A Case For Product Level Bidding
I’ve been futzing around with this post for a week…still a work in progess, but it’s time to post. PLEASE comment.
Since I started looking at the comparison shopping industry 18 months ago, I’ve wondered why the industry hasn’t taken off after 11 years (the intelligent agent, Bargain Finder, was launched by Bruce Krulwich from Arthur Andersen in July of ‘95). Yes, you could definitely make the point that the industry grew up a lot last year with $1.5B in acquisitions, but there’s still a sense that merchants just don’t grok the benefits of using this marketing channel.
If there are 75K merchants advertising on Google Adwords and Yahoo! Search Marketing (a couple people ‘in the know’ have mentioned this number to me, but I have no official confirmation), then why are there only 4K, 8K, or 12K merchants submitting feeds to the shopping comparison engines? I have a lot of theories, and I think it’s a combination of factors, but one idea goes like this:
Without product level knowledge and manipulation capabilities (trademarks of performance marketing systems popularized by Overture and Google), marketers will not flock to shopping comparison engines as there’s no transparent view of marketing performance. By not providing product (SKU) level reporting and bidding, as well as API access to their reporting systems, the shopping comparison engines are holding themselves back.
The point of this post is to defend this theory by providing simple examples that any PPC marketer can understand. The accounting terms have been dumbed down (no nit-picking on the lingo):, and I introduce a fictional shopping comparison enigne called BestestBargainBuys (bbb). Because of this, some of my arguments can and will be picked apart. I expect this and look forward to the ensuing discussion.
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Let’s say you sell widgets online. Here’s an unsophisticated but completely acceptable way to look at the profitability of your widget business:
Revenue = $10000
COGS = $5000
Profit = $5000
Marketing Cost = $4000
Gross Profit = $1000
As opposed to spending the $4000 anywhere, let’s say this widget company advertises online through the pay per click (PPC) engines. Instead of looking at $4000 in marketing costs, the company should dig deeper and look at the profitability of campaigns/categories or even better, keywords. The analytics systems on Google Adwords and Yahoo! Search Marketing (YSM) allow for this type of tracking.
The benefit? As opposed to spending $4000 on a hit-or-miss advertising campaign, the marketer can determine the profitability of individual keywords to optimize the marketing campaign; decreasing the bids of keywords that are not converting well and increasing the bids of keywords that are converting well. And with automated systems that bid towards some type of acquisition goal, marketers can sit back and watch the money roll in.
Ok, it’s not that easy, but sophisticated marketers (working on their own or through agencies) on Google and Yahoo! make a call through an API to quickly and efficiently grab # of clicks, cost per click, etc. in almost real time. This data is then matched up with revenue to provide a complete picture of return on investment (ROI) [remember, no nit-picking on the accounting lingo]. Marketers then act on the data, taking advantage of the open nature of Google and Yahoo!, and the dynamic auction style bidding systems that are the foundation of PPC marketing.
The unsophisticated marketer can make a go on the PPC engines, but without matching up granular marketing costs with associated revenues, the little guy will always leave money on the table or worse yet, stop advertising.
Let’s say a marketer who has been using the PPC engines for a while decides to venture into shopping comparison engine land. The merchant chooses Yahoo! Shopping and BestestBargainBuys (bbb). The merchant uses the simple pixel tracking [a crude and often incorrect measure of real performance] on bbb to figure out the overall effectiveness of the channel. Yahoo! Shopping (or rather Yahoo! Product Submit) does not provide pixel tracking so the marketer is pretty much happy as long as marketing cost is not greater than profit (as defined at the beginning of this post). This is blind marketing (and troublesome if the marketer is using multiple channels), but it might work for the unsophisticated marketer.
Whether on Yahoo! or bbb, the merchant is in trouble as clicks are only tracked on a category basis and not on a product or SKU level. The unsophisticated marketer might be fine with this. Again, as long as Profit - Marketing Cost > $0, he’s happy.
The sophisticated marketer, though, realizes that out of the 20 unique widgets submitted to bbb, he has no way to tell which widgets are converting at profitable rates. Just as in PPC marketing where the marketer tracks keyword level effectiveness, in shopping comparison engine marketing, the marketer should be tracking SKU level effectiveness. But bbb doesn’t allow for this.
So what does the sophisticated marketer do? He appends click through URLs with &src=bbb (source = bbb) or adds re-directs and programs his log analyzer to track this information. A workable solution. Now the sophisticated marketer needs to get cost data from bbb which means he has to login to bbb on a daily basis and run a report as there’s no API available.
The smart marketer puts all the pieces together, figures out that of 20 products, 12 are running at a loss on bbb. The marketer wants to immediately act on this insightful information. If he’s a PPC marketer, he’ll want to lower bids on the unprofitable listings not by category, but by SKU. Unfortunately, bbb doesn’t allow this.
So what does the sophisticated marketer do? He a) looks at his listings on bbb as a portfolio and continues to list all his products (as long as his spend is less than his profit), b) re-negotiates new minimum bid levels with bbb (which is only going to happen with significant spend…but how do you get to a significant spend if you’re losing money on more than half of you clicks?), or c) takes down 12 of his listings. I have a feeling option C is very popular.
At the same time, of the 8 listings that are performing well on bbb, the sophisticated marketer knows that he can increase his bids for 4 of those listings, get top placement, and drive additional profitable sales. Unfortunately, as we know, bbb does not offer product level bidding, so he chooses to leave his bids the same and looses out on additional sales.
Hopefully you now understand the power of SKU level performance information and bidding capabilities. Of the major shopping comparison engines, only NexTag and Shopzilla provide product level performance information (clicks) and product level bidding capabilities. Multiple engines offer product level performance information but not product level bidding capabilities.
I’m not really a conspiracy theorist, but not providing product level bidding is at the least irresponsible and at the worst an attempt to hide a significant waste of marketing dollars. I’d guess that only 25% of shopping comparison engine advertisers are ’sopshisticated’ enough to really get down to product level performance tracking. That means that 75% of marketers are wasting money…or maybe it’s even more as the ’sophisticated’ marketers might be going for the portfolio strategy as opposed to negotiating lower minimums or deleting unprofitable listings.
To sum this up, an industry expert emailed me:
“Some Comparison Shopping Engines (CSEs) give you a simple rate-card for category CPC, so as a merchant the only way you have to manage ROI is to cut products from the feed. This results in a bad experience for everyone:
CSEs – bad selection, less revenue
Merchants – limited selection at CSE
Consumers – limited experience
By allowing (and providing the info for) SKU-level bidding it gives the merchant the power to say – I’ll pay a lot for X, average for Y and below average for Z, but keep my entire catalog at the CSE.”
Similarly, another expert explained “allowing for product level bidding would smooth out revenue and product coverage.” Smart marketers upload a ton of products, get lots of clicks, then realize that the channel as a whole isn’t meeting performance metrics and therefore must take down the entire feed. At the same time, revenue for the shopping comparison engine spikes really quickly and then drops off just as quickly as merchants deactivate their listings.
So here are a couple recommendations for some shopping comparison engines
1. Add pixel tracking (as a first step) and educate consumers about intelligently tracking results (accounting for double counting – are sales from bbb and Adwords?)
2. Add product level performance information (including the ability to sort/filter SKUs)
3. Follow NexTag and Shopzilla’s lead and add product level bidding capabilities
4. Follow YSM and Google’s lead and develop APIs to allow merchants (and agencies) to call account information in real-time.
Steps 2 - 4 have the potential to open up the floodgates for business both in terms of new merchants and just as important, more intense usage by current merchants.

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