AI Meets Shopping

Plus, 🔓 Maximize ROAS: Mastering Meta Ad Testing


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LATEST

🛒 AI Meets Shopping: From Perplexity to Google’s AI Sales Assistant
Insights from The Verge and SER

AI is revolutionizing the online shopping experience, with platforms like Perplexity and Google introducing features that streamline purchases and assist users in product discovery. From ordering with a single click to personalized recommendations, these tools are reshaping e-commerce.

The Scoop:

1️⃣ Perplexity’s AI Shopping Tools

Perplexity’s new “Buy with Pro” feature allows Pro subscribers in the US to purchase products directly within its AI search engine, using saved shipping and billing details. Pro users also gain access to AI-written product summaries, a Snap to Shop feature for image-based searches, and free shipping on Pro purchases. 

Meanwhile, non-subscribers can enjoy AI shopping cards for detailed product insights. Perplexity’s merchant program further empowers sellers with shopping trend data and higher product visibility.

2️⃣ Google’s AI Sales Assistant

Google is testing an AI-powered sales assistant integrated into search results. Spotted by Brodie Clark, this feature allows users to engage in a chat that delivers product results directly based on free listings data. 

Accessed via a “Shop” call-to-action link, the assistant pulls tailored results for specific brands or retailers, though it’s unclear if participation is automated or opt-in during its beta phase.

These innovations demonstrate how AI is making shopping more intuitive and personalized. While Perplexity focuses on direct purchases and detailed product insights, Google’s sales assistant emphasizes conversational commerce for product discovery. Together, they represent a new era of seamless, AI-driven e-commerce.

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ROAS

🔓 Maximize ROAS: Mastering Meta Ad Testing

To achieve higher ROAS and optimize Meta ad performance, testing is essential. A structured, strategic approach ensures you identify top-performing creatives and audiences without wasting ad spend. Here’s how to effectively implement three testing strategies and scale for success.

Option 1: ABO Testing with Interest Segmentation

Ad Set Budget Optimization (ABO) is ideal for narrowing down audience interests. Divide your audience into specific interest segments (e.g., Segment 1, Segment 2, Segment 3) and assign four unique creatives to each segment. This method uncovers which interest groups align best with your ads, enabling you to refine targeting and boost relevance.

Option 2: Advantage+ with Broad Creative Testing

Leverage Meta’s AI with Advantage+, which optimizes campaigns across 5-20 creatives, eliminating the need for predefined targeting. This broad approach relies on Meta’s algorithm to identify the right audiences for your ads. For added precision, pre-test your creatives with tools like Neurons AI, which can improve CTR by 73% and boost brand awareness by 20%. Book your free demo to refine your ads before launch!

Option 3: CBO with Layered Targeting

Campaign Budget Optimization (CBO) allows you to test multiple audience layers—No Targeting, Interest, and Lookalike Audiences—within a single campaign. Allocate budget dynamically across these layers while testing four creatives per layer. This approach quickly identifies the audience types and messaging that perform best.

Scaling for Success

Post-testing, analyze results to identify winners:

  • For ABO, focus on top-performing interest segments.

  • For Advantage+, select creatives with the highest engagement.

  • For CBO, refine targeting based on the best-performing audience type.

Scale budgets toward these proven combinations, ensuring sustainable growth based on real data.

Meta ad success requires strategic testing and a commitment to data-driven decision-making. By implementing these phased strategies and scaling based on performance insights, you can create high-ROAS campaigns that consistently convert and drive growth.

FACEBOOK

🎯 Frequency Controls for Engagement Campaigns
Insights from Jon Loomer

Facebook has introduced frequency controls for Engagement campaigns, giving advertisers the ability to manage how often users see their ads. This follows similar updates to Awareness campaigns and offers greater precision in ad delivery.

The Scoop:

You can access this feature by selecting the Engagement objective, choosing “Video Views” under Engagement Type, and setting “Maximize ThruPlay views” as the performance goal. A Frequency Control option will appear, allowing you to either set a Frequency Cap (limits ad views per person) or a Target Frequency (sets an average number of views per user).

Key Requirements:

Target Frequency requires a lifetime budget, a 7-day schedule, and no bid strategies. If these aren’t met, you can still use Frequency Cap to restrict ad delivery.

Why It Matters:

This is the first time frequency controls have been available for Engagement campaigns in the Auction buying type. While it restricts the algorithm, it’s a helpful tool for advertisers needing to limit ad exposure for specific goals. Testing is essential to find the right balance for your campaign.

Frequency controls allow advertisers to better manage engagement campaigns, though results may vary depending on usage. Experiment to see how it impacts campaign performance and refine your strategy accordingly.

QUICK SCOOP

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🗞️21% of U.S. adults regularly get news from social media influencers, with 37% of those aged 18-29 leading the trend. Platforms like X (85%), Instagram (50%), and YouTube (44%) dominate news influencer activity reflecting growing distrust in traditional media as audiences seek perceived authenticity online.

🤖TikTok may soon allow creators to build AI bots in their likeness through the "V Project" on Douyin, the Chinese version of the app allowing creators to generate virtual avatars that mimic their personality, and enabling 24/7 interaction with users. Users can engage with these bots for insights, even when creators are offline.


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