People use AdWords daily budgets for a number of interesting things--things that Budgets aren't really intended for. We'll break down common use cases, and explain what alternatives make more sense for retailers.
Hey Roy, love your posts and had a question about Google Merchant Center feed structures. What makes a good feed structure? Is there a preferred feed structure that you think is best that provides the most useful information for success in AdWords?
There are three major components that really affect how your feed performs, structurally (that is, aside from the content of the titles and descriptions themselves which I'll cover in a future blog post).
First, where appropriate, use product groups, with parent and child products, where you have variants of a single product (by size, color, etc.). This expands the ways that Google can match your products against specific semantic searches ("XL gray waterproof jacket").
Second, the Product Type field is totally free to use however you'd need for specific attributes of your catalog. One of the common and more effective ways that I've seen the Product Type field is to emulate the merchandising decisions that went into your site's navigation.
Third, Custom Labels are a huge advantage. Price tiers are the first thing I use them for, but they're also handy for color, size, gender information, where applicable, as those dimensions can often uncover a level of distinct behavior above the individual SKU level.
The advantage to using the product group is that it increases your relevance for searches for the child products--such as "size 9 boating shoes" or "gray sailing vest". Further, it gives you the opportunity to split those variants out within the bidding taxonomy (provided you also pipe that data into custom_labels, or additional values in the product_type chain), which can be helpful if some versions carry a different conversion rate.
For example, a client who sells t-shirts split out both color and size, as some colors are vastly more popular, and sometimes the less common sizes will convert better (say, if you're trying to find an XS or XXXL), given the relatively weak competition for those segments.
Thanks for the question. If you have any additional questions about feed structures, Google Merchant Center, AdWords or really anything e-commerce feel free to drop me a line.
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Hey Roy, we have a small business we are looking to grow and are looking for some AdWords growth strategies. We'd love to get to the point where we are spending $100k or so in ad spend (and making money). We can afford a ROAS of 5.6. From what you can see of our account, what are your recommendations? Thanks for any advice you can offer up.
Hey Artie, that's actually an excellent exercise--one that I was putting in some time on recently, which you can read through here.
If we're talking about a 5.6 ROAS or 18% COS (hence the making money caveat), then that would require roughly $556,000 per month in topline revenue. To start with, you only have 2,450 products currently active in Google Shopping. While the impression share (for the past 30 days) is only about 24%, that means that even with an infinite budget, we can only realistically expect to get 2-3x the impressions from the market for those products--nowhere near the 25x increase you're talking about (going from $4k to $100k). I'd say you need to expand your catalog by at least 10x, spreading that net wide enough to capture that many eyeballs (if you'll forgive the mixed metaphor).
If you had ten times as many products, let's assume you could get 15x as much traffic, as the traffic compounds as you build brand recognition, retarget that audience, and continue to tune the site's conversion. If we also get a 25% increase in conversion rate during that time, that gets us to almost 19x the conversion count--a good chunk of the way to the 25x target.
One client I have experience with had 40k products, of which about half are parts which are drop shipped, so the meat of the catalog was probably 25k products. 85% of the company's orders are fulfilled through their own warehouses and inventory. About 100 products made up 50% of the revenue and 800 products made up 85%. If even one of those top products runs into trouble (some jerk blowing them out on Amazon, or the like), it is a big problem for the company. Over the last couple of years, they've worked to continuously explore new products, manufacturers, brands, and categories. Some products would over-mature, the price would drop out, and they'd need to replace it with something new--it was and still is a full time job for two people.
They've managed to spread out revenue to 500 skus making up 50%, and 1,800 skus making up 85%. That's still a lot less than the 25k products in their core catalog, but without those 25k, they would never have found or had the 1800 that really mattered. Also, the long-tail became healthier and healthier as they started to stock anything in that parts catalog that hit some traffic and sales threshold, which also boosted margins.
As I mention in the article, you then need to present the new products as effectively as possible. This includes product photography, but also supporting content (check out some of the videos on this site, for example), and conversion rate optimization. The great thing about CRO is that everything depends on conversion rates, so even a small change there gives you the freedom to do all kinds of things elsewhere in your funnel. For example, if you can amplify your conversion rates by a little, it actually frees you up to consider lowering prices (which has a dollar-for-dollar greater impact on sales than a larger marketing budget, for example), or other strategies. Sites live and die by conversion rates. But there are lots of tools out there that make that easier and easier to work on--but it does take a lot of time and attention. That's part of what I presented on at eTail last year, actually.
But the short answer is that the first step in that direction is to focus on sourcing and merchandising, as you need a lot more products to offer in order to have the draw for an audience that size.
Thanks for the question Artie. Drop me a line if you have any other questions. I love to talk shop.
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Hey Roy, have you had any experience working with the Data Driven Attribution Model in Google AdWords?
Do you have any recommendations on when you'd use it?
Nathan, happy to share my perspective on the Data Driven Attribution Model. Google defines the Data Driven Attribution Model as follows:
Data-driven attribution gives credit for conversions based on how people search for your business and decide to become your customers. It uses data from your account to determine which ads, keywords, and campaigns have the greatest impact on your business goals. You can use data-driven attribution for website and Google Analytics conversions from Search Network campaigns.
You can learn more about the Data Driven Attribution Model by visiting Google's support site.
The Data-Driven is currently a black-box, and I don't trust it. Attribution model and performance are chicken and egg, as the model becomes a self-fulfilling prophecy. If you picked First Click, then you'd invest more into high-funnel campaigns, and then high-funnel campaigns would perform "better", for example. If they're claiming that they can find the combination of model variables that increases the total at the bottom of the funnel, then that'd be cool... but the Conversion Optimizer, eCPC, Ad Optimization, and all of the other "magic black box" features in AdWords generally underperform (or outright fail) for mid-size retail accounts, as far as I've found.
I find that most of the time when Google launches some automated data analysis system that the first 6 months to 1 year are not very good and the early adopters don’t do well unless they have so much data the system can learn very quickly. It seems that it really takes 1-2 years to work the bugs out to where it generally works.
So, let's put it in the "wait and see" category, but I'm very skeptical. Till I see evidence suggesting I'm wrong (which happens from time to time), I'm going to stick with Time Decay.
Thanks for the question Nathan. I love to talk shop so don't hesitate to reach and drop me a line.
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Relationship Between Max CPC Bid, Actual CPC and Impression Share
Hi Roy, I had a question in regard to Max CPC bid, Actual CPC and Impression share. One of our campaigns in PLA has been over-target ROI significantly for a few weeks. Impression share is at the 60% range and I would love to push that into the 80% or more. What’s odd is that our max CPC bids in some cases can be in the $2-$3 range and our average CPC’s end up being in the 30-60 cents range. I did check in on our auction insights and it looks like we greatly outrank our competition in impression share. This implies that CPC’s aren’t being driven up due to lack of competition. I feel a bit skeptical about this though. Any thoughts? I don’t understand why google wouldn’t want to sell me those extra impressions.
When the actual CPCs are coming in much below the Max CPC Bid, then a lack of competition is the first thing that comes to mind to me, as well. While your impression share is strong, it's not so high that I expected to see $2.50 bids coming in at $0.50, though. However, the way you're interacting with other sites in the search auctions is still the only thing that affects CPCs like that, relative to bids.
What this might uncover is an opportunity with the product data, such as the titles. While I'm sure you're feeding in UPCs, it may be possible that Google isn't matching your products with all of the searches that they might be relevant to. For example, if I passed in a bunch of titles that were too short, then I would see apparently reduced competition--along with a significantly reduced impression pool, relative to a feed that was more robust.
Negative keywords can also have an impact so make sure there aren't any overzealous negative keywords limiting you from quality impressions.
Bid adjustments also may play a role in the delta you are seeing between the max CPC and actual CPC. Let's look at a typical mobile bid adjustment. If half of the clicks are mobile and mobile bids are half as much as desktop bids then the total average bid would be 3/4 what it would otherwise be and it wouldn't be reported at all.
Have questions? Drop me a line via the Contact form--I love to talk shop.