Line art illustration showing software development and customer research elements

How Optimization Research Increased Reach and Revenue for a New SaaS Product

Michael Patterson, Radius Insights, Radius Global Market Research 2021/10/michael-patterson-bio.jpg

by Michael Patterson, PhD

Chief Research Officer

Case Study:
Optimization of Offerings

 

Challenge

A Software as a Service (SaaS) company wanted to configure and price a new product that would be widely accepted by users while generating good revenue for the company.

We worked closely with key stakeholders to understand the software’s current and potential features, and to better understand sales and revenue goals they wanted to achieve. With activation strategies in mind, we set out to design a research approach that could help them develop an ideal product.

 

Custom Approach

Step 1: Understand the decision-making process.

We asked professionals to share their requirements and preferences in a survey that utilized an Adaptive Choice Based Conjoint which presents features in a way that mimics how decisions are made in real life. This method works best for configuring products with a large number of features to choose from.

Respondents were asked to:

  1. Identify important features.
  2. Evaluate product alternatives to determine their considerations of each.
  3. Determine the product they are most likely to purchase.

In order to best understand the decision making process and assess the relative importance of various features, respondents were shown a number of different screens which presented different SaaS product alternatives and selected the one they would most likely purchase.

 

Step 2: Developing an optimized product for testing.

Based on the research insights, we configured a product that had wide appeal and would generate good revenue. We discovered that, in addition to price, there were four features identified as key to the success of the new product:

  1. Wait time to speak with a live customer service representative.
  2. The percentage of work the software would complete vs. the user.
  3. The amount of guidance the software would provide.
  4. Number of contact resolution calls.

We built a product offering that included the most preferred configurations and found that the product appealed to 80 percent of the respondents, if offered at the same price as the current software. We also found that if the SaaS company increased the current price by 6 percent, revenue would be optimized for the client, with little impact to demand.

 

Line art illustration of person on laptop and software elements

We built a product offering that included the most preferred configurations and found that the product appealed to 80 percent of the respondents, if offered at the same price as the current software. We also found that if the SaaS company increased the current price by 6 percent, revenue would be optimized for the client, with little impact to demand.

 

Growth Outcome

To create an optimized product, we worked with the client including their engineering and marketing teams in order to help them get the most value out of the research. In this case, we led an activation workshop which involved detailing the results of the research via a presentation, and then working with them to identify the mix of features that would deliver the most appeal to customers. To identify this set of features, we used an Excel-based simulation tool which allowed us to conduct “what-if” scenarios allowing them to understand how different products would perform.

The focused led us to recommend that the company focus on the following features:

  • Ideally, the product should have a wait time of 1 minute or less for customer service calls.
  • Provide features that allow professionals to complete a vast majority of tasks within the software.
  • Provide features with specific guidance allowing issues to be quickly addressed.
  • Number of contact resolution calls should be kept to a minimum.

With these enhancements, the company could increase the price of the software by approximately $500 to maximize revenue. Most notably, we found that the optimized features would lead to the maximum revenue, with the highest amount among premium brand users.

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