| Title: | PurchaseMatch: How GOOG Could Hit $750, or How Yahoo / Microsoft Could Best Google |
| URL: | http://www.rimmkaufman.com/rkgblog/2008/04/13/purchase-match/ |
| Printed: | July 4, 2009 |
| Source: | The Rimm-Kaufman Group Blog, info@rimmkaufman.com |
- April 13, 2008
- 8 comments
Here’s my advice that, adopted by Google, could add 50% to their valuation.
Or if adopted by Yahoo or Microsoft, it could put them back in the game.
Let advertisers bid a premium for clicks from users with a recent online purchase.
Tomorrow I have post coming out at SEL arguing that the wisdom of the direct mail greats can teach us paid search marketers a great deal.
In other words: if the likes of Claude Hopkins, Albert Lasker, John Caples, David Ogilvy, Leo Burnett, and Maxwell Sackheim were alive today, they’d be (a) buying AdWords, and (b) kicking butt.
In the SEL post, I turned up my nose at demographic targeting for paid search.
Direct marketers have long known that demographics do a weak job of predicting response, whereas purchase recency does an incredible job.
I mentioned this idea in passing on the SEL post and wanted to expand on the notion further here.
Privacy concerns aside for the moment, consider the following proposal:
- This hypothetical program is called PurchaseMatch. (I just made that up.)
- Advertisers are only eligible participate in PurchaseMatch if they share conversion data with the search engine. (Hattip, Tony White and Abacus.) For Google, an Adwords conversion tag or Google analytics tag would qualify.
- PurchaseMatch is optional; eligible advertisers don’t have to use it.
- Just as advertisers today have the option to bid at the AdGroup level (dumb) or at the keyword level (smart), advertisers would have the ability to differentiate their bids by sixteen different PurchaseMatch segments.
- Here are proposed PurchaseMatch segments:
Days Since Last Purchase EXACT match PHRASE match BROAD match NON match Today E1 P1 B1 N1 This Week E7 P7 B7 N7 This Month E30 P30 B30 N30 This Year E365 P365 B365 N365 Here’s an example to clarify. Suppose you’re advertising the phrase “Canon Digital Camera”.
- If the engine detects the SERP was served to a user who bought anything at all online in the last year, that’d be a N365 user.
- If the user had bought anything online in the last 30 days, that would also be a N30 user.
- If the user had bought from an online store after clicking on an ad that broad matched “Canon Digital Camera” in the last 30 days, that would also be a B30 user.
- If the user had bought from an online store in the last week following a click on an ad which exact matched “Canon Digital Camera”, that would be a E7 user.
- The core idea: let advertisers bid more for ads based on user type, where the user type is a combination of purchase recency (day, week, month, year) and ad phrase relevance (exact match click before purchase, phrase match click before purchase, broad match click before purchase, any paid click before purchase).
Yes, this is too complicated. Smarter folks than me could likely simplify it intelligently.
But bidding by purchase recency would be marketing rocket fuel.
If, say, the economics of the phrase “Canon Digital Camera” made sense for a retailer today at $1.00 CPC, I’d guessing that under PurchaseMatch they’d be delighted to bid something like this:
| Days Since Last Purchase | EXACT match | PHRASE match | BROAD match | NON match |
| Today | E1: $20 |
P1: $14 |
B1: $10 |
N1: $5 |
| This Week | E7: $10 |
P7: $5 |
B7: $4 |
N7: $4 |
| This Month | E30: $5 |
P30: $4 |
B30: $3 |
N30: $2.50 |
| This Year | E365: $1.75 |
P365: $1.50 |
B365: $1.50 |
N365: $1.20 |
Of course, I just made those bids up.
If PurchaseMatch existed, smart bid management algorithms would use statistical optimization to determine the relative value of inbound clicks from different segments of users, and bid accordingly.
But I have no doubt that data would show that smart retailers could pay twenty-fold more for an E1 click versus what they’d pay for a generic click.
Some of you might be scratching your heads and thinking, “Hey, shouldn’t your guess for the value of an E1 be worth less than a E30, because the person just bought the widget and so have no need for another one for some while?” While that makes intuitive sense, in almost every case classic RFM has shown that response rate monotonically decreases with increasing R.
Others might be scratching their hands thinking, “Hey, why should the engines optimize for the direct response crew, as DR is only 10% of total US adspend, and the general advertising folks who comprise the 90% love their demographics?” I’d answer that I think Larry Page is right: the future of advertising belongs to direct.
And I think the privacy issues could be surmounted…
What do you think?
As a direct marketer, would you bid a premium based on recency data? Why or why not?
As a consumer, is PurchaseMatch just too creepy? Why or why not?
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I, as a consumer, would love PurchaseMatch.
Alan, spot on piece and nice touch to provide the pricing “ladder”. That’s what I would expect too - at the very least the relationships between the prices would look very similar.
I always thought this was one reason why Google launched a cart, to get more detail on purchase behavior. But it sure has been a while since they launched conversion tracking, I wonder why it’s taking them so long to do any purchase scoring? Privacy, I guess…
Seems like it would be really easy to start out with a “HotLine” service just like we have offline. Either you purchased something in the past 30 days or not, by category. That seems like a pretty privacy-friendly approach.
Could get into the finer scoring issues later on…
It’s an interesting idea, and Google’s already made it clear that they’ll be working to get more and more conversion data through Checkout, Conversion Optimizer and possibly Performics’ affiliate business.
It won’t add $50B to G’s market cap, though, for the same reason that the rise of Broad Match has failed to stem the flight of tens of billions in GOOG market cap these past few quartesr. [And I say that with the most profound respect for G's broad match vs that of other SE's.]
What took Google from $50B to $100B+ in market cap was growth in market share domestically and internationally, and increased # of searches per searcher during that time. Now that Google’s a monopoly in Europe and a near-monopoly in the U.S., market share growth, while not over, has diminished greatly from its heydey. Likewise, monetization improvements (both evil and non-evil ones…) haven’t stemmed the tide.
An offering that allows advertisers to bid more for more likely to convert searchers will surely happen in some way, shape, or form, but I seriously doubt that it will overcome the giant’s slowing growth. We as an industry haven’t really even *begun* to talk about how overvalued search traffic is, but we will once our nascent web analytics deployments start to tell us that other non-last-touch channels deserve 20-30-40% of the credit for a transaction for which search was the ‘last click’.
So IMO monetization improvements of the type you foresee will be overshadowed by more negative developments G will have to contend with. What will add $50B to G’s market cap is the rising tide of conversion rates that web analytics and conversion testing will bring about, but that’s gonna take quarters & years and will have less to do with free Google products, and more to do with marketers getting trained and/or paying partners to help them.
@BetterRetail — Why would you like this as a consumer? Should be invisible to searchers… explain?
@JimNovo — “Either you purchased something in the past 30 days or not, by category” — rather than trying to impose an ad-hoc categorization, I was trying to use the specificity of the search phrase match for the categorization.
@ChrisZ — Thanks for your long and thoughtful comment. I am so not the stock guru or a valuation guy, but here’s my scribbled napkin logic for the $750 guestimate: if some advertisers would pay 20x more, that might translate to an overall doubling of eCPM, effectively doubling G revenues (over what period?), leading to (?) +50% in valuation. You’re right though, larger forces could move Google’s value downward more significantly. OK, no more stock pontificating or headline baiting, back to real work now, where I have some better clue as to what I doing. :)
Hi Alan: As a consumer I feel most online advertising is wasteful in that it doesn’t actually make me want to buy. Your suggested approach allows advertisers to better target me and that makes my life easier.
Alan, this is a clever idea indeed. My two cents:
1) As a consumer I would find it a slightly creepy proposition. Basically, this is “behavioral targeting,” and as with the Facebook “Beacon” debacle, consumers are touchy about how their past behaviors are tracked and used to serve up custom advertising. Picture a shared computer where a spouse or coworker’s purchase history included borderline pornography, or prescription meds for a sensitive medical or psychological condition. It doesn’t have to be a shared computer to make broad-matched custom ads of that nature disturbing. No doubt Google could apply a smart relevancy algorithm, but the financial model would likely motivate some loose and awkward matches in pursuit of dollars.
2) As a marketer, I’d be interested. I do have a gut feeling that some sorts of recency are counter-indicators for another purchase, but you point out that classic RFM analysis says otherwise. I’d sure want to understand how recent purchasers migrate from one brand to another. For instance, in search-engine advertising today, your cheapest and best-converting ads are for your own brand-name terms, and it seems fair to keep it that way. Maybe Google deserves a premium for delivering “recent buyers” from your online rivals — but I’d be loathe to pay a premium for my own recent buyers (i.e. existing customers).
@Tom — you wrote:
“For instance, in search-engine advertising today, your cheapest and best-converting ads are for your own brand-name terms, and it seems fair to keep it that way. Maybe Google deserves a premium for delivering “recent buyers” from your online rivals”
Right. And to Jim’s comment about type of recency — eg purchase by category — that’s what got me to thinking about using the actual search phrase, along with its match type, to clarify type of purchase.
Cheers
Alan
To me the purchase category is less interesting than simply the fact of the purchase. To me, the category interest is revealed by the search phrase and the only interesting piece beyond that is whether this “person” actually buys stuff online, or are they people who research online and buy at their local store.
I’ve suggested this type of option to reps from Google, Yahoo and MSN several times over the last year or two. To this point the response has been: “We like the idea, but privacy concerns make it impossible.”
I think enlightened users would learn that by advertising to buyers and not to non-buyers online shoppers would get the benefit of targeted ads and those who wish to research wouldn’t be hassled by ads they don’t want to see. A win-win for consumers.
However, the engines might end up getting higher cpcs for some clicks, lower for others ending up in a wash, and that math may discourage them from pursuing the legal/privacy concerns.