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Google Shopping, Product Feed Management & Product Data Optimization


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The simple difficult secret of Google Shopping PPC Profits

Tim Gilbert 2017-09-20

A young stock analyst went and visited a guru who had retired as extremely wealthy after a long career as investor. He told the guru that he wanted learn the secret of making money on the market and asked his advice on becoming a great trader overnight.

The guru said "That's simple. Just buy low and sell high."

The young man asked "and how do I know what low and high are?" The old man replied, "ah, that takes a lifetime."


The secret of PPC Profit

The secret to maximizing your companies e-commerce pay-per-click (PPC) performance in Google Shopping, you need to do 2 simple things: advertise to those who want to buy your products, and don't advertise to those who don't want to buy. The hard part is accurately figuring out who wants to buy based on the few words contained in search terms, and how to use your product titles to attract the buyers you've identified, and using reverse keywords to exclude people who are either looking to buy things you don't sell, and using reverse keywords and Adwords campaign structure to reduce bid amounts for people who are just browsing but not ready to buy.

These are the kinds of information you need to know to maximize PPC profit:

  • What you sell
    • The products in your catalog
    • What problems they solve for customers
    • Each products' attributes and features
    • The profit margin of each product to control bid amounts
  • What your potential customers want
    • What do they search for that indicates buyer-intent
    • What problems they know they have and how they express their needs/wants
    • Which attributes/features they type when searching
    • Which attributes/features they care about even though they don't include them in the search
    • What percentage of customers are ready to buy for each search term
  • Who is just browsing
    • What do they search for that indicates casual interest
    • What percentage might become a buyer after browsing
  • Who is looking for something you don't offer
    • What keywords indicate that Google is showing your product ad for an unrelated search

How much can you gain from knowing and using this information?

We did a test where we optimized titles using knowledge of product data and general knowledge of what potential customers want. The case study of enhancing product titles resulted in 151% more clicks, a 47% increase in CTR & a 28% reduction in CPC.


Have intimate knowledge of what you sell

If you are in charge of the PPC strategy for your company, you should know your catalog backwards and forewards. You should know what products you have, the percentage of the catalog in each product category, the quality of your taxonomy/ontology, the average profit margins per category and per product, the sales volumes per category and per product, the common words and phrases in the unstructured text, all the attributes and distribution in your catalog, which attributes the manufacturers consider important for variants, which attributes correlate to price differences in products, synonyms for attributes and features, the up-to-date quality of your structured data, the kinds and quantities of errors in your titles, etc.

Unless you have a very small catalog and have worked on it for years, you need automatic tools and analyses to know each of the above.

The trickiest thing to know about all your products is the problems they solve, because some products solve a different problem for each customer.

Study what your potential customers want

The number one source for PPC campaigns to figure out what their customers want is their search query report (SQR). It contains many nuggets of insight to mine, but it can only tell you about things that are working at least a little. The Google Adwords SQR doesn't report on all the impressions that don't get any clicks, and reports on number or percentages of clicks and conversions have a lot of statistical noise that makes it hard to find new potential in the lower quantity long-tail searches. And for new product types, or if you are new retailer or just beginning to optimize PPC profit, there won't be information to get started.

The second source is using Google search term numbers. This is how you can find out the potential search terms for new products, products with no current PPC. You will need to look up the search quantities for every attribute value in your catalog (ideally using both your structured and unstructured data), then run analyses to determine which ones people are searching for.  There is an important step you'll need to take first which is generating the search terms to look up that combines each attribute with the context of the product type or brand. "Cotton" may be a very important attribute for customers looking for bedsheets, but unimportant for those searching for t-shirts.

Another source of customer insight is mining the feedback comments for the problem they needed solved, what they expected, what impressed them, and what disappointed them. Their problem and expectations will factor into analyzing buyer-intent, while the features that impressed them can make good additions to the product titles or bullet points.

Separate window-shoppers from buyers

The conversion rates of people browsing are much lower than the conversion rates of those who know at least generally what they want and are now just picking out which particular product to purchase. You can still make a profit on people browsing, but only at lower bid amounts for ads.

Currently in Google Shopping, the technique is to split buyers and browsers into separate ad campaigns with very different bid amounts using reverse keywords based on words that buyers will use that browsers won't.

Exclude unrelated searches

When your ads are shown to people who don't want the solutions you are offering, it is costing you in one of three ways. If you are paying per impression (CPM), then every non-potential-buyer search term is money down the drain. If you are paying per click (CPC), either the person will click by accident or curiosity which wastes your spend, or they will ignore your ad which decreases your click-through rate (CTR). In CPC, lowering the CTR decreases quality which means you must now bid more to capture the same number of impressions. Each of these reduces PPC profits and decreases the efficiency of your e-commerce strategy.


How to apply the information

Knowing is only part of the secret; the rest is applying it. We can break application into three steps: connecting the information, attracting buyers, and filtering non-buyers.

In Google Shopping Product Campaigns, you don't have direct control in creating the search terms that you want to bid on, and you aren't creating targeted text ads. What you control are your product titles, descriptions, bullet points. The product title is the most important piece since it will be shown in every kind of view (especially the first part of the title that will never be truncated). No amount of Adwords campaign restructuring or reverse keyword filtering will fix the problems created by having poor titles that don't attract buyers to begin with.

Connecting the Information

Each separate kind of information listed above must be related to other kinds in order to figure out the optimal title for each product. We have to match the search terms from the SQR to that particular product, the average monthly searches for each attribute value of the product (in context), the average searches and clicks for each attribute type (e.g. color, material, size) for the product type/category, and the important variant attributes for the product line/family.

Attracting the buyers

Once we have the information, we can create a new title optimized for PPC profit or improve an existing title. This is how to create a new product title to attract the attention of buyers:

  1. Create the optimal title pattern for the particular product category (e.g. "Brand Gender Feature Material Product-Type, Color, Size")
  2. Select the optimal value for each attribute (e.g. for Gender, pick the option with most searches "Men" vs "Mens" vs "Mens" vs "for Men")
  3. Fill in the values for each buyer-intent attribute in descending order (based on conversion rate, CTR, impressions) and then price-impact attributes (how much that attribute impacts the price) until either the pattern is complete, or the maximum title length is reached.

Filtering the non-buyers

Now that we have a title geared to get buyers to click, we need to create the Adwords campaign structure to separate out people browsing, and filter the non-buyers. We can identify reverse keywords for browsers by looking for words with high conversion rates relative to CTR rate, high product specificity, or high impact on product price. These words should be used to select a higher bid amount (see here for full description on how reverse keywords work).

For filtering out impressions and clicks from unrelated searches, we can look for search terms with high average monthly search numbers from Google, but little or no impressions and clicks in the SQR, and that appear in our product data.


Optimization isn't a one-time task

A lot of buyer-intent is found in the long-tail search terms, and those are ones that take time to build up statistically relevant SQR data. Your product catalog will also be changing over time as a new products are added and old products phased out. The marketplace itself changes as fads come and go.

The amount of work in analyzing product titles stays the same (which is why you should be using automated tools to look at your catalog regularly), but the amount of work in making the changes decreases as your titles get closer. The largest amount of work is in the first round of changes. To make it more manageable, you could use an automatic title building solution, or do the work in batches based on priority (focusing first on titles that are already selling well, and on those that have the most room for improvement).

If you are using an automatic title builder system, you can create multiple title versions and run A/B tests to optimize more quickly.