Digital Enablement
Using Machine Learning to Build a Patient-Centered Pricing Model
We used data science to help our client qualify more prospective patients without sacrificing their standard of care.
Enabling quick, actionable data insights that help create a competitive advantage and increase NPS scores.
Leveraging market research and hard data science, RevGen Partners uncovered what delighted and disappointed the customers of a leading solar company.
A market leader in residential solar panel technology recently acquired their top competitor along with 326,000 new customers. Positioned as the leader in the solar industry and now with over 500,000 customers, this solar company sought to grow solar energy’s share of the market and increase their pool of potential customers. Their primary objectives were to position themselves for future success by improving their net promoter score (NPS), increase customer referrals, and ultimately increasing their customer base.
The solar company wanted to retain existing customers and gain new prospects, which meant a strong NPS was essential. However, their score had been declining over time. A different consulting group previously focused on raising NPS scores but couldn’t capture the whole picture.
With no hard data science and broader industry insights left untapped, this company had many hypotheses regarding the sources of long-term customer dissatisfaction but couldn’t prove or disprove them, which left them questioning their approach.
This solar company had large quantities of data, but without data scientists in-house, they didn’t know how to organize, analyze, and apply those learnings.
We used data science to measure the correlation between voltage direct current (a key attribute of a solar customer) and NPS scores at three key points in the customer journey. This helped us to narrow down which milestones have the most impact on overall customer satisfaction and the customer’s willingness to act as a referral.
The solution included industry research, hard data science, and a data repository to house, query, and maintain the customer’s large quantity of data.
Diving into industry research, we were able to provide the company with broader context on industry trends, consumer motivations, propensity to refer, and more.
We gathered the client’s extensive data, sorted it, and built a database that would house everything—including the new insights we gathered. With all the data organized, the company applied hard data science to “find the story” within the data that told us the key drivers that made a customer a “promoter” or “detractor”.
We reviewed data from across the organization and performed a feature analysis to understand which factors were having a critical impact on the client’s NPS score — and why the score was declining over time.
This leading solar company now has organized data, industry-leading insights, and a more complete and compelling understanding of their customer. This resulted in:
Comprehensive industry research gave the client a fresh, new perspective and valuable insights on their industry.
The solar company can now use their data to deliver a better customer experience, which will help them increase their NPS score and build their customer base. They can use all of this information to quickly address service pain points or target areas such as sales, customer retention, and other customer behavior metrics.
With their new database, the company can now quickly and easily access sophisticated data. This data empowers them to develop predictive models to determine potential customer outcomes and opportunities and gives the company peace of mind in knowing that they’re pursuing the best course of action to drive long-term customer retention and future growth.
Thanks to working with RevGen Partners, the solar company has the tools they need to translate their NPS increase into revenue projections. These projections will help them determine the level of investment to make in different areas of their business, maximizing both their customers’ satisfaction and their profit.
We used data science to help our client qualify more prospective patients without sacrificing their standard of care.
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