Price And ROI Justification
Your price is a function of the value of the transformation you create for the niche, the niche’s ability to afford the solution, and competitor prices in the market offering alternatives to your solution.
We can determine the value of the transformation by calculating the expected value of all the outcomes.
The Expected Value
The expected value accounts for all possible outcomes and their respective values and probabilities.
Where n is the number of possible outcomes, E[X]is the expected value of all outcomes, Xi is the outcome value of event i and P(Xi)is the probability of Xi happening.
The expected value is used to justify the investment. If the expected value is greater than the cost of the investment, then a rational buyer will decide to close.
|MRR (Net Increase)||xi (Outcome Value – Equity Delta)||P(xi) Probability of Outcome||E(xi) Expected Value||Number Of Staff||Cost||ROI|
Economic buyers love this way of justifying a purchase decision because it shows that you did the work of mapping out the business case for them.
It also shows that you understand their business just as well as they do if not better.
If you can’t clearly map out the ROI, work with a few customers to determine the actual ROI and impact of your solution. You can use discovery calls and interview scripts.
Very often you will need to make assumptions about your business case.
As long as these assumptions are backed up by credible data, you can lean on them to form an economic case and justify your expected value.
You are promising to create $1M in value (gross contribution) and assigning a 25% chance that you can do this – if the customer aligns with the outcome value and the probability, that expected transformation is $250k.
If you only charge $25k (1/10th of the expected value), then the customer is guaranteed to buy from you.
The following example shows how the price changes with certainty or the probability of the outcome happening.
John creates a solution for construction companies over $10M in annual sales that if implemented correctly can save them at least 40 hours per month in administrative time.
His customers agree that each hour of administrative time is valued at $40.
The value created from his solution per month is then $1,600 ($40*40). The yearly value created from his solution is approximated to be $19,200.
However, this assumes that the client has a 100% probability of realizing this value. John ran an analysis using his customer data and conclude that only 80% of the clients are realizing the the 40 hour per month savings.
He assigns a probability value of 80% to the outcome for new customers and calculates a yearly expected value of $15,360 (80%*$19,200).
He then prices his product at 1/10th the expected value – $1,536 per year. The customer agrees with his assumptions and buys without thinking.
In the example above, the metric John affected (administrative time) was translated to real dollars using valid assumptions collected from the customer.
The outcome value of the transformation was calculated using these assumptions.
The probability value was found using real customer data and assigned to the outcome value which yielded an expected value.
The price was then chosen to be 1/10th the expected value.
If you can present a cost/expected value of 1/10, the customer will buy since it makes it difficult to find anything they could invest in the business that could beat a 10x return.
The price is also affected by the competitors in the market. The following example shows how price is affected by competitors in the market if there are similar expected values.
Using the example above – John’s product creates $15,360 in expected value and he is pricing it at $1,536, however, imagine Mary, a competitor enters the market with a new technology that allows her to offer the same transformation with the same 80% certainty as John for only $800 per year.
The customer choses Mary’s solution over John’s since the expected values are the same, but the price to achieve the outcome values are different and the ROI is 2x when Mary’s solution is compared to John’s.
Now let’s image that Mary’s track record and customer results are worse than John’s – pretend that Mary can only offer 25% certainty, then her expected value is only $4,800 (25%*19,200), then the customer is likely to go with John’s more expensive solution since the ROI is greater than Mary’s.
This example illustrates the relationship between price, expected value and competition. Notice that the customer just cares about the expected value.
You can charge a higher price if the expected value is greater than a competitor’s – meaning the transformation value is high and the probability of the transformation happening is higher than a competitor’s.
The expected value increases over time with continuous improvements of the mechanism.
The following examples shows this price evolution.
Example Of Price Evolution:
Mike chooses financial advisors as the niche and a transformation/promise of – “add an extra 7 high-net-worth clients per year.”
He calculates that the gross contribution per year of a client for a financial advisor is $20k.
The outcome value is then determined to be $140k per year (not too shabby).
However, Mike doesn’t have a product yet and hasn’t yet validated his mechanism – this means that the probability of Mike actually pulling off the transformation is relatively low.
Mike approaches a few beta customers with the transformation and the beta customers assign a 10% probability that Mike will actually pull of the transformation.
The expected value of the transformation is determined to be $14k (10%*140k).
Mike charges $5k to pilot the solution with his first beta customer. This transaction makes sense to the beta since $5k < $14k and the beta customer realized a 2x ROI.
After working on his solution for a year, Mike delivers the transformation and the probability of the outcome (7 clients per year) increases. Mike approaches another customer who is willing to assign a 25% probability to the outcome that Mike will pull of the transformation, making the expected value $35k. Mike pushes his prices up to $10k per year. This price increase continues as the certainty value increases via improvements to the solution and documented case studies.
The example above shows how prices can increase as the solution improves and the track record gets more solid. What Mike is actually doing is increasing the certainty value or the probability of the outcome happening which increases the price. The price will continue to increase until a competitor comes and offers the same expected value for a cheaper price.
Method 1: 1/10th The Expected Value
If you are able to prove an expected value to a customer, the customer should buy. If you charge 1/10th the expected value, the customer will jump over a fence to buy.
Step 1: Account for all possible outcomes and their values
Step 2: Determine probability of outcomes using 3rd party data and assumptions that you can back up to a customer.
Step 3: Determine the expected value using a model.
Step 4: Charge 1/10th the expected value
Product promises to create $50k per year in value. There is an 80% chance that this value will be created from your product based on your customer’s circumstances. The expectation value is $40k ($50k*.8).
Your customer will easily pay $4k per year since the ROI is 10x.
Example: 5% chance of creating at least $5M in value in 1 year. 50% chance of creating at least $100k in value in 1 year. Expectation value = $250k + $50k = $300k.
A customer will easily pay at least $30k to experience this result. If they can’t afford the cash outlay, it makes economic sense for them to take out a loan to pay you!
When is this method used?
When you are pitching larger deals to businesses and you need to justify pricing.
In your sales script and follow ups to justify pricing.
When you can map out the outcome and risks with some certainty for your customer.
When you can make credible assumptions about the impact of your solution for the customer.
When you are pitching sophisticated buyers with deep pockets.
How to handle competitor’s pricing.
If your competitor can create the same expectation value, then you will need to be priced lower to win the business.
However, in most cases, you can win with a higher price because either the value created is higher OR the certainty of creating the value is higher OR BOTH are true, which increases the expectation value.
To increase your price, you will either need to increase the value created OR increase the level of certainty OR BOTH.
Method 2 : Descending pricing method (used when testing a new market)
When to use this method?
When you are testing a new offer or new market and you are getting price resistance.
When you are trying to lower churn.
When you are still learning how to sell and you are looking for small wins to boost confidence.
Step 1: Calculate the expected value using method 1
Step 2: Descend using multiple offers until you get the deal.
Example: Product promises to create $50k per year in value. There is an 80% chance that this value will be created from your product based on your customer’s circumstances and your analysis.
The expectation value is $40k ($50k*.8). Your customer will easily pay $4k per year since the ROI is 10x.
However, in this case, your customer simply cannot afford $4k, but is able to outlay $2k. You come up with a smaller price and limit some of the features to get the deal done (lowering the expectation value). If this happens multiple times, your pricing converges at $2k because that’s what the market will bear.
Example 2: You are charging $599 per month for your subscription offer. The customer is experiencing value, but contacts you 90 days to cancel (maybe because a competitor is offering to do the same job for cheaper). Customer success drops the price to $299 per month to test if they stay on. If this continues to happen and the customer stays on at the new price point, then the price converges at $299 per month.
Method 3: The Trial Method (when you are starting and selling to betas)
When is this method used?
When you have a brand new product or offer without any case studies or data.
When you are entering a brand new market without case studies.
When your product delivers almost instantaneous value (using a trial funnel).
Step 1: Give the customer a set period of time to experience the value
Step 2: When the period expires, charge them at the end of the trial after they get results.
Example: You are charging $599 per month for your subscription offer. You offer your first customer a 60 day trial so you can collect your case study data. At the end of the trial, you request payment. If the customer experienced value, then they will be happy to pay you a fair price. If they don’t pay, then you need to fix your offer or change your price. Run multiple trials and collect multiple pricing data points. Use these data points to determine your initial pricing for customers going forward.
Method 4: 10% Increment Method
When is this method used?
When your offer is selling through and you are not experiencing price resistance.
When customers are saying “Really, that’s it?”
Step 1: Raise your price by 10% for each customer until you experience price resistance for 10% of your customers.
Example: You are charging $299 per month for your subscription offer. Customers are happy and you are not experiencing any price resistance. You increase your price to $329 per month, then $399 per month, then $499 per month. At the $499 per month mark, you experience some resistance, but your customers are still happy and they are not churning. You set your new price at $499 per month.
It can take you 20-30 customers in the same niche to dial in the price.
Remember to be scientific with your decisions. Don’t operate using your emotions. Look at the data and listen to your customers. If someone is churning out or complaining, try to determine the cause-effect relationship. Sometimes it has nothing to do with price – they simply do not need the product anymore because of a change in their circumstances. Or they suddenly got broke.
If you are not an expert salesperson yet, there is a good chance you will corrupt your pricing data. This is why we teach you how to sell in this program. As you gather more experience and more confidence with sales, there is a good chance you will be able to increase your prices.
Remember your pricing is not set in stone. It’s a function of the vehicle, your sales and marketing skills, and the market competitors.
Don’t get hung up on price. Pick a price, run with it, and iterate accordingly.