Woman checking receipt in grocery store

Daisy’s AI a Leading Indicator Predictive of Retail Sales Outcomes

A leading indicator is a measurable variable that predicts changes in economic conditions or business activity before it occurs. Leading indicators are particularly valuable in industries with long lead times (e.g., manufacturing), where changes in demand may take months or even years to manifest. By tracking leading indicators, businesses can make proactive decisions to adapt to changing market conditions and stay ahead of the competition. 

In retail, AI-powered decisions are leading indicators for sales outcomes. AI systems independently measure the quality of a decision to provide a mix of decisions that are highly impactful. They guide retailers in making data-driven decisions based on insights gathered from vast amounts of transaction data, driving significant financial results. 

With a strong association to positive outcomes, AI is without a doubt a must have in today’s retail space. This blog will provide an overview of why AI is a leading indicator predictive of retail sales and how Daisy’s technology is evidence of this correlation.  

Capabilities That Make AI a Leading Indicator of Sales Outcomes


Woman shopping in produce section of grocery store

 

AI systems analyze transaction data to provide the most impactful recommendations for promotional and non-promotional products based on consumers’ past behavior, search history, and purchase history. This is done in conjunction with the consideration of other factors, like product affinities, seasonality, etc. By leveraging these recommendations, retailers can increase the likelihood of customer purchases, ultimately driving sales.

Moreover, AI helps retailers optimize pricing strategies by analyzing competitor pricing, customer demand, and product availability, among other factors. This enables retailers to set prices that are competitive, yet profitable, and encourages sales – especially as consumers become increasingly price sensitive.

Ultimately, AI systems offer impactful decisions that enable retailers to make data-driven decisions. It is precisely these quality decisions that are leading indicators for sales outcomes, as they lead to product and pricing strategies that provide a better shopping experience and drive customer purchases.  


How Does Daisy Generate Recommendations?

We deliver decisions that are beyond the scope of human ability – i.e., the millions of granular decisions that simply cannot be made manually. In retail, these are often the decisions that are massively correlated to sales outcomes. 

Our system collects and distills retail intelligence to deliver highly impactful decisions for promotions and pricing. We recommend the right mix of items to promote and not promote at the right price, quantity, and in the right channels; personalized to each organization to drive increased traffic and sales. 

We rank our recommendations on their ability to drive incremental sales utilizing our Relative Index – which illustrates the relative strength of one recommendation versus another (Fig. 1). Our recommendations are also assigned a green, yellow, or red color score – visually representing their strength and level of impact (Fig. 1). Strong (i.e., green) recommendations are typically ‘Halo’ driving products and price points – i.e., those that drive associated sales and are most impactful in terms of their effect on total store.

 Daisy retail portal mockup
Fig. 1 shows products recommended for promotion with their Daisy Rank and color score on the right-hand side as well as the Relative Index.

What Makes the Daisy System a Leading Indicator?

As aforementioned, autonomous AI independently creates a metric with which it measures the quality of a decision - uncovering those that will result in the best outcome. At Daisy, our Relative Index metric is a leading indicator highly correlated to sales outcomes. Importantly, it is a leading indicator that is incredibly granular – i.e., at the level of the decisions that retailers make every day. 

Since low-ranked green recommendations represent the products and prices that are most impactful according to the Relative Index, leveraging those recommendations means we can predictably grow sales. As a rule of thumb, green decisions make more money than yellow decisions make more money than red decisions.  

This chain of causality makes the Daisy system easy for users, as they can simply choose our best products and price points when making promotional product and price decisions. Retailers that closely follow the best recommendations (i.e., the best products and prices) indicated by the Daisy Relative Index, rank, and color scoring have the potential to see total company sales grow more than 5%.  

Retailers can identify patterns, trends, and correlations that would be impossible to detect manually with the help of AI. By leveraging this intelligence, retailers can optimize their sales strategies, target the right customers, and make data-driven decisions that lead to improved sales outcomes.  

Those leveraging the Daisy solution have the power to predictably grow their business – with the potential to increase total store sales more then 5%. With a leading indicator this strong, investing in AI-powered decision-making means being well-positioned to thrive in today’s industry.

To learn how we can help you predictably grow sales, get in touch!

Subscribe to our newsletter and learn how AI will provide a competitive edge and elevate your people to do the tasks only they do best

Sign me up