Decoding the Algorithms of Amazon: Understanding How Consumer Demand Impacts Ecommerce


It’s hard to remember, but before the roads were filled with Amazon trucks delivering our packages in two days or less, we used to drive to the store to shop for what we needed. Brick-and-mortar stores teamed up with brands to determine the optimal placement and positioning of products to entice consumers and their wallets. Where your product landed on the shelf had everything to do with your relationship with the buyer. These days, however, consumers are the ones driving product placement, and owning the digital shelf has everything to do with the technology behind the scenes.

A Consumer-Run Ecommerce World

According to eMarketer, this year’s global ecommerce market is expected to total $6.3 trillion, and Amazon’s proportion of these sales is also forecast to rise. In order to thrive in this economic market, it is critical for retailers to dive into consumer data and apply their learnings strategically. Generative AI has started to play an ever-increasing role in this process.

A recent survey from Google Cloud supports this concept, reporting that 81% of retail decision-makers feel an urgency to adopt generative AI in their businesses. Google is one of many well-known brands that recently introduced AI initiatives, including its Vertex AI Search tool that utilizes LLMs to uncover relevant searches, ultimately resulting in increased sales. Instacart and Walmart have enhanced their search capabilities with the addition of generative AI to help consumers identify and purchase products more efficiently. Last September, Instacart added conversational search to its platform, and Walmart launched a similar capability in January 2024 at CES.

Understanding the Algorithms of Amazon

As the largest ecommerce retailer in the world, Amazon has developed its own AI technologies to analyze and take action based on consumers’ shopping behaviors. Amazon and other retailers are relying more and more on these kinds of algorithms that use AI to interpret data from consumers’ spending habits, along with cash flow and profit maximization inputs, to better manage inventory and help determine what items are front and center when consumers hop online to shop.


Amazon has even developed a supply chain optimization solution that uses AI and automation to forecast inventory and warehouse placement of items. This has an impact on what SKUs brands will actually sell through on the site and is a change from the more traditional methods involving vendor managers and buyers, aka humans. This hybrid approach to decision making could eventually evolve and be 100% algorithm driven.

A Single Source of Truth in Data

To succeed in this environment, brands need a single source of truth for their data to effectively manage their ecommerce business. This ensures that internal teams operate in efficient synchrony, using the same set of information across all functions.

Integrating data such as market share, sales, advertising performance, inventory availability and content quality creates a 360-degree view that makes it easier to make quick and educated decisions. When implemented shrewdly, this strategy enables teams to manage profitability at the SKU level, monitor (and ultimately grow) market share, automate the resolution of potential issues on product detail pages, monitor the competitive and relevant category landscapes and more.

Ecommerce businesses that have easy access to a complete view of the key data they need to run their business create a competitive advantage over those that don’t.

Drive Demand with Incremental Real-Time Ad Strategies

If a brand wants to truly own its digital shelf, it must adopt a day-parting, incrementality-focused advertising strategy that optimizes ad spend in real time, based on the latest data that informs which pairing of keywords and SKU will result in the most incremental sales at any given time.

The key to this metric is the estimation of sales a brand would not have gotten if it didn’t utilize advertising. Incremental advertising incorporates a dynamic share of voice and search rankings, shopper propensity to buy and relevancy of searches to develop this estimate. This strategy reduces cost and effort compared to traditional methods such as media mix modeling (MMM). And instead of relying on historical data to make decisions, incremental advertising allows you to use current data to inform ad spending immediately.

The biggest source of information on customer behavior and buying trends, as well as key predictors of where the market is headed, comes from real-time data sourced from online retailers. Leading brands use technology partners to interpret data that includes trending search terms and customer reviews to guide their advertising strategy.

Both high-performing and underperforming search terms offer insight into where ad dollars should be invested and potentially redirected. Subsequently, brands can modify their advertising budget for positively performing search phrases, enhance their content to align with evolving customer preferences as indicated by the search terms, and refine to grab customers’ attention. Tracking competitor data trends is also fruitful and will further inform ad spend and strategic decision-making.

Leveraging tech is the only way to incorporate real-time consumer behavior into your ad strategy while also taking into account competitive dynamics and your own brand strength in determining the optimal deployment of ad dollars.

The Importance of an Inventory-Aware Advertising Strategy

To maximize the impact of advertising in generating additional sales growth, the most sophisticated brands have implemented an inventory-aware advertising strategy. The only way to do this is to have a single source of truth in your business, one that combines sales, marketing and supply chain data. This will mitigate losses not only due to wasted ad dollars spent on items that otherwise would sell out; it also mitigates the risk of degraded Share of Voice, which comes from items going out of stock and being pushed down rankings in favor of other items that still have inventory. 

Going Forward

Significant advances in technology, led by the rapid adoption of generative AI, will continue to transform all aspects of the consumer shopping journey. These technologies have enhanced customer experiences, optimized operations, and driven unprecedented levels of personalization. As a result, brands will be forced to dramatically change how they operate their businesses going forward.

From planning and forecasting inventory, product content development and advertising management and execution, brands must thoughtfully adapt to new technologies to thrive in this algorithmic world. Adopting these technologies is a strategic must, not just a choice, if you want to remain relevant and competitive. Success in the ecommerce space is inextricably linked to a brand’s capacity to effectively integrate and leverage these emerging AI technologies.

Himanshu Jain is the GM and VP of product at CommerceIQ. Jain is an experienced business leader with 12+ years of experience across product management, customer success, business development, statistical modeling, building enterprise software and services. He leads product management for the CommerceIQ Advertising platform.

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