The Added Sales Value ML Personalization Brings
Top US Retailers

Or If You’re Not Walmart, What Do You Do?

Retail has been transformed by AI and ML driven personalization. Personalization is used for many purposes such as product recommendations, coupons, special personalized offers, personalized communication touchpoints and more. Consumer behavior in 2023 is dependent on many impactful factors: global recession and inflation, more online shopping and an even greater offering than ever before. So, what should retailers do in order to retain customers and increase sales? Focus on personalization and more so with technology (AI/ML) that helps in learning and understanding consumer behavior in order to monetize the data and create a better customer experience.

Artificial Intelligence in Global Retail Market to Reach
$57.8 Billion
by 2030

The Future is Very Much Here

AI/ML is everywhere and is here to stay, but the technology and the market has matured. Brands use personalization to make every transaction relevant, and customer engagement, retention and loyalty is dependent on this.

The market continues to grow and top retailers cannot be left behind, but there is also the need to find the right provider – one that understands both the data and how to monetize it. The technology chosen should align with business goals and strategy.

What is AI/ML Personalization and What is it’s Value to the Retailer?

AI/ML-driven personalization uses machine learning (ML), deep learning, natural language processing (NLP), etc. to personalize a brand’s marketing messages, content, products, offering and services. And now we hear more and more about XAI – explainable artificial intelligence is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms.

Once, a long long time ago, you had the corner shop, where the seller knew your name, size and favorite color and could offer you exactly what you wanted – with a smile! Now, as the world has grown and businesses with it, the vast amounts of data that retailers have can be evaluated and used to create customized recommendations and offers – very much like the seller of old times but much faster and on a much larger scale.

Strategy! And Some More Strategy

The most important part of personalization is strategy – both on the organization’s side as well as the technology provider’s side. In order to strategize we need to consider some important facts:

  • Only 15 percent of retailers have fully implemented personalization strategies (US)
  • The global personalization software market hit an estimated $943 million in 2022
  • Product recommendations and predictive customes service are the top two personalization uses in marketing
  • 91% of consumers are more likely to shop with brands that provide relevant offers and recommendations (US)

So, we have 91% of consumers wanting personalization but only 15% of retailers fully implementing personalization technology and strategies – how do we overcome this gap? In addition personalization must be accurate in order to be effective – and this brings up another issue – data collection. For personalized products and services, 47% of consumers and 63% of marketers think companies need consent to use their data. So strategy is essential in order to overcome these obstacles (read our paper on personal relevance and how to use it effectively).

So, How Can AI/ML Add Value to Retailers?

Increase Average Order Value: Average order value (AOV) tracks the average dollar amount spent each
time a customer places an order on a website or mobile app. Using AI/ML increases the total purchase amount in a single order.


Average order value (AOV) of e-mail personalized with the use of artificial intelligence (AI) according to marketers in the United States as of February 2018 (in U.S. dollars)

Fig 1. The statistic shows the average order value (AOV) of e-mail personalized with the use of artificial intelligence (AI) according to marketers in the United States as of February 2018. It was found that responding marketers who were using AI for e-mail personalization recorded an AOV of 145 U.S dollars, seven dollars higher than those who were not using AI in their campaigns.

Supply Chain Optimization

AI can review consumers’ previous purchase patterns and provide an alert when the stock of best-selling products may reach a critically low level. Maintaining a well-stocked inventory is essential to retailers. AI can also provide insights into consumer demand, whether they are seasonal or economical.

Increase Customer Satisfaction and Loyalty

Improved customer experience is the top benefit of personalization according to marketers. AI can help in a number of ways, whether these are chatbots or predictions into what the customer wants. AI will provide customers with personalized content, messaging and offerings during their shopping journey and will feel that they are taken care of by the brand throughout their experience.

But in order to really use AI to the organization’s advantage, the real power of AI/ML is the ability to constantly learn from the data and help monetize this data for the retailer.

How Has Sagarmatha’s ML Platform Contributed to the Continuous Learning and Year-Over-Year Improvement of Retailers?

Sagarmatha’s ML-based software solutions enable retailers to deliver personalized and relevant shopping experiences while providing strategic decision support. We have established successful partnerships with top-tier retailers globally, collaborating closely with them to optimize the performance of their personalized campaigns based on their unique business goals and constraints.

By leveraging our proven technology and aligning it with the retailers’ objectives, we develop tailored strategies that cater to each customer’s specific needs. The following examples demonstrate the tangible results achieved through the combination of our technology, expert team, and customer-centric approach.

2022 Customer Example: US Leading Retailer Incremental Sales – Year Over Year Continued Performance Increase



ML has clearly changed the retail industry and continues to do so – customers experience an individual journey, which in turn strengthens their brand loyalty and engagement. Technology is a critical component of every retailers’ strategy plan, but it needs a partner who can help monetize the vast amounts of data the technology provides.

Sagarmatha has been at the forefront of grocery retail personalization since 1998, dedicated to empowering retailers and suppliers to understand shoppers’ behavior and optimize business outcomes by leveraging consumer behavior-based ML/BI technology.

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