Diving into the world of ecommerce PPC advertising, I’m thrilled to sit down with Anastasia Braitsik, a global leader in SEO, content marketing, and data analytics. With her extensive experience, Anastasia has helped countless businesses navigate the complex landscape of digital marketing, particularly in optimizing pay-per-click strategies for online retail. Today, we’ll explore her insights on leveraging powerful tools like Performance Max, mastering Amazon Ads, balancing social media for brand awareness, and utilizing dashboards for profitability. Her expertise offers a deep dive into how platforms and data-driven decisions can shape successful ecommerce campaigns.
How have you seen Performance Max transform campaign results in your experience, and can you share a memorable case study that showcases its impact while walking us through the key steps you took to optimize it?
I’ve seen Performance Max become an absolute game-changer for ecommerce clients, especially because it thrives on the high sales volume data these businesses naturally generate. I recall working with a mid-sized online retailer who struggled with inconsistent returns from traditional Google Ads. After switching to PMax, we saw their return on ad spend (ROAS) jump significantly within just a couple of months. The key was the sheer volume of transactions feeding the algorithm—think hundreds of sales weekly versus the sporadic leads of a non-ecommerce setup. To optimize, we first focused on their product feed, refining titles and descriptions with targeted keywords by exporting the feed from Google Merchant Center and fine-tuning it with specific brand tone guidelines. Then, we segmented the campaigns using custom labels for overstock items, giving them dedicated budgets after identifying top performers. Lastly, we ensured conversion tracking was airtight by integrating Shopify data, pulling in revenue and costs for automated bidding. It felt like solving a puzzle—each piece clicking into place, and the relief when we saw those numbers climb was palpable.
What’s been your most eye-opening experience with Amazon Ads’ detailed reporting, and could you break down how you used Search Query reports to tweak a campaign, revealing the results or insights gained from that process?
Amazon Ads’ transparency with data is something I’ve found incredibly refreshing compared to the often opaque metrics from other platforms. One standout moment was working with a client selling niche kitchen gadgets—when I first dug into their Search Query reports, I was blown away by how clearly we could see conversion rates for their SKUs against the broader market. For instance, we noticed one product had a conversion rate of just 8% for a key term, while the market average was closer to 20%. That gap was a wake-up call. Using the report, we pinpointed underperforming keywords and adjusted the product listing by enhancing images and tweaking the offer to be more competitive. Within weeks, the conversion rate climbed to 18%, which not only boosted ad performance but also nudged their organic ranking higher on Amazon’s algorithm. It was like getting a backstage pass to the customer’s mind—seeing exactly where we were losing them and being able to act on it with precision. Honestly, that level of clarity is rare, and it made me appreciate Amazon’s ecosystem even more.
Given that social platforms are often better for awareness than direct sales, how do you balance social media in your ecommerce strategy, and can you share a specific campaign where it drove visibility while explaining how you measured success beyond immediate sales figures?
Social media definitely plays a unique role in ecommerce, and I see it as a powerhouse for awareness rather than a direct sales driver. I balance it by prioritizing platforms like Amazon or PMax for immediate conversions, while allocating a portion of the budget—say, 20-30%—to social for top-of-funnel engagement. A memorable campaign was for a startup launching a quirky fitness product. We ran a giveaway on Meta platforms, costing us around $10 CPM for 1,000 impressions, and it exploded with visibility—reaching tens of thousands of potential customers in days. We didn’t judge success on sales right away; instead, we tracked engagement metrics like video view rates and ad frequency, alongside growing our email list by over 2,000 new subscribers from that single push. It felt like planting seeds—watching the buzz build online was electric, even if the harvest in sales came later through remarketing. Success, to me, was in those numbers of impressions and new contacts, knowing they’d fuel future campaigns down the line.
Amazon’s ranking philosophy seems to tie ad spend to organic rankings through conversion rates—how have you leveraged this in your campaigns to improve product visibility, and can you walk us through a time you adjusted an offer or pricing based on conversion data with the outcome?
Amazon’s ranking system is fascinating because it indirectly rewards ad spend through conversion rates, giving marketers a clear lever to pull for better visibility. I’ve leveraged this by focusing on driving clicks and sales via ads to boost those rates, knowing it feeds into organic rankings. A specific case was with a client selling seasonal outdoor gear. Their Search Query report showed a conversion rate of 10% for a high-traffic keyword, lagging behind the market’s 22%. We analyzed competitor listings and realized our pricing was slightly off-putting, so we tested a limited-time discount and bundled a small freebie to sweeten the deal. After running targeted ads with the updated offer, the conversion rate shot up to 19% within a month, and we saw the product climb several spots in organic search results for that keyword. It was like watching a slow climb up a steep hill—each percentage point felt hard-earned, but seeing the listing rise in visibility made the effort worth it. That direct feedback loop on Amazon is incredibly motivating because you know exactly what’s working.
Dashboarding tools are highlighted as essential for tracking profitability across platforms—can you share your go-to approach for setting up a dashboard that simplifies complex data, and provide an example of a decision made based on dashboard insights and its impact on campaign performance?
Dashboarding is a lifeline for ecommerce because you’re juggling data from so many platforms—Shopify, Amazon, ad consoles, you name it. My go-to approach is to centralize everything using a tool like Sellerboard, which pulls revenue, costs, and performance down to the SKU level via API integrations. I prioritize simplicity: combining data sources into one view and focusing on key metrics like profitability per product and ROI by platform. For example, with a client running ads across Google, Amazon, and Meta, our dashboard revealed that one SKU was bleeding money on Meta due to high costs with low returns, despite decent overall revenue. We paused that platform for the SKU, reallocating the budget to Amazon where the same product showed stronger conversion rates of around 20%. The result was a 15% uptick in overall campaign profitability within two weeks. It felt like clearing the fog—having all that data in one place was like turning on a spotlight, showing us exactly where to pivot. That decision wouldn’t have been possible without the dashboard’s clarity.
What is your forecast for the future of ecommerce PPC advertising, especially with evolving platforms and data transparency?
Looking ahead, I think ecommerce PPC is going to become even more data-driven, with platforms pushing for deeper automation and AI integration to handle the massive datasets we work with. I foresee tools like Performance Max evolving to offer even more granular control while still leaning on machine learning—imagine feeds auto-optimizing in real time based on live consumer trends. On the transparency front, I hope Amazon’s model of detailed reporting sets a standard that pressures others like Google or Meta to open up more, though I suspect they’ll resist to protect their ecosystems. We might see a split where closed platforms like Amazon become the go-to for lower-funnel precision, while social channels double down on awareness with richer engagement metrics. It’s an exciting, if unpredictable, space—I’m curious to see how marketers adapt to balancing privacy concerns with the hunger for actionable data. What do you think will be the next big shift?
