The R2D business model makes use of continuous, vast stream of customer/market data to optimize inventory and logistics so that they can provide fast delivery, minimal friction, flexibility and precise execution for each customer and for each transaction. Additionally, these businesses should make the execution of the transaction as effortless for the customer as possible.
After the transaction with the customer is completed, Businesses using the R2D business model should use the data on the transaction to make repeating the transaction as easy as possible (for example, using saved product/service preferences and payment/shipping information or making inventory decisions that would make future transactions faster).
In addition, R2D businesses should use the volume of transaction information at the population level to make product/inventory decisions and invest in scaling the most popular product/services so that transactions become faster and more effortless (e.g. Amazon’s scaling their inventory and logistics capabilities wherever the data points).
Business Model 2: Curated Offering
Businesses that deal with customers who need to select products from among an overwhelming number of options and who are willing to share information should develop the Curated Offering (CO) business model. This business model requires optimizing the customer experience in the Request stage of the customer journey.
The CO business model makes use of continuous, vast stream of market/customer data to make useful and meaningful product/service suggestions and recommendations. These businesses should make use of available customer data to ensure that the recommendations as relevant to each customer as possible.
After the transaction with the customer is completed, Businesses using the CO business model should use the data on the transaction to present even more useful recommendations in more areas of the customer’s needs than what the customer would otherwise be exposed to or would choose from amongst on their own.
At the population level, companies should use learnings from the continuous flow of data to invest in more relevant portfolios of product/service offerings and capitalize on potential packages of popular products/service offerings.
Business Model 3: Coach Behavior
Businesses that deal with customers who could benefit from overcoming inertia and biases in their product and service decisions/investments and who are willing to share personal data and get suggestions should develop the Coach Behavior (CB) business model. This business model requires optimizing the customer experience in the Recognition stage of the customer journey.
The CB business model makes use of continuous, vast stream of market/customer data to predict how and when a customer could benefit from a product and service offering. These businesses should make use of available customer data to track when the timing and product/service offering is advantageous to the customer and then to effectively communicate those suggestions to the customer
After the transaction with the customer is completed, Businesses using the CB business model should use the data on the transaction improve the timing, usefulness, and relevance of the suggestions.
At the population level, companies should use learnings from the continuous flow of data to invest in ensuring that customers continue to realize gains from suggested products services so that customers share more information and deepen the advisory relationship.
Business Model 4: Automated Execution
Businesses that deal with customers who have very predictable behavior (and for whom costs of mistakes are small) and who are comfortable partnering with other businesses should develop the Automated Execution (AB) business model. This business model requires optimizing the entire customer experience.
The AB business model requires companies to be awarded the full trust of their customers so that the customer is willing to share all relevant data with the company and to entrust the company with decision/purchasing authority on the customers’ behalf. These businesses should make use of this customer data to determine the best timing and product/services for a customer’s circumstances and then to execute on these determinations to the customer’s benefit.
Though this is a continuously replenishing process, the business using the AB business model should be learning from each customer transactions so that future replenishments and offerings are more helpful to the customer and that any slight errors are eliminated.
These learnings should be developed at the population level as well so that investments can be made in improving operational execution and scaling product/service offerings.
Continuously Repeat and Invest
All of these strategies require continuous, real-time learning from the continuous flow of data (most likely using machine-learning/artificial intelligence capabilities). The conclusions drawn from the data as to the most advantageous (from the customer and company perspective) product/service offerings can be used to maximize returns and then to reinvest in emerging product/service offerings and capabilities.