SaaS Product Pricing Headache? Choice-Based Conjoint (CBC) Analysis Can Help
To determine the optimal price point for your Saas product, you first need to understand your customers’ perception of the value of your product.
Understanding the variance of our prospects value-perceptions includes a gamut of research techniques including relatively simple surveys. Ultimately, the knowledge you glean from your target market, or actual users, can provide actionable insights as to both the real and perceived value of your product, and guide you to the price-point that is most likely to drive the greatest revenue.
Choice-Based Analysis & Your Optimal SaaS Price Point
One method for identifying your product’s perceived value is choice-based conjoint (CBC) analysis. It is considered by many experts in the space to be one of the most accurate methods for determining an optimal price, and its application has increased over the years in different industries.
CBC analysis provides respondents with a choice of multiple product options and asks for a rating on which option or package they would most likely purchase. Respondents are given information on plan features and prices so that they can compare real and perceived value-based difference between the alternatives. This mimics dilemmas and trade-offs customers face everyday when deciding between products. CBC analysis also provides insights on the perceived importance of different features — especially useful in value-based and multi-tiered pricing.
When You Should Consider CBC Analysis
This surveying method is ideal if you have a more complex product with multiple features, and if your objective is to determine what features and options customers would prefer. It can also help you evaluate new offerings or variations thereof against your existing range of products and that of your competitors. Finally, as CBC is often used to study the relationship between price and demand, it’s especially useful when the price-demand relationship differs from brand to brand.
By understanding precisely how people make decisions and what they value in your products and services, you can determine the sweet spot or optimum level of features and services that balance value to the customer against cost to the company.
If you’re asking questions such as: should we build more features? should we bring our prices down? or what changes will hurt our competitors most?, then a CBC analysis may be useful for you.
But There are Many Additional Benefits We Haven’t Even Touched On Yet…
CBC is widely used for pricing and brand value studies. Chris Chapman of Google has discussed its many benefits, including:
- Ability to conduct a study via the Internet or paper-based surveys
- Allowing the researcher to include a “None” option for respondents, AKA: “I wouldn’t choose any of these”
- Providing greater robustness of results — particularly for pricing the product
- Enabling comparisons with fixed products or tasks, so you can test against an existing standard
- Providing real-time feedback on new products or variations of existing products
- Simulating the decisions your target consumers would make in the marketplace
- Providing insights on how a new product would be received in the marketplace
- Aiding in forecasting potential demand or market share
- Ability to deal with interactions
Ensure a successful CBC study by following these simple, general guidelines:
- Use focus groups or surveys with open-ended questions — this will help define your top features
- Keep options clear and as simple as possible
- Don’t have more than five or six features to choose from
- Follow general online survey technique best practices
- Test your survey
- Keep your survey to 15–20 minutes maximum
- Provide incentives — such as gift cards — to respondents
Moving from the Raw Data to Analysis and Interpretation
After you’ve finished the analysis, a range of statistical tools (typically included with software such as Sawtooth) analyzes which items customers choose or prefer from the product profiles.
This will help quantify what is driving the preference from the features and levels, but more importantly, it evaluates and compares each feature and level against one another.
Once you understand your customer’s needs, what they value and how they will use your SaaS product, you can then determine how much those customers would potentially pay for your service. This can be done successfully with a CBC method — especially if your product contains a lot of features, and you need to know what your audience prefers, and at which level. This wealth of data will help determine your product’s price sensitivity, enabling you to continuously correct and improve your pricing over time.