Leveraging AI For Advertising Strategies In The Age Of Retail Media
Hai Mag is the cofounder and CEO of Eva, Profit Maximization Software and Agency Services for Amazon and all Marketplaces.
In my previous articles, I explored strategies for maximizing profits on Amazon and other e-commerce marketplaces, as well as optimizing brand management through AI and consultants to create a competitive advantage. Today, I want to delve into the rise of retail media and the role AI is playing in advertising strategies, particularly in campaign creation and bid optimization.
As I see it, retail media has transformed the e-commerce landscape and can offer brands new opportunities to reach their target audiences on platforms like Amazon. Brands can now invest in digital ads to capture shoppers’ attention before they make a purchase. As brands compete for visibility, some might be exploring artificial intelligence to help navigate the complexities of modern retail advertising. Doing so, however, requires a deep understanding of advertising metrics and how to use AI strategically.
Understanding Key Metrics
To develop effective advertising strategies, I recommend using a few key metrics.
• Advertising cost of sales: This metric measures the efficiency of your advertising spend. It’s calculated as ad spending divided by the revenue attributed to the ads. A lower ACOS indicates a more efficient campaign.
• Total advertising cost of sales: Unlike ACOS, TACOS considers total sales revenue, including organic sales, which can provide a broader view of your ad spend’s impact on overall revenue.
• Profit return on ad spend: This metric focuses on profitability; it calculates the profit generated from advertising spend. A positive PRAS suggests that your ad spend is generating profit.
• Total profit return on ad spend: TPRAS expands on PRAS by including all organic and advertising-generated profits. This metric provides a comprehensive view of your profitability to help ensure that your advertising efforts are truly beneficial.
By integrating these metrics into your advertising strategy, you can gain deeper insights into the effectiveness of your campaigns and make informed decisions that drive profitability.
How AI Can Be Used In Advertising
My company provides an AI platform for online brands and advertisers to help with tracking inventory, crafting campaigns and more. Through this experience, I’ve seen AI can be used in advertising strategies in a number of ways, such as:
1. Campaign creation and bid optimization: Campaign creation can be a labor-intensive process that demands meticulous attention to detail and constant adjustments. AI can help streamline this process by automating the creation of targeted campaigns and making real-time adjustments based on performance data. For brands seeking to maximize their presence on marketplaces such as Amazon, AI can also help identify high-performing keywords, optimize ad placements and adjust bids.
However, brands still need to consider three main pillars when approaching advertising: First, are the campaigns profitable? Second, is there enough inventory to supply the demand? Typically, campaigns are not inventory-aware and work independently. Last is the conversion strategies; test campaigns to see which ones convert the best, as I’ve found a conversion rate of 10% can also improve the campaign effectiveness by 10% to 15%.
2. Inventory awareness: Advertising without considering inventory levels can lead to wasted ad spend. For online sellers, running out of stock can result in lost sales. AI can monitor inventory and adjust advertising efforts accordingly.
3. Impression share and profitability: Understanding how much impression share you gain per ad spend is crucial. As impression share decreases, the profitability of your ads may decline. AI can monitor this metric and adjust bids to maintain an optimal balance between spend and visibility. By analyzing impression share and adjusting bidding strategies, brands can ensure their ads are seen by the right customers at the right time.
Best Practices When Using AI
When getting started with AI, instead of starting a new approach and using AI in all products, I suggest implementing one product at a time. Then, you can expand your use of AI gradually. This makes more sense to see the advantages and shortfalls of the algorithms. Any external factor that has never happened before can have an impact on AI algorithms, such as a logistics crisis or a pandemic, for example. The impact of such external factors needs to be analyzed by your team to make sure algorithms are adjusted based on the new context.
While AI can handle many aspects of advertising automatically, the human element remains essential. People are crucial in interpreting data and making strategic decisions that AI might overlook. Understanding the nuances of customer behavior, seasonal trends and competitive dynamics requires a level of intuition and experience that AI alone cannot provide. By combining AI-driven insights with human expertise, brands can develop comprehensive strategies that drive long-term success.
For example, at my company, our pay-per-click strategists spend a lot of their time analyzing the competition, their conversion strategies, pricing, ratings, reviews and consumer audiences and build defensive and offensive advertising strategies where AI can be short of insight. We’ve found combining these strategies with AI creates optimum results.
In conclusion, using AI in retail media and advertising strategies can offer advantages. However, the human touch remains vital in analyzing data, understanding customer journeys and crafting competitive strategies. As retail media continues to evolve, balancing AI with human expertise will be the key to success.
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