Modernization of In-Home Sales for E-Commerce

PROTOTYPING

The founders of a pre-seed startup wanted to revolutionize sales of in-home energy equipment with eCommerce. With years of experience and historical data, they knew they had an opportunity, but needed to prove the concept rigorously. Extrasensory1 was engaged to combine the founders' tacit knowledge and their historical data into a hands-on prototype that aligned the interests of customers and the business so that seed funding could be pursued.

Motivation

Years of selling home energy equipment had exposed the founders to the inefficiencies of in-home sales. But with a high-priced, complex purchase like a furnace or boiler there seemed to be no way around it. Even if the 100s of individual pieces of information that went into a quote could be collected on an eCommerce website, would customers be willing and able to provide them? More importantly, would they feel comfortable doing so? From the point of view of the business, an error-prone quoting process would lead to unpredictable and diminished margins, ill will, or both.

Approach

Extrasensory understood the need to model the quoting process from the customer's point of view. We began by receiving an overview of the process from the head of sales and reviewing the historical data. The next step was to observe the process in person: Extrasensory arranged to send an advisor to shadow front-line sales personnel as they visited customers' homes over several days. These observations put customer intentions and emotions behind the otherwise dry database codes.

With this thorough understanding of business and customer considerations, we created a prototype of the customer-facing eCommerce quoting process as follows:

  • Machine learning was used to develop a predictive cost model from over 100 available inputs.
  • These inputs were boiled down to a set of under 10 essential ones, trading off predictive power for ease of use.
  • A projection of cost, price, and margin developed by backtesting against historical data was used to demonstrate financial viability.
  • An interactive web-based flow chart was used test the process from the customer point of view.
  • The above was iterated with the founders and the heads of sales and operations until it was ready to be handed over for design and fundraising.

Results

Extrasensory's prototype gave investors confidence in the idea, and the founders were able to raise seed funds to build the platform and begin operations. Since the handover from Extrasensory, they have raised over $14 million in two rounds, completed over 5000 installations, and saved customers an average of $1,900. Customers have responded with reviews averaging 4.8 stars on Google, and the company plans to expand to the national level.

Methods

Cross-functional Advisory

Gathering and alignment of functional objectives with management strategy and vision.

AI/Machine Learning

State-of-the-art methods maximizing the value of proprietary data.

Backtesting Based Development

Iterative development of business process or software features based on projections of performance using historical data.

Impact

$14 million

Seed funding raised.

$9.5 million

Savings for customers.

4.8 ⭐⭐⭐⭐⭐

Rating on Google reviews.

1While this case study is written from the point of view of Extrasensory, this work was done by the principal consultant as an independent contractor prior to the formation of Extrasensory.