As of Q1 2018, Google Shopping ads drove 76.4 percent of retail search ad spend, eclipsing text ads in markets around the world. As these Product Listing Ads (PLAs) become more competitive, the question becomes how to maximize ROI without simply piling on budget.
The answer is competitive search intelligence: understanding where your spend will have the most impact, identifying your strengths and your competition’s weaknesses, discovering hidden (and cost-effective) opportunities and eliminating waste.
With a comprehensive competitive analysis across categories, devices and ad types, search marketers can get a complete picture of their share of clicks vs. competition across the search market, including PLA. With that information, you can finesse your approach to focus spend on the most lucrative opportunities, not to mention knowing what your competitors are doing at any given time.
The fact is, for many retailers, even a small increase in CTR can mean a huge uptick in revenue, so finding a niche opportunity or mitigating the impact of an encroaching competitor can make a huge difference. Here are six steps any retailer should consider to optimize PLA spend in an increasingly competitive landscape:
- Take advantage of AI. The sheer volume and scale of keywords in a typical search campaign can make mapping out competitive terms by category or market niche nearly impossible to do manually, especially given the dynamic nature of search. Using machine learning for categorization is a must. It can provide speed and scale no human can match to identify valuable, revenue-driving search terms, categorize them within 1,500 AdWords taxonomies and do it quickly enough to spot trends in real time.
- Watch your back. Dynamically monitoring PLA trends across channels and devices will give you advance warning if a new player emerges or makes a move in your PLA space, enabling you to tailor your strategy toward specific threats when necessary.
- Prep for seasonal shifts. From “tankinis” to “prom gowns,” seasonal trends can create big search opportunities virtually overnight. Look at last season’s trends and data to identify gaps and double down on PLA winners ahead of your competition.
- Compare product by product. Ad tactics for a specific popular product can vary widely across retailers. Looking at your competitors’ product ads and performance can help you discover the specific ad characteristics — from images to copy to price point or details in the ad title — that will make your ads and PLA spend more effective.
- Reduce waste. Are you displaying men’s apparel products in response to women’s clothing search terms? Are you throwing money at terms all but owned by a dominant competitor? This kind of waste is common in the PLA world. Competitive analysis will let you see where you can tighten up your creative and focus dollars on low-hanging fruit.
- Think page position. Listing results can include as many as 17 ads, making top positioning an important goal. Again, there will be categories where top positioning is virtually impossible (or at least price-prohibitive). Focus instead on niche areas or gaps where you can dominate the results page and bring new shoppers through the door.
As PLAs continue to capture a large share of search spend, markets must be more efficient in how they execute on this channel. To optimize, streamline and get more value from Google Shopping campaign, search marketers should be looking at the market in a holistic way:
- Investigating the value of competitive intelligence.
- Integrating Google Shopping campaigns with AdWords/text ad campaigns to remain agile in a competitive landscape.
- Conducting gap analyses across the retail market to find opportunities.
- Leveraging machine learning for search term categorization.
- Building a comprehensive understanding of consumer search behavior.
Want to learn more? Check out our detailed report on The Rise of Google Shopping.
About The Author
Adthena is the The Ultimate Search Intelligence Solution. It serves hundreds of the world’s largest advertisers through its patented “Whole Market View” technology. Updated daily and unrivaled, Adthena uses machine learning to help digital marketers understand their paid and organic search landscape and improve campaign performance. Processing over 10TB of new data, indexing 500 million adverts and 200 million keywords in 15 different languages every day, Adthena works with over 250 clients spread across 14 different business sectors ranging from retail, finance, travel and automotive. Our Solutions include: Partner Management, Strategic Benchmarking, Gap Analysis, Ad Copy Analysis and Brand Protection.