From numerous blogs, articles, videos and other materials that I have gathered over the last few months, and in particular the very generous information freely shared by Price Intelligently, I have blatantly lifted, copied, and compiled this cheat sheet of what I feel are the essential points of a pricing strategy and it’s ongoing execution.
And yes, to commit to a pricing strategy on an ongoing basis is a ton of work. But it’s worth it. As presented by Price Intelligently “In our study of 512 SaaS companies, we found out that monetization had the largest impact by far on your bottom line.” Acquisition increased growth by 3.32%, retention by 6.71% and monetization (pricing) outperformed both combined at 12.7%. Pricing is the best business lever to target “better customer channels, or raising prices to better fit value.”
Pricing is a continuous process that never ends;
- week 1 to 4; customer / market research
- week 5 to 7; the customer communication plan and impact analysis
- week 8 to 9; implementing changes
- week 10 to 12; evaluating changes, compiling lessons learned
Bring together a multidisciplinary team from your company to form a pricing committee comprised of;
- customer success
Have and maintain the following data on a real time, or near real time basis, to evaluate pricing changes and measure progress;
- MCAC; Monthly Customer Acquisition Cost
- MRR; Monthly Recurring Revenue with Growth (Prior Year MRR over Current Year MRR) > 20%
- MCCR; Monthly Customer Churn Rate < 1%
- CLTV; Customer Lifetime Value
- CLTV to MCAC Ratio > 3:1
Know the value metric that your customers evaluate your pricing by. What is the primary unit of consumption that they are hiring you to deliver and that they will on average evaluate your pricing plans by? Your value metric must align with your customers needs, it should grow with the customer as they grow, or as they choose to consume more of your product offer, and it should be easy for them to understand and compare across your pricing plans.
Ideal Customer Profiles
You want to multiply what has worked and what is on trend to work next. To do this you need to know who is most likely to hire you to do the job that you provide and who values your work the most. You need to know who your ideal customers are. This isn’t guesswork. Your existing customer data, assuming you have customers, and the new business that you are winning, will tell you.
For every customer you have and every opportunity that is in your pipeline and that is showing a high likelihood of closing you need to know the following:
- the sector (industry) they are in
- the size of their company
- what role your purchaser holds within their company
- their consumption (quantity) of your value metric (or intended consumption for opportunities)
- what features they value most, and least (Relative Preference Scores - defined next)
- their willingness to pay (Price Sensitivity Analysis - defined next)
- their lifetime value to you (or forecasted life time value for opportunities)
Then segment your customers into 3 to 5 ideal customer profile groups based upon their life time value. By segment you will now know what sectors to target, the typical size of company you should pursue, and who from those companies are your purchasers.
For each aggregated customer profile you need to know what % of your customer base they comprise, what their life time value is, the customer acquisition cost, and the ratio of lifetime value to customer acquisition cost for this profile. Anything less than a 3:1 ratio is unlikely profitable to pursue unless they are a gateway to your higher tiers.
Everyone, from product development, pricing, marketing, sales, customer success and support now knows who they are working for and what they need to do to maximize returns from your highest value ideal customer profiles.
Product development knows who to build for based upon their relative preference scores. Pricing knows by profile what their price sensitivity is to maximize both market share and revenue. Marketing knows who to target and how to speak to them. Sales knows who to pursue and sell to. Customer success knows to focus on maximizing highest tier profiles by retaining them and converting lower tiers into that segment. And support takes great care to eliminate all friction for these high value groups.
As a whole, the goal of the company is to move customers up the ideal customer profiles to consistently increase the % of the customer base that is in the highest tier. Lincoln Murphy of Customer Success fame, refers to this ladder of profiles as Success Vectors.
Relative Preference Scores
Determine the features that are valued most, and those that are least valued, by talking to your customers. Present them with your list of hypothesized features that you believe your customers want and ask them to rank rate them as either Most Preferred or Least Preferred. Also ask them if there is anything that isn’t on your features list that should be. Calculate the relative preference score for each feature by subtracting the number of times a feature is least preferred from the number of times it is most preferred and dividing that number by the number of participants in the survey. Plot the relative preference scores for each ideal customer profile and update it at least quarterly.
Price Sensitivity Analysis
Determine the willingness to pay of your Customers by asking them how they value the job that they would hire you to do by classifying on a sliding point price scale the following price sensitivity questions;
- At what price would you consider the product to so expensive that you would not consider buying it? (Too Expensive)
- At what price would you consider the product to be priced so low that you question the quality of it? (Too Cheap)
- At what price would you consider the product is starting to be expensive, so that it is not out of the question, but you would have to give it some thought before buying it? (Expensive/High Side)
- At what price would you consider the product to be a bargain - a great buy for the money? (Cheap / Good Value)
Plot the results for each price sensitivity questions; Too Expensive, Too Cheap, Expensive / High Side, Cheap / Good Value, on a chart that has the Price Points on the X axis and the % Of Respondents on the Y axis. Between the intersections of the 4 Price Sensitivity lines is the acceptable Price Range.
By changing the Y axis from % Of Respondents to % Of Sales Lost in the Price Sensitivity Analysis chart and taking the area below the Too Cheap line and Too Expensive line you can plot the price elasticity of your market. The lowest point of the area drawn will result in the highest market share.
However, highest market share might not equate to the highest aggregate revenue, you need to slide along the scale to determine your optimum market share versus price point as it relates to the best bottom line for your company. This can be calculated by determining the potential revenue at each price point for 100 customers by multiplying the price point by the percent of customers that would be willing to pay that amount and when plotted on your Potential Revenue Chart it clearly presents the cumulative revenue impact of your price point options for 100 customers.
To present your pricing page package it up into plans, with each plan targeting a respective ideal customer profile. Typically moving from your lowest tier value plan on the left through to your highest tier plan on the right. Each plan is packaged based upon the ideal customer profile delineations for feature preferences and price sensitivities, with the value metric and the features provided increasing as the plans move from lowest to highest tiers.
The pricing package design checklist:
- Keep it simple and clear so that potential customers can make an informed decision, full disclosure, no need to “call”
- Highlight your value metric to show exactly that matters most to the customer across plans
- Provide non-friction gateways to plans, not trials, how can they sample and continue sampling without barrier causing trial expirations
- Redirect from bargain shopping to value seeking by using comparatives between plans
- Use the number 9 in prices
- Anchor and drive the sale of lower priced items by comparing to much higher priced items
- Structure prices using a 3 part tariff; base fee, includes X value metric, anything above X costs Y
- Make sure all plans maximize their respective values while not robbing from each other
- Do not do competitor price comparisons - customers are tired of them
- Descriptive text conveys time and experiences more than price, customers tend to make decisions based upon time saved and the experience delivered more so than price
- Provide local pricing - design for local markets, use their currencies, their language, use the PPP http://www.economist.com/content/big-mac-index to set local prices
- Do not discount your prices as a negotiating tactic. It lowers willingness to pay and increases churn rates thereby decreasing lifetime values. Do consider providing published discounts for nonprofits, education, etc.
- Do not A/B test your pricing page - there is rarely enough traffic to statistically validate the results and it annoys the hell out of customers if they have an inconsistent pricing experience