, I’ve learned to look at customers who have gone through the entire new experience from the beginning to understand the real impact.
We saw this when we updated our pricing model at Dealfront in 2023. The new pricing introduced simpler and more affordable options to customers, and even though we publicly released the model in July and shared it on our website, it took another 2 months before we truly started to see the impact on the conversions.
The expectations someone has when they engage with your company have a big impact on the eventual outcome of that process, and it’s hard to change these expectations later on.
Especially if you’ve introduced a new pricing option as part of your product-led strategy, then understanding the new ACV is key. In addition, it’s important to keep an eye on the original deals your company was closing and if those are still coming in. You’ll want to understand if what you are implementing is additive to your existing revenue, or if it replaces (or “cannibalizes”) that revenue.
When looking at this, keep an eye on the different customer segments. If your product-led implementation is bringing in customers with a lower ACV than before but from a new customer segment, this is likely a positive outcome. However if you are seeing a lower ACV from the same segment, then you’ll want to see a higher numbers of customers or some other value for the business to make up for that.
Contract Length
If you haven’t made significant changes to your pricing model, then a fair working assumption is that retention will remain the same as before until you learn otherwise.
A good proxy to assess if you should expect changes on this dimension is to compare the product behavior of previous customers with the product behavior your new customers are showing. If they are similar, then there’s a good chance that retention behavior will be similar. If you are seeing different usage either like lower activity or a lower number of active users, then this could be an indicator that this metric looks different in your new approach.
Obviously if you have introduced a new contract term, like a monthly plan for self-service users when you previously only sold annually, then you can expect the average contract length on this new segment to be lower. For the model to still work, this would for example have to be offset by a larger number of deals or being able to sell to a segment that wasn’t buying before.
Expansion Revenue
Expansion revenue is the hardest metric to get an handle on, yet it’s crucial to understand in a land and expand strategy. When your company offers a lower priced contract, it’s not uncommon for a larger customer to first adopt your solution for just a few users before deciding to onboard the entire company.
Some companies even have it as their deliberate strategy to sell a $10k to $20k contracts at scale with high velocity, and then sell $200k expansion deals to a subgroup of this customer base after they’ve been onboarded.
Therefore not including expansion revenue in your assessment could completely skew the perceived value of a product-led motion. It’s not a realistic expectation though, to have to wait for a year or longer to understand this metric. Luckily there are some things you can do to gain more confidence on expansion earlier on.
The simplest way to get a baseline value is by looking at the contracted revenue you are getting in your existing model. As long as you are capturing the same segment, then even when the PLG model starts you at a lower ACV, you would know from experience that you can grow at least some of these customers to that value.
In that case is you would take your current ACV after expansion and deduct the product-led new business ACV from this amount. The result is the upside you know you can expand the contract with, even if the starting point is lower. Let’s say you can grow your current customers to a $70k annual contract and you are now closing customers at $15k initial contracts on average. If this is the same customer segment, then you would know that there is $55k upsell potential based on past experiences.
Keep in mind that these are just estimates. Customers can behave differently in a product-led approach, but historic numbers will be more relevant to your business then using industry averages or something similar.
If you are considering introducing product-led principles throughout your entire Go To Market model and you have a customer base today, then another good option to get more familiar with the expansion number is to implement Product-Led Expansion first.
This allows you to get a more reliable metric of how you could upsell to customers within the product, and it’s relatively straightforward to implement and usually easy to combine with your existing approach.
This would allow you to learn from this experience and get actual values for what product-led expansion could look like in your business model before applying PLG further in your Go To Market.
Follow the data
PLG is only the right choice if the results are actually better. Don’t introduce a cheaper plan if it cannibalizes your existing revenue unintentionally. And don’t introduce a free trial if it results in less customers engaging with your business. Run tests and look at the data before making big decisions.
An expectation could for example be that you will close more deals of a lower value with PLG, but that’s not always the case. The specifics of your business and market matter. In some cases it can actually be better to sell the full contract upfront.
For example if every buying decision has to go through a complex decision making process. Then you wouldn’t want to repeat this within months after closing the first contract. In that case, a traditional sales approach that maximizes initial contract value might be a better fit than a land and expand approach.
You may also be aiming for an increase in the efficiency of your existing Go To Market with PLG. This could mean that a good result would actually not see you close more deals, but the closing rates of your sales team would go up.
Again though, it is not a given that this will happen. If the product doesn’t guide the user to the next step in their buying consideration properly, then sales will still have to do most of the work. What’s important therefore, is to run these experiments and look at numbers, before you make any big decisions.